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Ganguly AP, Alvarez KS, Mathew SR, Soni V, Vadlamani S, Balasubramanian BA, Bhavan KP. Intersecting social determinants of health among patients with childcare needs: a cross-sectional analysis of social vulnerability. BMC Public Health 2024; 24:639. [PMID: 38424507 PMCID: PMC10902938 DOI: 10.1186/s12889-024-18168-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 02/21/2024] [Indexed: 03/02/2024] Open
Abstract
INTRODUCTION Access to childcare is an understudied social determinant of health (SDOH). Our health system established a childcare facility for patients to address childcare barriers to healthcare. Recognizing that social risk factors often co-exist, we sought to understand intersecting social risk factors among patients with childcare needs who utilized and did not utilize the childcare facility and identify residual unmet social needs alongside childcare needs. METHODS We conducted a cross-sectional analysis of patients who enrolled in the childcare facility from November 2020 to October 2022 to compare parameters of the Social Vulnerability Index (SVI) associated with the census tract extracted from electronic medical record (EMR) data among utilizers and non-utilizers of the facility. Overall SVI and segmentation into four themes of vulnerability (socioeconomic status, household characteristics, racial/ethnic minority status, and housing type/transportation) were compared across utilizers and utilizers. Number of 90th percentile indicators were also compared to assess extreme levels of vulnerability. A sample of utilizers additionally received a patient-reported social needs screening questionnaire administered at the childcare facility. RESULTS Among 400 enrollees in the childcare facility, 70% utilized childcare services and 30% did not. Utilizers and non-utilizers were demographically similar, though utilizers were more likely to speak Spanish (34%) compared to non-utilizers (22%). Mean SVI was similar among utilizers and non-utilizers, but the mean number of 90th percentile indicators were higher for non-utilizers compared to utilizers (4.3 ± 2.7 vs 3.7 ± 2.7, p = 0.03), primarily driven by differences in the housing type/transportation theme (p = 0.01). Non-utilizers had a lower rate of healthcare utilization compared to utilizers (p = 0.02). Among utilizers who received patient-reported screening, 84% had one unmet social need identified, of whom 62% agreed for additional assistance. Among social work referrals, 44% were linked to social workers in their medical clinics, while 56% were supported by social work integrated in the childcare facility. CONCLUSIONS This analysis of SDOH approximated by SVI showed actionable differences, potentially transportation barriers, among patients with childcare needs who utilized a health system-integrated childcare facility and patients who did not utilize services. Furthermore, residual unmet social needs among patients who utilized the facility demonstrate the multifactorial nature of social risk factors experienced by patients with childcare needs and opportunities to address intersecting social needs within an integrated intervention. Intersecting social needs require holistic examination and multifaceted interventions.
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Affiliation(s)
- Anisha P Ganguly
- Center of Innovation and Value, Parkland Health, Dallas, TX, USA.
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- Health Equity Fellow, Parkland Health, 5200 Harry Hines Blvd, Dallas, TX, 75235, USA.
| | | | - Sheryl R Mathew
- Center of Innovation and Value, Parkland Health, Dallas, TX, USA
| | - Virali Soni
- Center of Innovation and Value, Parkland Health, Dallas, TX, USA
| | - Suman Vadlamani
- School of Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
- Institute for Implementation Science, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
| | - Kavita P Bhavan
- Center of Innovation and Value, Parkland Health, Dallas, TX, USA
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Rodriguez SA, Lee SC, Higashi RT, Chen PM, Eary RL, Sadeghi N, Santini N, Balasubramanian BA. Factors influencing implementation of a care coordination intervention for cancer survivors with multiple comorbidities in a safety-net system: an application of the Implementation Research Logic Model. Implement Sci 2023; 18:68. [PMID: 38049844 PMCID: PMC10694894 DOI: 10.1186/s13012-023-01326-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 11/24/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND Under- and uninsured cancer survivors have significant medical, social, and economic complexity. For these survivors, effective care coordination between oncology and primary care teams is critical for high-quality, comprehensive care. While evidence-based interventions exist to improve coordination between healthcare teams, testing implementation of these interventions for cancer survivors seen in real-world safety-net settings has been limited. This study aimed to (1) identify factors influencing implementation of a multicomponent care coordination intervention (nurse coordinator plus patient registry) focused on cancer survivors with multiple comorbidities in an integrated safety-net system and (2) identify mechanisms through which the factors impacted implementation outcomes. METHODS We conducted semi-structured interviews (patients, providers, and system leaders), structured observations of primary care and oncology operations, and document analysis during intervention implementation between 2016 and 2020. The practice change model (PCM) guided data collection to identify barriers and facilitators of implementation; the PCM, Consolidated Framework for Implementation Research, and Implementation Research Logic Model guided four immersion/crystallization data analysis and synthesis cycles to identify mechanisms and assess outcomes. Implementation outcomes included appropriateness, acceptability, adoption, and penetration. RESULTS The intervention was appropriate and acceptable to primary care and oncology teams based on reported patient needs and resources and the strength of the evidence supporting intervention components. Active and sustained partnership with system leaders facilitated these outcomes. There was limited adoption and penetration early in implementation because the study was narrowly focused on just breast and colorectal cancer patients. This created barriers to real-world practice where patients with all cancer types receive care. Over time, flexibility intentionally designed into intervention implementation facilitated adoption and penetration. Regular feedback from system partners and rapid cycles of implementation and evaluation led to real-time adaptations increasing adoption and penetration. DISCUSSION Evidence-based interventions to coordinate care for underserved cancer survivors across oncology and primary care teams can be implemented successfully when system leaders are actively engaged and with flexibility in implementation embedded intentionally to continuously facilitate adoption and penetration across the health system.
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Affiliation(s)
- Serena A Rodriguez
- Department of Health Promotion & Behavioral Sciences, School of Public Health, The University of Texas Health Science Center at Houston (UTHealth Houston), 2777 North Stemmons Freeway, Dallas, TX, 75207, USA.
- Center for Health Promotion & Prevention Research, UTHealth Houston School of Public Health, 7000 Fannin, Houston, TX, 77030, USA.
- UTHealth Houston Institute for Implementation Science, 2777 North Stemmons Freeway, Dallas, TX, 75207, USA.
| | - Simon Craddock Lee
- Department of Population Health, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA
- University of Kansas Cancer Center, 2650 Shawnee Mission Parkway, Westwood, KS, 66205, USA
| | - Robin T Higashi
- Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Patricia M Chen
- Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Rebecca L Eary
- Department of Family and Community Medicine, University of Texas Southwestern Medical Center, 5939 Harry Hines Blvd., Suite 303, Dallas, TX, 75390, USA
| | - Navid Sadeghi
- Department of Internal Medicine, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, 6202 Harry Hines Blvd, Dallas, TX, 75235, USA
- Parkland Health, 5200 Harry Hines Blvd, Dallas, TX, 75235, USA
| | - Noel Santini
- Department of Internal Medicine, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
- Parkland Health, 5200 Harry Hines Blvd, Dallas, TX, 75235, USA
| | - Bijal A Balasubramanian
- Center for Health Promotion & Prevention Research, UTHealth Houston School of Public Health, 7000 Fannin, Houston, TX, 77030, USA
- UTHealth Houston Institute for Implementation Science, 2777 North Stemmons Freeway, Dallas, TX, 75207, USA
- Department of Epidemiology, Human Genetics & Environmental Sciences, UTHealth Houston School of Public Health, 2777 North Stemmons Freeway, Dallas, TX, 75207, USA
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Betts AC, Murphy CC, Shay LA, Balasubramanian BA, Markham C, Roth ME, Allicock M. Polypharmacy and medication fill nonadherence in a population-based sample of adolescent and young adult cancer survivors, 2008-2017. J Cancer Surviv 2023; 17:1688-1697. [PMID: 36346577 PMCID: PMC10164839 DOI: 10.1007/s11764-022-01274-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/11/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE We examined the association between polypharmacy-an established risk factor for nonadherence in the elderly-and medication fill nonadherence in a large national sample of adolescent and young adult cancer survivors (AYAs) in the USA. METHODS We pooled data (2008-2017) from the Medical Expenditure Panel Survey. We defined polypharmacy as ≥ 3 unique medications prescribed, based on self-report and pharmacy data, and medication fill nonadherence as self-reported delay or inability to obtain a necessary medication. We estimated prevalence of medication fill nonadherence among AYAs (age 18-39 years with a cancer history). We used logistic regression to estimate the association between (1) polypharmacy and medication fill nonadherence in AYAs, and (2) total number of medications prescribed and medication fill nonadherence, controlling for sex, number of chronic conditions, disability, and survey year. RESULTS AYAs (n = 598) were predominantly female (76.2%), age 30-39 years (64.9%), and non-Hispanic White (72.1%). Nearly half were poor (19.0%) or near-poor/low income (21.6%). One in ten AYAs reported medication fill nonadherence (9.75%). Of these, more than 70% cited cost-related barriers as the reason. AYAs with polypharmacy had 2.49 times higher odds of medication fill nonadherence (95%CI 1.11-5.59), compared to those without polypharmacy. Odds of medication fill nonadherence increased by 16% with each additional medication prescribed (AOR 1.16, 95% CI 1.07-1.25). CONCLUSIONS Polypharmacy may be an important risk factor for medication fill nonadherence in AYAs in the USA. IMPLICATIONS FOR CANCER SURVIVORS Improving AYAs' medication adherence requires eliminating cost-related barriers, particularly for those with polypharmacy.
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Affiliation(s)
- Andrea C Betts
- Department of Health Promotion and Behavioral Sciences, University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Dallas, TX, USA.
| | - Caitlin C Murphy
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Houston, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Houston, TX, USA
| | - L Aubree Shay
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, San Antonio, TX, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Dallas, TX, USA
| | - Christine Markham
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Houston, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Houston, TX, USA
| | - Michael E Roth
- Division of Pediatrics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Marlyn Allicock
- Department of Health Promotion and Behavioral Sciences, University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Dallas, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Dallas, TX, USA
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Jetelina KK, Lee SC, Booker-Nubie QS, Obinwa UC, Zhu H, Miller ME, Sadeghi N, Dickerson U, Balasubramanian BA. Importance of primary care for underserved cancer patients with multiple chronic conditions. J Cancer Surviv 2023; 17:1276-1285. [PMID: 34984632 PMCID: PMC9320948 DOI: 10.1007/s11764-021-01159-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 12/22/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE To understand the impact of pre-existing conditions on healthcare utilization among under- and uninsured patients in the transition from cancer treatment to post-treatment survivorship. METHODS Using electronic health record data, we constructed a cohort of patients seen in an integrated county health system between 1/1/2010 and 12/31/2016. Six hundred thirty-one adult patients diagnosed with non-metastatic breast or colorectal cancer during this period (cases) were matched 1:1 on sex and Charlson comorbidity index to non-cancer patients who had at least two chronic conditions and with at least one visit to the health system during the study period (controls). Conditional fixed effects Poisson regression models compared number of primary care and emergency department (ED) visits and completed [vs. no show or missed] appointments between cancer and non-cancer patients. RESULTS Cancer patients had significantly lower number of visits compared with non-cancer patients (N = 46,965 vs. 85,038). Cancer patients were less likely to have primary care (IRR = 0.25; 95% CI: 0.24, 0.27) and ED visits (IRR = 0.57; 95% CI: 0.50, 0.64) but more likely to complete a scheduled appointment (AOR = 4.83; 95% CI: 4.32, 5.39) compared with non-cancer patients. Cancer patients seen in primary care at a higher rate were more likely to visit the ED (IRR = 2.06; 95% CI: 1.52, 2.80) than those seen in primary care at a lower rate. CONCLUSION Health systems need to find innovative, effective solutions to increase primary care utilization among cancer patients with chronic care conditions to ensure optimal management of both chronic conditions and cancer. IMPLICATIONS FOR CANCER SURVIVORS Maintaining regular connections with primary care providers during active cancer treatment should be promoted.
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Affiliation(s)
- Katelyn K Jetelina
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA
| | - Simon Craddock Lee
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA.
- Department of Population and Data Sciences, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA.
| | - Quiera S Booker-Nubie
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX, USA
| | - Udoka C Obinwa
- Dallas Department of Health and Human Services, Dallas, TX, USA
| | - Hong Zhu
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA
- Department of Population and Data Sciences, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA
| | - Michael E Miller
- Department of Population and Data Sciences, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA
| | - Navid Sadeghi
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA
- Department of Internal Medicine, Division of Hematology/Oncology, UT Southwestern Medical Center, Dallas, TX, USA
- Parkland Health & Hospital System, Dallas, TX, USA
| | | | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 5323 Harry Hines Blvd, MSC 9066, Dallas, TX, 75390-9066, USA
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Roberts MM, Marino M, Wells R, Atem FD, Balasubramanian BA. Differences in Use of Clinical Decision Support Tools and Implementation of Aspirin, Blood Pressure Control, Cholesterol Management, and Smoking Cessation Quality Metrics in Small Practices by Race and Sex. JAMA Netw Open 2023; 6:e2326905. [PMID: 37531106 PMCID: PMC10398408 DOI: 10.1001/jamanetworkopen.2023.26905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 06/22/2023] [Indexed: 08/03/2023] Open
Abstract
Importance Practice-level evidence is needed to clarify the value of population-based clinical decision support (CDS) tools in reducing racial and sex disparities in cardiovascular care. Objective To evaluate the association between CDS tools and racial and sex disparities in the aspirin use, blood pressure control, cholesterol management, and smoking cessation (ABCS) care quality metrics among smaller primary care practices. Design, Setting, and Participants This cross-sectional study used practice-level data from the Agency for Healthcare Research and Quality-funded EvidenceNOW initiative. The national initiative from May 1, 2015, to April 30, 2021, spanned 12 US states and focused on improving cardiovascular preventive care by providing quality improvement support to smaller primary care practices. A total of 576 primary care practices in EvidenceNOW submitted both survey data and electronic health record (EHR)-derived ABCS data stratified by race and sex. Main Outcomes and Measures Practice-level estimates of disparities between Black and White patients and between male and female patients were calculated as the difference in proportions of eligible patients within each practice meeting ABCS care quality metrics. The association between CDS tools (EHR prompts, standing orders, and clinical registries) and disparities was evaluated by multiply imputed multivariable models for each CDS tool, adjusted for practice rurality, ownership, and size. Results Across the 576 practices included in the analysis, 219 (38.0%) had patient panels that were more than half White and 327 (56.8%) had panels that were more than half women. The proportion of White compared with Black patients meeting metrics for blood pressure (difference, 5.16% [95% CI, 4.29%-6.02%]; P < .001) and cholesterol management (difference, 1.49% [95% CI, 0.04%-2.93%] P = .04) was higher; the proportion of men meeting metrics for aspirin use (difference, 4.36% [95% CI, 3.34%-5.38%]; P < .001) and cholesterol management (difference, 3.88% [95% CI, 3.14%-4.63%]; P < .001) was higher compared with women. Conversely, the proportion of women meeting practice blood pressure control (difference, -1.80% [95% CI, -2.32% to -1.28%]; P < .001) and smoking cessation counseling (difference, -1.67% [95% CI, -2.38% to -0.95%]; P < .001) metrics was higher compared with men. Use of CDS tools was not associated with differences in race or sex disparities except for the smoking metric. Practices using CDS tools showed a higher proportion of men meeting the smoking counseling metric than women (coefficient, 3.82 [95% CI, 0.95-6.68]; P = .009). Conclusions and Relevance The findings of this cross-sectional study suggest that practices using CDS tools had small disparities that were not statistically significant, but CDS tools were not associated with reductions in disparities. More research is needed on effective practice-level interventions to mitigate disparities.
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Affiliation(s)
- Madeline M. Roberts
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston (UTHealth Houston) School of Public Health, Dallas
| | - Miguel Marino
- Department of Family Medicine, Oregon Health & Science University, Portland
- School of Public Health, Oregon Health & Science University, Portland
| | - Rebecca Wells
- Department of Management, Policy, & Community Health, UTHealth Houston School of Public Health, Houston
| | - Folefac D. Atem
- Department of Biostatistics and Data Science, UTHealth Houston School of Public Health, Dallas
| | - Bijal A. Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston (UTHealth Houston) School of Public Health, Dallas
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Betts AC, Murphy CC, Shay LA, Balasubramanian BA, Markham C, Allicock M. Polypharmacy and prescription medication use in a population-based sample of adolescent and young adult cancer survivors. J Cancer Surviv 2023; 17:1149-1160. [PMID: 34997910 PMCID: PMC10614319 DOI: 10.1007/s11764-021-01161-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/22/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE We examined prescription medication use and identified correlates of polypharmacy-taking multiple medications-in adolescent and young adult cancer survivors (AYAs), who experience early-onset chronic conditions. METHODS Our cross-sectional study pooled data (2008-2017) from the national Medical Expenditure Panel Survey. We estimated prevalence of polypharmacy (≥ 5 unique prescription medications over an approximate 1-year period) in AYAs (age 18-39 years with a history of cancer) and age- and sex-matched controls, overall and by sociodemographics, clinical factors, and health indicators. We compared survivors' and controls' medication use across therapeutic classes. To identify correlates of polypharmacy among AYAs, we included factors with p < 0.20 in bivariable analysis in a multivariable logistic regression model. RESULTS AYAs (n = 601) had a higher prevalence of polypharmacy than controls (n = 2,402), overall (31.5% vs. 15.9%, p < .01) and by all sociodemographics, clinical factors, and health indicators. A majority of AYAs with multiple chronic conditions (58.8%, 95% CI 47.3-70.4) or disability (61.3%, 95% CI 52.6-70.0) had polypharmacy. Patterns of AYAs' medication use across therapeutic classes were consistent with their chronic conditions. Nearly one-third used opioid/narcotic analgesics (32.2% vs. 13.7% of controls, p < 0.01). Among AYAs, multiple chronic conditions (aOR 4.68, 95% CI 2.23-9.83) and disability (aOR 3.70, 95% CI 2.23-6.14) were correlated with polypharmacy. CONCLUSIONS Chronic conditions and disabilities, including aftereffects of cancer treatment, may drive polypharmacy in AYAs. Future research should examine adverse outcomes of polypharmacy and opioid/narcotic use in AYAs. IMPLICATIONS FOR CANCER SURVIVORS AYAs with chronic conditions or disabilities should be monitored for polypharmacy.
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Affiliation(s)
- Andrea C Betts
- Department of Health Promotion and Behavioral Sciences, School of Public Health, University of Texas Health Science Center at Houston (UTHealth), 2777 N. Stemmons Fwy., Ste. 8400, Dallas, TX, 75207, USA.
| | - Caitlin C Murphy
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Houston, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Houston, TX, USA
| | - L Aubree Shay
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, San Antonio, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Houston, TX, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Dallas, TX, USA
| | - Christine Markham
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Houston, TX, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Houston, TX, USA
| | - Marlyn Allicock
- Department of Health Promotion and Behavioral Sciences, School of Public Health, University of Texas Health Science Center at Houston (UTHealth), 2777 N. Stemmons Fwy., Ste. 8400, Dallas, TX, 75207, USA
- Center for Health Promotion and Prevention Research, UTHealth School of Public Health, Dallas, TX, USA
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Whigham LD, Messiah SE, Balasubramanian BA, Dhurandhar NV. The essential role of primary care providers in obesity management. Int J Obes (Lond) 2023; 47:249-250. [PMID: 36792911 DOI: 10.1038/s41366-023-01268-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 11/18/2022] [Accepted: 01/25/2023] [Indexed: 02/17/2023]
Affiliation(s)
- Leah D Whigham
- Center for Community Health Impact and Department of Health Promotion & Behavioral Sciences, The University of Texas Health Science Center at Houston, School of Public Health El Paso, El Paso, TX, USA.
| | - Sarah E Messiah
- Department of Epidemiology, Human Genetics & Environmental Sciences, The University of Texas Health Science Center at Houston, School of Public Health Dallas, Dallas, TX, USA.,Center for Pediatric Population Health, The University of Texas Health Science Center at Houston, School of Public Health, Dallas, TX, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics & Environmental Sciences, The University of Texas Health Science Center at Houston, School of Public Health Dallas, Dallas, TX, USA.,UTHealth Houston Institute for Implementation Science, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
| | - Nikhil V Dhurandhar
- Department of Nutritional Sciences, Texas Tech University, Lubbock, TX, USA.
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Cohen DJ, Balasubramanian BA, Lindner S, Miller WL, Sweeney SM, Hall JD, Ward R, Marino M, Springer R, McConnell KJ, Hemler JR, Ono SS, Ezekiel-Herrera D, Baron A, Crabtree BF, Solberg LI. How Does Prior Experience Pay Off in Large-Scale Quality Improvement Initiatives? J Am Board Fam Med 2022:jabfm.2022.AP.220088. [PMID: 36113993 DOI: 10.3122/jabfm.2022.ap.220088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/21/2022] [Accepted: 06/23/2022] [Indexed: 03/21/2023] Open
Abstract
INTRODUCTION To examine the association of prior investment on the effectiveness of organizations delivering large-scale external support to improve primary care. METHODS Mixed-methods study of 7 EvidenceNOW grantees (henceforth, Cooperatives) and their recruited practices (n = 1720). Independent Variable: Cooperatives's experience level prior to EvidenceNOW, defined as a sustained track record in delivering large-scale quality improvement (QI) to primary care practices (high, medium, or low). Dependent Variables: Implementation of external support, measured as facilitation dose; effectiveness at improving (1) clinical quality, measured as practices' performance on Aspirin, Blood Pressure, Cholesterol, and Smoking (ABCS); and (2) practice capacity, measured using the Adaptive Reserve (AR) score and Change Process Capacity Questionnaire (CPCQ). Data were analyzed using multivariable linear regressions and a qualitative inductive approach. RESULTS Cooperatives with High (vs low) levels of prior experience with and investment in large-scale QI before EvidenceNOW recruited more geographically dispersed and diverse practices, with lower baseline ABCS performance (differences ranging from 2.8% for blood pressure to 41.5% for smoking), delivered more facilitation (mean=+20.3 hours, P = .04), and made greater improvements in practices' QI capacity (CPCQ: +2.04, P < .001) and smoking performance (+6.43%, P = .003). These Cooperatives had established networks of facilitators at the start of EvidenceNOW and leadership experienced in supporting this workforce, which explained their better recruitment, delivery of facilitation, and improvement in outcomes. DISCUSSION Long-term investment that establishes regionwide organizations with infrastructure and experience to support primary care practices in QI is associated with more consistent delivery of facilitation support, and greater improvement in practice capacity and some clinical outcomes.
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Affiliation(s)
- Deborah J Cohen
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS).
| | - Bijal A Balasubramanian
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Stephan Lindner
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - William L Miller
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Shannon M Sweeney
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Jennifer D Hall
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Rikki Ward
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Miguel Marino
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Rachel Springer
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - K John McConnell
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Jennifer R Hemler
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Sarah S Ono
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - David Ezekiel-Herrera
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Andrea Baron
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Benjamin F Crabtree
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
| | - Leif I Solberg
- From Department of Family Medicine and Department of Medical and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB, RW); Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Family Medicine, Oregon Health & Science University Portland, OR (SMS, JDH, MM, RS, DE-H, AB); Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Department of Psychiatry and Department of Family Medicine, Oregon Health & Science University Portland, OR; VHA Office of Rural Health, Department of Veterans Affairs and VA Portland Health Care System, Portland, OR (SSO); HealthPartners Institute, Minneapolis MN (LIS)
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Balasubramanian BA, Lindner S, Marino M, Springer R, Edwards ST, McConnell KJ, Cohen DJ. Improving Delivery of Cardiovascular Disease Preventive Services in Small-to-Medium Primary Care Practices. J Am Board Fam Med 2022:jabfm.2022.AP.220038. [PMID: 36096660 DOI: 10.3122/jabfm.2022.ap.220038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 04/03/2022] [Accepted: 04/08/2022] [Indexed: 03/21/2023] Open
Abstract
BACKGROUND The EvidenceNOW initiative provided smaller primary care practices with external support interventions to implement quality improvement strategies focused on cardiovascular disease prevention. This manuscript reports effectiveness of EvidenceNOW interventions in improving quality metrics. METHODS: Seven regional Cooperatives delivered external support interventions (practice facilitation, health information technology support to assist with audit and feedback, performance benchmarking, learning collaboratives, and establishing community linkages) to 1278 smaller primary care practices. Outcomes included proportion of eligible patients meeting Centers for Medicaid and Medicare Services-specified ABCS metrics, that is, Aspirin for those at risk of ischemic vascular disease; achieving target Blood pressure among hypertensives; prescribing statin for those with elevated Cholesterol, diabetes, or increased cardiovascular disease risk; and screening for Smoking and providing cessation counseling. An event study compared prepost changes in outcomes among intervention practices and a difference-in-differences design compared intervention practices to 688 external comparison practices. RESULTS: Mean baseline outcomes ranged from 61.5% (cholesterol) to 64.9% (aspirin). In the event study, outcomes improved significantly (aspirin: +3.39 percentage points, 95% CI, 0.61-6.17; blood pressure: +1.59, 95% CI, 0.12-3.06; cholesterol: +4.43, 95% CI, 0.33-8.53; smoking: +7.33, 95% CI, 4.70-9.96). Difference-in-differences estimates were similar in magnitude but statistically significant for smoking alone. Preintervention trends were significant for smoking, but parallel-trends tests were not significant. CONCLUSIONS: EvidenceNOW Cooperatives improved cardiovascular prevention quality metrics among small and medium sized primary care practices across the US. While estimated improvements were small, they reflected average changes across a large and diverse sample of practices.
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Affiliation(s)
- Bijal A Balasubramanian
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC).
| | - Stephan Lindner
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC)
| | - Miguel Marino
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC)
| | - Rachel Springer
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC)
| | - Samuel T Edwards
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC)
| | - K John McConnell
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC)
| | - Deborah J Cohen
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX (BAB; Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health & Science University, Portland, OR (SL, KJM); Department of Family Medicine, Oregon Health & Science University, Portland, OR (MM, RS, STE, DJC); School of Public Health, Oregon Health & Science University, Portland, OR (MM); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland OR (STE); Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR (DJC)
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Sweeney SM, Baron A, Hall JD, Ezekiel-Herrera D, Springer R, Ward RL, Marino M, Balasubramanian BA, Cohen DJ. Effective Facilitator Strategies for Supporting Primary Care Practice Change: A Mixed Methods Study. Ann Fam Med 2022; 20:414-422. [PMID: 36228060 PMCID: PMC9512557 DOI: 10.1370/afm.2847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 03/16/2022] [Accepted: 05/04/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Practice facilitation is an evidence-informed implementation strategy to support quality improvement (QI) and aid practices in aligning with best evidence. Few studies, particularly of this size and scope, identify strategies that contribute to facilitator effectiveness. METHODS We conducted a sequential mixed methods study, analyzing data from EvidenceNOW, a large-scale QI initiative. Seven regional cooperatives employed 162 facilitators to work with 1,630 small or medium-sized primary care practices. Main analyses were based on facilitators who worked with at least 4 practices. Facilitators were defined as more effective if at least 75% of their practices improved on at least 1 outcome measure-aspirin use, blood pressure control, smoking cessation counseling (ABS), or practice change capacity, measured using Change Process Capability Questionnaire-from baseline to follow-up. Facilitators were defined as less effective if less than 50% of their practices improved on these outcomes. Using an immersion crystallization and comparative approach, we analyzed observational and interview data to identify strategies associated with more effective facilitators. RESULTS Practices working with more effective facilitators had a 3.6% greater change in the mean percentage of patients meeting the composite ABS measure compared with practices working with less effective facilitators (P <.001). More effective facilitators cultivated motivation by tailoring QI work and addressing resistance, guided practices to think critically, and provided accountability to support change, using these strategies in combination. They were able to describe their work in detail. In contrast, less effective facilitators seldom used these strategies and described their work in general terms. Facilitator background, experience, and work on documentation did not differentiate between more and less effective facilitators. CONCLUSIONS Facilitation strategies that differentiate more and less effective facilitators have implications for enhancing facilitator development and training, and can assist all facilitators to more effectively support practice changes.
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Affiliation(s)
- Shannon M Sweeney
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Andrea Baron
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Jennifer D Hall
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | | | - Rachel Springer
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Rikki L Ward
- Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, Texas
| | - Miguel Marino
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, Texas
| | - Deborah J Cohen
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
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Marino M, Solberg L, Springer R, McConnell KJ, Lindner S, Ward R, Edwards ST, Stange KC, Cohen DJ, Balasubramanian BA. Cardiovascular Disease Preventive Services Among Smaller Primary Care Practices. Am J Prev Med 2022; 62:e285-e295. [PMID: 34937670 DOI: 10.1016/j.amepre.2021.10.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 10/14/2021] [Accepted: 10/17/2021] [Indexed: 11/01/2022]
Abstract
INTRODUCTION Cardiovascular disease preventive services (aspirin use, blood pressure control, and smoking-cessation support) are crucial to controlling cardiovascular diseases. This study draws from 1,248 small-to-medium-sized primary care practices participating in the EvidenceNOW Initiative from 2015-2016 across 12 states to provide practice-level aspirin use, blood pressure control, and smoking-cessation support estimates; report the percentage of practices that meet Million Hearts targets; and identify the practice characteristics associated with better performance. METHODS This cross-sectional study utilized linear regression modeling (analyzed in 2020-2021) to examine the association of aspirin use, blood pressure control, and smoking-cessation support performance with practice characteristics that included structural attributes (e.g., size, ownership, rurality), practice capacity and contextual characteristics, health information technology, and patient panel demographics. RESULTS On average, practice performance on aspirin use, blood pressure control, and smoking-cessation support quality measures was 64% for aspirin, 63% for blood pressure, and 62% for smoking-cessation support. The 2012 Million Hearts goal of achieving the rates of 70% was achieved by 52% (aspirin), 32% (blood pressure), and 54% (smoking) of practices. Practice characteristics associated with aspirin use, blood pressure control, and smoking-cessation support performance included ownership (hospital/health system-owned practices had 11% higher aspirin performance than clinician-owned practices [p=0.001]), rurality (rural practices had lower performance than urban practices in all aspirin use, blood pressure control, and smoking-cessation support quality metrics [difference in aspirin=11.1%, p=0.001; blood pressure=4.2%, p=0.022; smoking=14.4%, p=0.009]), and disruptions (practices that experienced >1 major disruption showed lower aspirin performance [-7.1%, p<0.001]). CONCLUSIONS Achieving the Million Hearts targets may be assisted by collecting and reporting practice-level performance, which can promote change at the practice level and identify areas where additional support is needed to achieve initiative goals.
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Affiliation(s)
- Miguel Marino
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon; School of Public Health, Oregon Health & Science University, Portland, Oregon.
| | - Leif Solberg
- HealthPartners Institute, Minneapolis, Minnesota
| | - Rachel Springer
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - K John McConnell
- Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, Oregon; Department of Emergency Medicine, School of Medicine, Oregon Health & Science University, Portland, Oregon
| | - Stephan Lindner
- Center for Health Systems Effectiveness, Oregon Health & Science University, Portland, Oregon
| | - Rikki Ward
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, Texas
| | - Samuel T Edwards
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Kurt C Stange
- Center for Community Health Integration, Case Western Reserve University, Cleveland, Ohio
| | - Deborah J Cohen
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, Texas
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Damgacioglu H, Sonawane K, Zhu Y, Li R, Balasubramanian BA, Lairson DR, Giuliano AR, Deshmukh AA. Oropharyngeal Cancer Incidence and Mortality Trends in All 50 States in the US, 2001-2017. JAMA Otolaryngol Head Neck Surg 2021; 148:155-165. [PMID: 34913945 DOI: 10.1001/jamaoto.2021.3567] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Importance Oropharyngeal cancer (OPC) incidence is rising among men in the US. Comprehensive assessments of nationwide trends in OPC incidence and mortality by demographics, tumor characteristics at diagnosis, and geography are lacking. Objective We examined secular trends in OPC incidence and mortality rates in all 50 US states and the District of Columbia (DC). Design, Setting, and Participants In this cross-sectional study, we used the US Cancer Statistics data set to examine OPC incidence trends from 2001 through 2017. Observed and incidence-based mortality trends were evaluated using data from the National Center for Health Statistics and Surveillance Epidemiology and End Results program, respectively. Data analysis was conducted from January to April 2021. Results Nationwide, 260 182 OPC cases were identified; 209 297 (80%) occurred in men, 168 674 (65%) with regional stage, and 142 068 (55%) in the Southeast and Midwest regions, during 2001 to 2017. Incidence of OPC increased nationally 2.7% per year among men, with a notable (over 3% per year) rise among non-Hispanic White men and in men aged 65 years and older. Overall, among women, the annual percentage change was 0.5% (95% CI, -0.28% to 1.22%). Among men, with a 3.1% per year rise (95% CI, 2.4% to 3.8%), regional-stage OPC incidence increased nearly 2-fold. Among women, regional-stage OPC incidence increased 1.0% per year (95% CI, 0.3% to 1.7%). Among men, OPC incidence increased in all states and regions except Alaska, DC, and Wyoming. Among men, the most pronounced increases (more than 3.5% per year) were clustered in the Southeast and Midwest regions. Among women, a rise of more than 2% per year was also concentrated in the Southeast and Midwest regions. Among men, OPC incidence-based mortality increased 2.1% per year (95% CI, 1.0% to 3.2%) overall in recent years (from 2006 to 2017). In contrast, among women, the annual percentage change in OPC incidence-based mortality was -1.2% (95% CI, -2.5% to 0.1%). Conclusion and Relevance The findings of this cross-sectional study suggest that the incidence of OPC has continued to increase nationally among men in the US, with rapid increases among the elderly population. The notable rise in regional-stage OPC and the concurrent recent rise in mortality among men is troubling and calls for urgent improvements in prevention. Distinct geographic patterns with notable rises in the Midwest and Southeast regions imply the need for improved and targeted prevention as well as future studies to understand etiological reasons for geographic disparities.
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Affiliation(s)
- Haluk Damgacioglu
- Center for Health Services Research, Department of Management, Policy, and Community Health, School of Public Health, UTHealth Science Center at Houston, Texas
| | - Kalyani Sonawane
- Center for Health Services Research, Department of Management, Policy, and Community Health, School of Public Health, UTHealth Science Center at Houston, Texas.,Center for Healthcare Data, Department of Management, Policy and Community Health, School of Public Health, UT Health Science Center at Houston, Texas
| | - Yenan Zhu
- Center for Health Services Research, Department of Management, Policy, and Community Health, School of Public Health, UTHealth Science Center at Houston, Texas
| | - Ruosha Li
- Department of Biostatistics and Data Science, School of Public Health, UT Health Science Center at Houston, Texas
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, UT Health Science Center at Houston, Texas
| | - David R Lairson
- Center for Health Services Research, Department of Management, Policy, and Community Health, School of Public Health, UTHealth Science Center at Houston, Texas
| | - Anna R Giuliano
- Center for Immunization and Infection Research in Cancer, Moffitt Cancer Center, Tampa, Florida
| | - Ashish A Deshmukh
- Center for Health Services Research, Department of Management, Policy, and Community Health, School of Public Health, UTHealth Science Center at Houston, Texas
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Francis JK, Rodriguez SA, Dorsey O, Blackwell JM, Balasubramanian BA, Kale N, Day P, Preston SM, Thompson EL, Pruitt SL, Tiro JA. Provider perspectives on communication and dismissal policies with HPV vaccine hesitant parents. Prev Med Rep 2021; 24:101562. [PMID: 34976628 PMCID: PMC8683895 DOI: 10.1016/j.pmedr.2021.101562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 09/10/2021] [Accepted: 09/12/2021] [Indexed: 11/16/2022] Open
Abstract
Providers (29%) experience HPV-specific vaccine hesitancy from parents. Providers feel least confident in responding to families’ religious beliefs. Some providers (25%) agree with dismissal policies for families refusing vaccines.
Parental vaccine hesitancy is a growing concern. Less is known about provider or practice characteristics that encounter HPV-specific vaccine-hesitant parents, the providers’ confidence in responding to HPV vaccine concerns, and the attitudes and use of vaccine dismissal policies (i.e., removing patients from the practice). North Texas providers completed an online survey. Dependent variables assessed: (1) percentage of HPV vaccine-hesitant parents encountered in practice defined as substantive, or high (≥11%, or among more than one out of ten adolescent patient encounters) versus low (≤10%) levels; (2) confidence in responding to 11 HPV vaccine concerns; (3) attitudes and use of vaccine dismissal policies. Chi-square and Fisher’s exact tests were conducted. Among 156 providers, 29% reported high HPV vaccine hesitancy (≥11% of patient population). Overall, providers reported being “very confident” in addressing vaccine concerns (mean: 3.37 out of 4, SD: 0.57). Mean confidence scores were significantly higher for white (vs. non-white) providers and for pediatricians (vs. family practitioners). Providers were least confident in responding to parents’ religious/personal beliefs (69%). Some providers (25%) agreed with policies that dismissed vaccine-hesitant parents after repeated counseling attempts. More providers used dismissal policies for childhood (19%) than adolescent (10%) immunizations. Provider communication training should include parental religious/personal beliefs to effectively address HPV vaccine hesitancy. Other regions should examine their HPV-specific vaccine hesitancy levels to understand how the use of dismissal policies might vary between adolescent and childhood immunizations.
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Austin JD, Allicock M, Fernandez ME, Balasubramanian BA, Lee SC. Understanding the Delivery of Patient-Centered Survivorship Care Planning: An Exploratory Interview Study With Complex Cancer Survivors. Cancer Control 2021; 28:10732748211011957. [PMID: 34689577 PMCID: PMC8718161 DOI: 10.1177/10732748211011957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Introduction: Understanding key elements of the survivorship care planning process, such as patient-centered communication (PCC) and health self-efficacy, are critical for delivering patient-centered survivorship care to cancer survivors with multiple chronic conditions (“complex cancer survivors”). Building upon our team’s recent research efforts to examine the survivorship care planning process from a patient-centered lens, this exploratory study leveraged an ongoing quasi-experimental trial to elucidate the experience of complex cancer survivors with survivorship care planning and post-treatment management. Methods: We conducted a hypothesis-generating thematic content analysis on 8 interview transcripts. Results: Survivors reported positive experiences communicating with their oncology care team but the presence of multiple chronic conditions in addition to cancer creates additional barriers to patient-centered survivorship care. Conclusion: These findings support the need for further in-depth research aimed at improving PCC across all care teams and enabling self-management by delivering more personalized survivorship care planning that aligns with survivor’s needs, values, and preferences.
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Affiliation(s)
- Jessica D Austin
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.,Department of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Marlyn Allicock
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA.,UTHealth School of Public Health, Center for Health Promotion and Prevention Research, Houston, TX, USA
| | - Maria E Fernandez
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Dallas, TX, USA.,UTHealth School of Public Health, Center for Health Promotion and Prevention Research, Houston, TX, USA
| | - Bijal A Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA.,UTHealth School of Public Health, Center for Health Promotion and Prevention Research, Houston, TX, USA.,Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Dallas, TX, USA
| | - Simon Craddock Lee
- Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA.,Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Affiliation(s)
- Quiera S Booker
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA
| | - Jessica D Austin
- Department of Epidemiology and Sociomedical Sciences, Columbia Mailman School of Public Health, 722 W 168th St, New York, NY, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA
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Balasubramanian BA, Higashi RT, Rodriguez SA, Sadeghi N, Santini NO, Lee SC. Thematic Analysis of Challenges of Care Coordination for Underinsured and Uninsured Cancer Survivors With Chronic Conditions. JAMA Netw Open 2021; 4:e2119080. [PMID: 34387681 PMCID: PMC8363913 DOI: 10.1001/jamanetworkopen.2021.19080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
IMPORTANCE Although a majority of underinsured and uninsured patients with cancer have multiple comorbidities, many lack consistent connections with a primary care team to manage chronic conditions during and after cancer treatment. This presents a major challenge to delivering high-quality comprehensive and coordinated care. OBJECTIVE To describe challenges and opportunities for coordinating care in an integrated safety-net system for patients with both cancer and other chronic conditions. DESIGN, SETTING, AND PARTICIPANTS This multimodal qualitative study was conducted from May 2016 to July 2019 at a county-funded, vertically integrated safety-net health system including ambulatory oncology, urgent care, primary care, and specialty care. Participants were 93 health system stakeholders (clinicians, leaders, clinical, and administrative staff) strategically and snowball sampled for semistructured interviews and observation during meetings and daily processes of care. Data collection and analysis were conducted iteratively using a grounded theory approach, followed by systematic thematic analysis to organize data, review, and interpret comprehensive findings. Data were analyzed from March 2019 to March 2020. MAIN OUTCOMES AND MEASURES Multilevel factors associated with experiences of coordinating care for patients with cancer and chronic conditions among oncology and primary care stakeholders. RESULTS Among interviews and observation of 93 health system stakeholders, system-level factors identified as being associated with care coordination included challenges to accessing primary care, lack of communication between oncology and primary care clinicians, and leadership awareness of care coordination challenges. Clinician-level factors included unclear role delineation and lack of clinician knowledge and preparedness to manage the effects of cancer and chronic conditions. CONCLUSIONS AND RELEVANCE Primary care may play a critical role in delivering coordinated care for patients with cancer and chronic diseases. This study's findings suggest a need for care delivery strategies that bridge oncology and primary care by enhancing communication, better delineating roles and responsibilities across care teams, and improving clinician knowledge and preparedness to care for patients with cancer and chronic conditions. Expanding timely access to primary care is also key, albeit challenging in resource-limited safety-net settings.
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Affiliation(s)
- Bijal A. Balasubramanian
- University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Dallas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Robin T. Higashi
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
- University of Texas Southwestern Medical Center, Dallas
| | | | - Navid Sadeghi
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
- University of Texas Southwestern Medical Center, Dallas
- Parkland Health and Hospital System, Dallas, Texas
| | | | - Simon Craddock Lee
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
- University of Texas Southwestern Medical Center, Dallas
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17
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Kindratt TB, Allicock M, Atem F, Dallo FJ, Balasubramanian BA. Email Patient-Provider Communication and Cancer Screenings Among US Adults: Cross-sectional Study. JMIR Cancer 2021; 7:e23790. [PMID: 34328421 PMCID: PMC8367146 DOI: 10.2196/23790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 04/12/2021] [Accepted: 06/02/2021] [Indexed: 11/21/2022] Open
Abstract
Background The growth of electronic medical records and use of patient portals have allowed for patients and health care providers to communicate via email and direct messaging between health care visits. Email patient-provider communication (PPC) may enhance traditional face-to-face PPC by allowing patients to ask questions, receive clear explanations, engage in shared decision-making, and confirm their understanding between in-person visits. Despite increasing trends in the use of email PPC since the early 2000s, few studies have evaluated associations between email PPC and the uptake of preventive services. Objective The objective of this study was to determine associations between the use of email PPC and the likelihood of undergoing breast, cervical, and colon cancer screenings among adults who have received health care in the past 12 months. Methods Secondary, cross-sectional data from the 2011-2015 National Health Interview Survey were combined and analyzed. For each cancer screening, inclusion criteria were based on the age of screening recommendations and prior history of cancer diagnosis (n=35,912 for breast, n=48,512 for cervical, and n=45,884 for colon). The independent variable was whether adults used email PPC in the past 12 months (yes or no). The dependent variables were whether (1) women (aged ≥40 years) received a mammogram in the past 12 months; (2) women (aged 21-65 years) received a Pap test in the past 12 months; and (3) individuals (aged ≥50 years) received a colon cancer screening in the past 12 months. Bivariate and multivariable logistic regression analyses were conducted. Results Adults who reported receiving all three cancer screenings in the past 12 months were more likely to be non-Hispanic White; be married or living with a partner; have a bachelor’s degree or higher education level; have health insurance coverage; and perceive their health as excellent, very good, or good (all P<.001). Men were more likely to receive colon cancer screenings than women (P<.001). Multivariable logistic regression models showed women who used email to communicate with their health care providers had greater odds of receiving breast (odds ratio [OR] 1.32, 95% CI 1.20-1.44) and cervical (OR 1.11, 95% CI 1.02-1.20) cancer screenings than women who did not use email PPC. Adults who used email to communicate with their health care providers had 1.55 times greater odds (95% CI 1.42-1.69) of receiving a colon cancer screening than those who did not use email PPC. Conclusions Our results demonstrate that email PPC is a marker of increased likelihood of adults completing age-appropriate cancer screenings, particularly breast, cervical, and colon cancer screenings. More research is needed to examine other factors related to the reasons for and quality of email PPC between patients and health care providers and determine avenues for health education and intervention to further explore this association.
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Affiliation(s)
- Tiffany B Kindratt
- Public Health Program, Department of Kinesiology, College of Nursing and Health Innovation, University of Texas at Arlington, Arlington, TX, United States
| | - Marlyn Allicock
- Department of Health Promotion and Behavioral Sciences, School of Public Health Dallas, UTHealth, The University of Texas Health Science Center at Houston, Dallas, TX, United States.,Center for Health Promotion and Prevention Research, Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Folefac Atem
- Department of Biostatistics and Data Science, School of Public Health Dallas, UTHealth, The University of Texas Health Science Center at Houston, Dallas, TX, United States
| | - Florence J Dallo
- Department of Public and Environmental Wellness, School of Health Sciences, Oakland University, Rochester, MI, United States
| | - Bijal A Balasubramanian
- Center for Health Promotion and Prevention Research, Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, United States.,Department of Epidemiology, Human Genetics, and Environmental Health Sciences, School of Public Health Dallas, UTHealth, The University of Texas Health Science Center at Houston, Dallas, TX, United States
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18
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Edwards ST, Marino M, Solberg LI, Damschroder L, Stange KC, Kottke TE, Balasubramanian BA, Springer R, Perry CK, Cohen DJ. Cultural And Structural Features Of Zero-Burnout Primary Care Practices. Health Aff (Millwood) 2021; 40:928-936. [PMID: 34097508 DOI: 10.1377/hlthaff.2020.02391] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Although much attention has been focused on individual-level drivers of burnout in primary care settings, examining the structural and cultural factors of practice environments with no burnout could identify solutions. In this cross-sectional analysis of survey data from 715 small-to-medium-size primary care practices in the United States participating in the Agency for Healthcare Research and Quality's EvidenceNOW initiative, we found that zero-burnout practices had higher levels of psychological safety and adaptive reserve, a measure of practice capacity for learning and development. Compared with high-burnout practices, zero-burnout practices also reported using more quality improvement strategies, more commonly were solo and clinician owned, and less commonly had participated in accountable care organizations or other demonstration projects. Efforts to prevent burnout in primary care may benefit from focusing on enhancing organization and practice culture, including promoting leadership development and fostering practice agency.
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Affiliation(s)
- Samuel T Edwards
- Samuel T. Edwards is an assistant professor of medicine at Oregon Health and Science University and a staff physician in the Section of General Internal Medicine, Veterans Affairs Portland Health Care System, both in Portland, Oregon
| | - Miguel Marino
- Miguel Marino is an associate professor of biostatistics in the Department of Family Medicine, Oregon Health and Science University, and at the OHSU-Portland State University School of Public Health, in Portland, Oregon
| | - Leif I Solberg
- Leif I. Solberg is a senior research investigator at HealthPartners Institute, in Minneapolis, Minnesota
| | - Laura Damschroder
- Laura Damschroder is an implementation research consultant through Implementation Pathways, LLC, and a research investigator in the Veterans Affairs Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, in Ann Arbor, Michigan
| | - Kurt C Stange
- Kurt C. Stange is the Dorothy Jones Weatherhead Professor of Medicine; a professor of family medicine and community health, population and quantitative health sciences, oncology, and sociology; and the director of the Center for Community Health Integration, Case Western Reserve University, in Cleveland, Ohio
| | - Thomas E Kottke
- Thomas E. Kottke is a senior research investigator at HealthPartners Institute
| | - Bijal A Balasubramanian
- Bijal A. Balasubramanian is an associate professor in the Department of Epidemiology, Human Genetics, and Environmental Sciences and regional dean of UTHealth School of Public Health, in Dallas, Texas
| | - Rachel Springer
- Rachel Springer is a biostatistician in the Department of Family Medicine, Oregon Health and Science University
| | - Cynthia K Perry
- Cynthia K. Perry is a professor in the School of Nursing, Oregon Health and Science University
| | - Deborah J Cohen
- Deborah J. Cohen is a professor of family medicine and vice chair of research in the Department of Family Medicine, Oregon Health and Science University
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Cohen DJ, Sweeney SM, Miller WL, Hall JD, Miech EJ, Springer RJ, Balasubramanian BA, Damschroder L, Marino M. Improving Smoking and Blood Pressure Outcomes: The Interplay Between Operational Changes and Local Context. Ann Fam Med 2021; 19:240-248. [PMID: 34180844 PMCID: PMC8118489 DOI: 10.1370/afm.2668] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 10/23/2020] [Accepted: 10/29/2020] [Indexed: 01/25/2023] Open
Abstract
PURPOSE We undertook a study to identify conditions and operational changes linked to improvements in smoking and blood pressure (BP) outcomes in primary care. METHODS We purposively sampled and interviewed practice staff (eg, office managers, clinicians) from a subset of 104 practices participating in EvidenceNOW-a multisite cardiovascular disease prevention initiative. We calculated Clinical Quality Measure improvements, with targets of 10-point or greater absolute improvements in the proportion of patients with smoking screening and, if relevant, counseling and in the proportion of hypertensive patients with adequately controlled BP. We analyzed interview data to identify operational changes, transforming these into numeric data. We used Configurational Comparative Methods to assess the joint effects of multiple factors on outcomes. RESULTS In clinician-owned practices, implementing a workflow to routinely screen, counsel, and connect patients to smoking cessation resources, or implementing a documentation change or a referral to a resource alone led to an improvement of at least 10 points in the smoking outcome with a moderate level of facilitation support. These patterns did not manifest in health- or hospital system-owned practices or in Federally Qualified Health Centers, however. The BP outcome improved by at least 10 points among solo practices after medical assistants were trained to take an accurate BP. Among larger, clinician-owned practices, BP outcomes improved when practices implemented a second BP measurement when the first was elevated, and when staff learned where to document this information in the electronic health record. With 50 hours or more of facilitation, BP outcomes improved among larger and health- and hospital system-owned practices that implemented these operational changes. CONCLUSIONS There was no magic bullet for improving smoking or BP outcomes. Multiple combinations of operational changes led to improvements, but only in specific contexts of practice size and ownership, or dose of external facilitation.
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Affiliation(s)
- Deborah J Cohen
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Shannon M Sweeney
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | | | - Jennifer D Hall
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Edward J Miech
- Regenstrief Institute, Center for Health Services Research, Indianapolis, Indiana
| | - Rachel J Springer
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, Texas
| | - Laura Damschroder
- Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Miguel Marino
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon
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Barlow WE, Beaber EF, Geller BM, Kamineni A, Zheng Y, Haas JS, Chao CR, Rutter CM, Zauber AG, Sprague BL, Halm EA, Weaver DL, Chubak J, Doria-Rose VP, Kobrin S, Onega T, Quinn VP, Schapira MM, Tosteson ANA, Corley DA, Skinner CS, Schnall MD, Armstrong K, Wheeler CM, Silverberg MJ, Balasubramanian BA, Doubeni CA, McLerran D, Tiro JA. Evaluating Screening Participation, Follow-up, and Outcomes for Breast, Cervical, and Colorectal Cancer in the PROSPR Consortium. J Natl Cancer Inst 2020; 112:238-246. [PMID: 31292633 DOI: 10.1093/jnci/djz137] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 04/11/2019] [Accepted: 07/03/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Cancer screening is a complex process encompassing risk assessment, the initial screening examination, diagnostic evaluation, and treatment of cancer precursors or early cancers. Metrics that enable comparisons across different screening targets are needed. We present population-based screening metrics for breast, cervical, and colorectal cancers for nine sites participating in the Population-based Research Optimizing Screening through Personalized Regimens consortium. METHODS We describe how selected metrics map to a trans-organ conceptual model of the screening process. For each cancer type, we calculated calendar year 2013 metrics for the screen-eligible target population (breast: ages 40-74 years; cervical: ages 21-64 years; colorectal: ages 50-75 years). Metrics for screening participation, timely diagnostic evaluation, and diagnosed cancers in the screened and total populations are presented for the total eligible population and stratified by age group and cancer type. RESULTS The overall screening-eligible populations in 2013 were 305 568 participants for breast, 3 160 128 for cervical, and 2 363 922 for colorectal cancer screening. Being up-to-date for testing was common for all three cancer types: breast (63.5%), cervical (84.6%), and colorectal (77.5%). The percentage of abnormal screens ranged from 10.7% for breast, 4.4% for cervical, and 4.5% for colorectal cancer screening. Abnormal breast screens were followed up diagnostically in almost all (96.8%) cases, and cervical and colorectal were similar (76.2% and 76.3%, respectively). Cancer rates per 1000 screens were 5.66, 0.17, and 1.46 for breast, cervical, and colorectal cancer, respectively. CONCLUSIONS Comprehensive assessment of metrics by the Population-based Research Optimizing Screening through Personalized Regimens consortium enabled systematic identification of screening process steps in need of improvement. We encourage widespread use of common metrics to allow interventions to be tested across cancer types and health-care settings.
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Affiliation(s)
| | - Elisabeth F Beaber
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Berta M Geller
- Departments of Family Medicine, and the University of Vermont Cancer Center, University of Vermont, Burlington, VT
| | - Aruna Kamineni
- Kaiser Permanente Washington Health Research Institute, Seattle, WA
| | - Yingye Zheng
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jennifer S Haas
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Dana Farber, Harvard Cancer Institute, Harvard School of Public Health, Boston, MA
| | - Chun R Chao
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA
| | | | - Ann G Zauber
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Brian L Sprague
- Departments of Surgery and Radiology, University of Vermont, Burlington, VT
| | - Ethan A Halm
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX.,Simmons Comprehensive Cancer Center, Dallas, TX
| | - Donald L Weaver
- Department of Pathology and the UVM Cancer Center, University of Vermont, Burlington, VT
| | - Jessica Chubak
- Kaiser Permanente Washington Health Research Institute, Seattle, WA
| | - V Paul Doria-Rose
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA.,Healthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
| | - Sarah Kobrin
- Healthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
| | - Tracy Onega
- Departments of Biomedical Data Science, Epidemiology, and the Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | | | - Marilyn M Schapira
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, and CMC VA Medical Center, Philadelphia, PA
| | - Anna N A Tosteson
- The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Celette Sugg Skinner
- Simmons Comprehensive Cancer Center, Dallas, TX.,Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX
| | - Mitchell D Schnall
- Department of Radiology, University of Pennsylvania, Perelman School of Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Katrina Armstrong
- General Medicine Division, MA General Hospital, Harvard Medical School, Boston, MA
| | - Cosette M Wheeler
- Departments of Pathology and Obstetrics and Gynecology, University of New Mexico Health Science Center, Albuquerque, NM.,University of New Mexico Comprehensive Cancer Center, Albuquerque, NM
| | | | - Bijal A Balasubramanian
- Simmons Comprehensive Cancer Center, Dallas, TX.,UTHealth School of Public Health, Dallas, TX
| | - Chyke A Doubeni
- Department of Family Medicine and Community Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Dale McLerran
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jasmin A Tiro
- Simmons Comprehensive Cancer Center, Dallas, TX.,Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX
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Chan AT, Drew DA, Nguyen LH, Joshi AD, Ma W, Guo CG, Lo CH, Mehta RS, Kwon S, Sikavi DR, Magicheva-Gupta MV, Fatehi ZS, Flynn JJ, Leonardo BM, Albert CM, Andreotti G, Beane-Freeman LE, Balasubramanian BA, Brownstein JS, Bruinsma F, Cowan AN, Deka A, Ernst ME, Figueiredo JC, Franks PW, Gardner CD, Ghobrial IM, Haiman CA, Hall JE, Deming-Halverson SL, Kirpach B, Lacey JV, Marchand LL, Marinac CR, Martinez ME, Milne RL, Murray AM, Nash D, Palmer JR, Patel AV, Rosenberg L, Sandler DP, Sharma SV, Schurman SH, Wilkens LR, Chavarro JE, Eliassen AH, Hart JE, Kang JH, Koenen KC, Kubzansky LD, Mucci LA, Ourselin S, Rich-Edwards JW, Song M, Stampfer MJ, Steves CJ, Willett WC, Wolf J, Spector T. The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action. Cancer Epidemiol Biomarkers Prev 2020; 29:1283-1289. [PMID: 32371551 PMCID: PMC7357669 DOI: 10.1158/1055-9965.epi-20-0606] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 05/01/2020] [Accepted: 05/04/2020] [Indexed: 01/08/2023] Open
Abstract
The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.
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Affiliation(s)
- Andrew T Chan
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - David A Drew
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Long H Nguyen
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Amit D Joshi
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Wenjie Ma
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Chuan-Guo Guo
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Chun-Han Lo
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Raaj S Mehta
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Sohee Kwon
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Daniel R Sikavi
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Marina V Magicheva-Gupta
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Zahra S Fatehi
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Jacqueline J Flynn
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Brianna M Leonardo
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Christine M Albert
- Department of Cardiology, Cedars-Sinai Hospital, Los Angeles, California
| | - Gabriella Andreotti
- Division of Cancer Epidemiology & Genetics, Occupational and Environmental Epidemiology Branch, National Institutes of Health, National Cancer Institute, Bethesda, Maryland
| | - Laura E Beane-Freeman
- Division of Cancer Epidemiology & Genetics, Occupational and Environmental Epidemiology Branch, National Institutes of Health, National Cancer Institute, Bethesda, Maryland
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Houston, Texas
| | - John S Brownstein
- Computational Epidemiology Group, Boston Children's Hospital, Boston, Massachusetts
| | - Fiona Bruinsma
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Annie N Cowan
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | | | - Jane C Figueiredo
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Hospital, Los Angeles, California
| | - Paul W Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Genetic and Molecular Epidemiology, Lund University, Malmo, Sweden
| | - Christopher D Gardner
- Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, California
| | - Irene M Ghobrial
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center and the Epidemiology and Genetics Division, Department of Preventive Medicine, University of Southern California, Los Angeles, California
| | - Janet E Hall
- National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
| | | | - Brenda Kirpach
- Hennepin Health Care Research Institute, Berman Center for Outcomes and Clinical Research, Minneapolis, Minnesota
| | - James V Lacey
- Division of Health Analytics, Department of Computational and Quantitative Medicine, City of Hope, Duarte, California
| | | | - Catherine R Marinac
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Maria Elena Martinez
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California
- Moores Cancer Center, University of California, San Diego, La Jolla California
| | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Anne M Murray
- Hennepin Health Care Research Institute, Berman Center for Outcomes and Clinical Research, Minneapolis, Minnesota
| | - Denis Nash
- Institute for Implementation Science in Population Health, City University of New York (CUNY), New York, New York
- Department of Epidemiology and Biostatistics, School of Public Health, City University of New York (CUNY), New York, New York
| | - Julie R Palmer
- Slone Epidemiology Center, School of Medicine, Boston University, Boston, Massachusetts
| | | | - Lynn Rosenberg
- Slone Epidemiology Center, School of Medicine, Boston University, Boston, Massachusetts
| | - Dale P Sandler
- National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
| | - Shreela V Sharma
- Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Houston, Texas
| | - Shepherd H Schurman
- National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
| | | | - Jorge E Chavarro
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - A Heather Eliassen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jaime E Hart
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jae Hee Kang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Karestan C Koenen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Laura D Kubzansky
- Department of Social and Behavioral Sciences and Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Sebastien Ourselin
- Department of Twin Research & Genetic Epidemiology, Kings College, London, United Kingdom
| | - Janet W Rich-Edwards
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Mingyang Song
- Clinical & Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Meir J Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Claire J Steves
- Department of Twin Research & Genetic Epidemiology, Kings College, London, United Kingdom
| | - Walter C Willett
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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22
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Austin JD, Chansard M, Lee SC, Balasubramanian BA. Abstract C096: Influence of primary care connectedness on early-stage cancer diagnosis among vulnerable patients in an integrated, safety-net setting. Cancer Epidemiol Biomarkers Prev 2020. [DOI: 10.1158/1538-7755.disp19-c096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
Introduction. Vulnerable populations, such as minorities, under-, and uninsured patients receiving care from safety-net settings, are more likely to receive a late-stage cancer diagnosis, resulting in higher mortality rates. Studies have shown that being connected to a primary care provider can play a vital role in timely diagnosis of early-stage cancer. Yet, vulnerable populations often have difficulty accessing primary care services and resources in most safety-net settings where care is fragmented. Receiving care in an integrated health system may help to reduce stage disparities by providing the infrastructure to support continuity and coordination of care. Yet, the degree to which vulnerable patients are connected to a primary care provider within an integrated setting is uncertain. A better understanding of the role of primary care connectedness among vulnerable patient populations receiving care in an integrated, safety-net hospital setting is needed to address the issue of stage disparity. We hypothesize that vulnerable patients connected to a primary care provider prior to their cancer diagnosis will have increased odds of early-stage cancer diagnosis. Methods. As part of an ongoing prospective study, we examined a cross-sectional sample of 66 patients diagnosed with Stage I-III colorectal and breast cancer receiving care within an integrated, safety-net hospital system during the years 2017 and 2018. We analyzed medical records data to generate descriptive statistics to characterized patient demographics, cancer-related demographics, and primary care connectedness - defined as having a primary care provider listed in the medical record prior to diagnosis. Using logistic regression, we calculated the odds of early-stage disease, according to the American Joint Commission on Cancer (AJCC) (stages I and II vs. III) as a function of primary care connectedness. Results. The majority of the sample was non-white (58%) and nearly half reported having no insurance (47%). Females comprised nearly 80% of the sample and one-third of the sample was diagnosed with colorectal cancer. In addition, nearly 60% had a primary care provider listed in the medical record prior to their cancer diagnosis and 60% received an early-stage diagnosis. Preliminary findings from the logistic regression support our hypothesis that vulnerable patients connected to a primary care provider prior to a cancer diagnosis had significantly higher odds of early-stage diagnosis (OR = 3.9, 95% CI 1.2-13.0). Conclusion. Being connected to a primary care provider may help to reduce stage disparities among vulnerable populations receiving care from an integrated safety-net setting. Integrated safety-net settings may facilitate early-stage diagnosis through clear referral pathways that ensure more timely diagnosis after screening abnormalities and prevent diagnostic delay.
Citation Format: Jessica D Austin, Matthieu Chansard, Simon C Lee, Bijal A Balasubramanian. Influence of primary care connectedness on early-stage cancer diagnosis among vulnerable patients in an integrated, safety-net setting [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr C096.
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Affiliation(s)
- Jessica D Austin
- 1UTHealth School of Public Health in Dallas, Dallas, Texas, USA,
| | | | - Simon C Lee
- 3Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas, USA
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23
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Murphy CC, Halm EA, Skinner CS, Balasubramanian BA, Singal AG. Challenges and Approaches to Measuring Repeat Fecal Immunochemical Test for Colorectal Cancer Screening. Cancer Epidemiol Biomarkers Prev 2020; 29:1557-1563. [PMID: 32457184 DOI: 10.1158/1055-9965.epi-20-0230] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 04/14/2020] [Accepted: 05/11/2020] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Colorectal cancer screening with fecal immunochemical testing (FIT) can reduce colorectal cancer-related mortality. Effectiveness of FIT may be compromised when patients do not adhere to a regular schedule. However, having no standard measure of repeat FIT presents challenges for assessing effectiveness across populations and settings. We compared three measures of repeat FIT in a large, integrated health care system in Dallas, Texas. METHODS We identified 18,257 patients age-eligible (50-60 years) for FIT in January 1-December 31, 2010 and followed over four rounds of screening. Measures included: (i) repeat FIT in prior screeners, or completion of FIT within 9-15 months of the previous; (ii) yes-no patterns, whereby patients were assigned yes or no in 9-15 month windows; and 3) proportion of time covered (PTC), or the amount of time patients were up-to-date with screening relative to time eligible. RESULTS Repeat FIT varied by measure. Using a prior screeners measure, 15.8% of patients with a normal FIT in round 1 completed repeat FIT in round 2. Repeat FIT was notably higher (52.3%) using PTC. The most common yes-no pattern was YNNN or "one-and-done," and only 9.4% of patients completed two consecutive FITs across all rounds (YYNN). CONCLUSIONS Different measures of repeat FIT yielded a range of estimates, making comparison across studies difficult. Researchers should weigh the advantages and disadvantages of each measure and select the most appropriate to their research question. IMPACT Our study highlights the need for future research of repeat FIT measures that best approximate screening effectiveness.
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Affiliation(s)
- Caitlin C Murphy
- Department of Population & Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Ethan A Halm
- Department of Population & Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Celette Sugg Skinner
- Department of Population & Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Bijal A Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
- Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health in Dallas, Dallas, Texas
| | - Amit G Singal
- Department of Population & Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
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24
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Abstract
Few studies have examined how different qualities and modes (face-to-face vs electronic) of patient–provider communication (PPC) influence cancer screening uptake. Our objective was to determine whether receiving a breast, cervical, and colorectal cancer screening is influenced by (1) qualities of face-to-face and (2) the use of e-mail PPC. We analyzed Health Information National Trends Survey 4, cycles 1 to 4 data. To assess qualities of face-to-face PPC, adults reported how often physicians spent enough time with them, explained so they understood, gave them a chance to ask questions, addressed feelings and emotions, involved them in decisions, confirmed understanding, and helped them with uncertainty. Adults reported whether they used e-mail PPC. We used multivariable logistic regression to evaluate the odds of receiving cancer screenings based on face-to-face and e-mail PPC. Adults whose health-care providers involved them in decision-making had highest odds of receiving breast (odds ratio [OR] = 1.38; 95% confidence interval [CI] = 1.11-1.71), cervical (OR = 1.30; 95% CI = 1.06-1.60), and colorectal (OR = 1.25; 95% CI = 1.03-1.51) cancer screenings. No significant associations were observed between e-mail PPC and cancer screenings. More research is needed to explore this association.
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Affiliation(s)
- Tiffany B Kindratt
- Public Health Program, Department of Kinesiology, College of Nursing and Health Innovation, University of Texas at Arlington, Arlington, TX, USA
| | - Folefac Atem
- Department of Biostatistics and Data Science, UT Health, School of Public Health Dallas, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Florence J Dallo
- Department of Public and Environmental Wellness, School of Health Sciences, Oakland University, Rochester, MI, USA
| | - Marlyn Allicock
- Department of Health Promotion and Behavioral Sciences, UT Health, School of Public Health Dallas, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Center for Health Promotion and Prevention Research, UT Southwestern-Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA
| | - Bijal A Balasubramanian
- Center for Health Promotion and Prevention Research, UT Southwestern-Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA.,Department of Epidemiology, Human Genetics, and Environmental Sciences, UT Health, School of Public Health Dallas, The University of Texas Health Science Center at Houston, Houston, TX, USA
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Kindratt TB, Dallo FJ, Allicock M, Atem F, Balasubramanian BA. The influence of patient-provider communication on cancer screenings differs among racial and ethnic groups. Prev Med Rep 2020; 18:101086. [PMID: 32309115 PMCID: PMC7155227 DOI: 10.1016/j.pmedr.2020.101086] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 03/09/2020] [Accepted: 03/29/2020] [Indexed: 12/11/2022] Open
Abstract
Our study aimed to estimate how associations between adults' perceptions of specific domains of PPC quality and their likelihood of receiving cancer screenings differed by race and ethnicity. We analyzed 2011-2015 Medical Expenditure Panel Survey (MEPS) data. Samples included 7337 women ages 50-74 (breast), 13,276 women ages 21-65 (cervical), and 9792 adults ages ≥50 years (colorectal). To examine individual domains of PPC quality (independent variables), adults reported how often providers: listened; showed respect; spent enough time; explained things; gave specific instructions; and demonstrated health literate practices (gave clear instructions and asked them to "teach-back" how they will follow instructions). Dependent variables were breast, cervical, and colorectal cancer screenings. Multivariable logistic regression was used to evaluate the odds of receiving cancer screenings using a composite measure of PPC quality and separate domains. Hispanic and non-Hispanic black adults who reported their providers always demonstrated PPC quality had higher odds of receiving colorectal cancer screenings compared to those whose providers did not. Adults' perceptions of whether or not their provider gave them specific instructions increased their odds of receiving breast (Hispanics OR = 1.65, 95% CI = 1.09, 2.51; non-Hispanic blacks OR = 1.54, 95% CI = 1.06, 2.24) and colorectal (non-Hispanic whites OR = 1.37, 95% CI = 1.13, 1.66; Hispanics OR = 1.29, 95% CI = 1.01, 1.66; non-Hispanic blacks OR = 1.92, 95% CI = 1.39, 2.65) cancer screenings. Non-Hispanic Asian women who reported their health care providers demonstrated "teach-back" had higher odds (OR = 2.25; 95% CI = 1.10, 4.62) of receiving cervical cancer screenings. Efforts to improve cancer screenings should focus on training providers to demonstrate health literate practices to improve cancer screenings.
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Affiliation(s)
- Tiffany B Kindratt
- University of Texas at Arlington, Public Health Program, Department of Kinesiology, College of Nursing and Health Innovation, 500 West Nedderman Drive, Arlington, TX 76019-0259, United States
| | - Florence J Dallo
- Oakland University, Department of Public and Environmental Wellness, School of Health Sciences, United States
| | - Marlyn Allicock
- UT Health, The University of Texas Health Science Center at Houston, School of Public Health Dallas, Department of Health Promotion and Behavioral Sciences, United States
| | - Folefac Atem
- UT Health, The University of Texas Health Science Center at Houston, School of Public Health Dallas, Department of Biostatistics and Data Science, United States
| | - Bijal A Balasubramanian
- UT Health, The University of Texas Health Science Center at Houston, School of Public Health Dallas, Department of Epidemiology, Human Genetics, and Environmental Sciences, Center for Health Promotion and Prevention Research, UT Southwestern - Harold C. Simmons Comprehensive Cancer Center, United States
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26
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Jetelina KK, Yudkin JS, Miller S, Berry E, Lieberman A, Gupta S, Balasubramanian BA. Patient-Reported Barriers to Completing a Diagnostic Colonoscopy Following Abnormal Fecal Immunochemical Test Among Uninsured Patients. J Gen Intern Med 2019; 34:1730-1736. [PMID: 31228053 PMCID: PMC6712145 DOI: 10.1007/s11606-019-05117-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 01/02/2019] [Accepted: 03/13/2019] [Indexed: 01/30/2023]
Abstract
BACKGROUND For colorectal cancer (CRC) screening to improve survival, patients with an abnormal fecal immunochemical test (FIT) must follow-up with a diagnostic colonoscopy. Adherence to follow-up is low and patient-level barriers for suboptimal adherence have yet to be explored. OBJECTIVE To characterize barriers for non-completion of diagnostic colonoscopy after an abnormal FIT reported by under- and uninsured patients receiving care in a safety-net health system. DESIGN A longitudinal, cohort study of CRC screening outreach to 8565 patients using mailed FIT kits. Patients with abnormal FIT results received telephonic navigation to arrange for a no-cost diagnostic colonoscopy. PATIENTS Adults aged 50-64 years receiving care at a North Texas safety-net health system. APPROACH Descriptive analyses characterized the patient sample and reasons for lack of follow-up after abnormal FIT over the 3-year outreach program. Thematic qualitative analyses characterized reasons for lack of follow-up with a colonoscopy after the abnormal FIT. KEY RESULTS Of 689 patients with an abnormal FIT, 45% (n = 314) did not complete a follow-up colonoscopy. Among the 314 non-completers, 184 patients reported reasons for not completing a follow-up colonoscopy included health insurance-related challenges (38%), comorbid conditions (37%), social barriers such as transportation difficulties and lack of social support (29%), concerns about FIT/colonoscopy process (12%), competing life priorities (12%), adverse effects of bowel preparation (3%), and poor health literacy (3%). Among the 314 non-completers, 131 patients did not report a barrier, as 51% reported that that had completed a previous colonoscopy in the past 10 years, 10% refused with no reason, and 10% were never reached by phone. CONCLUSIONS Future studies aimed at improving FIT screening and subsequent colonoscopy rates need to address the unique needs of patients for effective and sustainable screening programs. TRIAL REGISTRATION NCT01946282.
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Affiliation(s)
- Katelyn K Jetelina
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center, School of Public Health, 6011 Harry Hines Blvd. V8.112, Dallas, TX, 75390, USA.
| | - Joshua S Yudkin
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center, School of Public Health, 6011 Harry Hines Blvd. V8.112, Dallas, TX, 75390, USA
| | - Stacie Miller
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.,Moncrief Cancer Center, Fort Worth, TX, USA
| | - Emily Berry
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.,Moncrief Cancer Center, Fort Worth, TX, USA
| | - Alicea Lieberman
- Rady School of Management, University of California, San Diego, San Diego, CA, USA
| | - Samir Gupta
- Department of Internal Medicine, University of California, San Diego, San Diego, CA, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center, School of Public Health, 6011 Harry Hines Blvd. V8.112, Dallas, TX, 75390, USA.,Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.,Moncrief Cancer Center, Fort Worth, TX, USA
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27
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Lieberman A, Gneezy A, Berry E, Miller S, Koch M, Ahn C, Balasubramanian BA, Argenbright KE, Gupta S. Financial Incentives to Promote Colorectal Cancer Screening: A Longitudinal Randomized Control Trial. Cancer Epidemiol Biomarkers Prev 2019; 28:1902-1908. [PMID: 31387970 DOI: 10.1158/1055-9965.epi-19-0039] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 03/22/2019] [Accepted: 07/31/2019] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Financial incentives may improve health behaviors. We tested the impact of offering financial incentives for mailed fecal immunochemical test (FIT) completion annually for 3 years. METHODS Patients, ages 50 to 64 years, not up-to-date with screening were randomized to receive either a mailed FIT outreach (n = 6,565), outreach plus $5 (n = 1,000), or $10 (n = 1,000) incentive for completion. Patients who completed the test were reinvited using the same incentive the following year, for 3 years. In year 4, patients who returned the kit in all preceding 3 years were reinvited without incentives. Primary outcome was FIT completion among patients offered any incentive versus outreach alone each year. Secondary outcomes were FIT completion for groups offered $5 versus outreach alone, $10 versus outreach alone, and $5 versus $10. RESULTS Year 1 FIT completion was 36.9% with incentives versus 36.2% outreach alone (P = 0.59) and was not statistically different for $10 (34.6%; P = 0.31) or $5 (39.2%; P = 0.070) versus outreach alone. Year 2 completion was 61.6% with incentives versus 60.8% outreach alone (P = 0.75) and not statistically different for $10 or $5 versus outreach alone. Year 3 completion was 79.4% with incentives versus 74.8% outreach alone (P = 0.080), and was higher for $10 (82.4%) versus outreach alone (P = 0.033), but not for $5 versus outreach alone. Completion was similar across conditions in year 4 (no incentives). CONCLUSIONS Offering small incentives did not increase FIT completion relative to standard outreach. IMPACT This was the first longitudinal study testing the impact of repeated financial incentives, and their withdrawal, on FIT completion.
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Affiliation(s)
- Alicea Lieberman
- Rady School of Management, University of California San Diego, La Jolla, California
| | - Ayelet Gneezy
- Rady School of Management, University of California San Diego, La Jolla, California
| | - Emily Berry
- University of Texas Southwestern Medical Center, Moncrief Cancer Institute, Fort Worth, Texas
| | - Stacie Miller
- University of Texas Southwestern Medical Center, Moncrief Cancer Institute, Fort Worth, Texas
| | - Mark Koch
- Department of Family Medicine, John Peter Smith Health Network, Fort Worth, Texas
| | - Chul Ahn
- University of Texas Southwestern Medical Center, Harold C. Simmons Cancer Center, Dallas, Texas.,Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Bijal A Balasubramanian
- Department of Epidemiology, Genetics, & Environmental Science, UT Health School of Public Health, Dallas, Texas
| | - Keith E Argenbright
- University of Texas Southwestern Medical Center, Moncrief Cancer Institute, Fort Worth, Texas.,University of Texas Southwestern Medical Center, Harold C. Simmons Cancer Center, Dallas, Texas.,Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Samir Gupta
- San Diego Veterans Affairs Healthcare System, San Diego, California. .,Department of Internal Medicine, Division of Gastroenterology, and the Moores Cancer Center, University of California San Diego, San Diego, California
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Ono SS, Crabtree BF, Hemler JR, Balasubramanian BA, Edwards ST, Green LA, Kaufman A, Solberg LI, Miller WL, Woodson TT, Sweeney SM, Cohen DJ. Taking Innovation To Scale In Primary Care Practices: The Functions Of Health Care Extension. Health Aff (Millwood) 2019; 37:222-230. [PMID: 29401016 DOI: 10.1377/hlthaff.2017.1100] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Health care extension is an approach to providing external support to primary care practices with the aim of diffusing innovation. EvidenceNOW was launched to rapidly disseminate and implement evidence-based guidelines for cardiovascular preventive care in the primary care setting. Seven regional grantee cooperatives provided the foundational elements of health care extension-technological and quality improvement support, practice capacity building, and linking with community resources-to more than two hundred primary care practices in each region. This article describes how the cooperatives varied in their approaches to extension and provides early empirical evidence that health care extension is a feasible and potentially useful approach for providing quality improvement support to primary care practices. With investment, health care extension may be an effective platform for federal and state quality improvement efforts to create economies of scale and provide practices with more robust and coordinated support services.
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Affiliation(s)
- Sarah S Ono
- Sarah S. Ono ( ) is an assistant professor in the Department of Family Medicine at Oregon Health & Science University and an investigator in the Center to Improve Veteran Involvement in Care, Veterans Affairs (VA) Portland Health Care System, both in Portland
| | - Benjamin F Crabtree
- Benjamin F. Crabtree is a professor in the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, in New Brunswick, New Jersey
| | - Jennifer R Hemler
- Jennifer R. Hemler is a research associate in the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School
| | - Bijal A Balasubramanian
- Bijal A. Balasubramanian is an associate professor in the Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, in Texas
| | - Samuel T Edwards
- Samuel T. Edwards is an assistant research professor in the Department of Family Medicine and an assistant professor of medicine at Oregon Health & Science University and a staff physician in the Section of General Internal Medicine, VA Portland Health Care System
| | - Larry A Green
- Larry A. Green is a professor of family medicine and the Epperson-Zorn Chair for Innovation in Family Medicine at the University of Colorado Denver, in Aurora
| | - Arthur Kaufman
- Arthur Kaufman is distinguished professor in the Department of Family and Community Medicine and vice chancellor for community health at the University of New Mexico, in Albuquerque
| | - Leif I Solberg
- Leif I. Solberg is a senior adviser and director for care improvement research at HealthPartners Institute, in Minneapolis, Minnesota
| | - William L Miller
- William L. Miller is chair emeritus in the Department of Family Medicine, Lehigh Valley Health Network, in Allentown, Pennsylvania
| | - Tanisha Tate Woodson
- Tanisha Tate Woodson is a senior research associate in the Department of Family Medicine, Oregon Health & Science University
| | - Shannon M Sweeney
- Shannon M. Sweeney is a research associate in the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School
| | - Deborah J Cohen
- Deborah J. Cohen is a professor and vice chair of research in the Department of Family Medicine at Oregon Health & Science University
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Cohen DJ, Dorr DA, Knierim K, DuBard CA, Hemler JR, Hall JD, Marino M, Solberg LI, McConnell KJ, Nichols LM, Nease DE, Edwards ST, Wu WY, Pham-Singer H, Kho AN, Phillips RL, Rasmussen LV, Duffy FD, Balasubramanian BA. Primary Care Practices' Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement. Health Aff (Millwood) 2019; 37:635-643. [PMID: 29608365 DOI: 10.1377/hlthaff.2017.1254] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. To determine whether EHRs produce reports adequate to the task, we examined survey responses from 1,492 practices across twelve states, supplemented with qualitative data. Meaningful-use participation, which requires the use of a federally certified EHR, was associated with the ability to generate reports-but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, such as difficulty manipulating and aligning measurement time frames with quality improvement needs, lack of functionality for generating reports on electronic clinical quality measures at different levels, discordance between clinical guidelines and measures available in reports, questionable data quality, and vendors that were unreceptive to changing EHR configuration beyond federal requirements. The current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.
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Affiliation(s)
- Deborah J Cohen
- Deborah J. Cohen ( ) is a professor of family medicine and vice chair of research in the Department of Family Medicine at Oregon Health & Science University, in Portland
| | - David A Dorr
- David A. Dorr is a professor and vice chair of medical informatics and clinical epidemiology, both at Oregon Health & Science University
| | - Kyle Knierim
- Kyle Knierim is an assistant research professor of family medicine and associate director of the Practice Innovation Program, both at the University of Colorado School of Medicine, in Aurora
| | - C Annette DuBard
- C. Annette DuBard is vice president of Clinical Strategy at Aledade, Inc., in Bethesda, Maryland
| | - Jennifer R Hemler
- Jennifer R. Hemler is a research associate in the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, in New Brunswick, New Jersey
| | - Jennifer D Hall
- Jennifer D. Hall is a research associate in family medicine at Oregon Health & Science University
| | - Miguel Marino
- Miguel Marino is an assistant professor of family medicine at Oregon Health & Science University
| | - Leif I Solberg
- Leif I. Solberg is a senior adviser and director for care improvement research at HealthPartners Institute, in Minneapolis, Minnesota
| | - K John McConnell
- K. John McConnell is a professor of emergency medicine and director of the Center for Health Systems Effectiveness, both at Oregon Health & Science University
| | - Len M Nichols
- Len M. Nichols is director of the Center for Health Policy Research and Ethics and a professor of health policy at George Mason University, in Fairfax, Virginia
| | - Donald E Nease
- Donald E. Nease Jr is an associate professor of family medicine at the University of Colorado School of Medicine, in Aurora
| | - Samuel T Edwards
- Samuel T. Edwards is an assistant research professor of family medicine and an assistant professor of medicine at Oregon Health & Science University and a staff physician in the Section of General Internal Medicine, Veterans Affairs Portland Health Care System
| | - Winfred Y Wu
- Winfred Y. Wu is clinical and scientific director in the Primary Care Information Project at the New York City Department of Health and Mental Hygiene, in Long Island City, New York
| | - Hang Pham-Singer
- Hang Pham-Singer is senior director of quality improvement in the Primary Care Information Project at the New York City Department of Health and Mental Hygiene
| | - Abel N Kho
- Abel N. Kho is an associate professor and director of the Center for Health Information Partnerships, Northwestern University, in Chicago, Illinois
| | - Robert L Phillips
- Robert L. Phillips Jr is vice president for research and policy at the American Board of Family Medicine, in Washington, D.C
| | - Luke V Rasmussen
- Luke V. Rasmussen is a clinical research associate in the Department of Preventive Medicine, Northwestern University
| | - F Daniel Duffy
- F. Daniel Duffy is professor of medical informatics and internal medicine at the University of Oklahoma School of Community Medicine-Tulsa
| | - Bijal A Balasubramanian
- Bijal A. Balasubramanian is an associate professor in the Department of Epidemiology, Human Genetics, and Environmental Sciences, and regional dean of UTHealth School of Public Health, in Dallas, Texas
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Kamineni A, Tiro JA, Beaber EF, Silverberg MJ, Wheeler CM, Chao CR, Chubak J, Skinner CS, Corley DA, Kim JJ, Balasubramanian BA, Paul Doria-Rose V. Cervical cancer screening research in the PROSPR I consortium: Rationale, methods and baseline findings from a US cohort. Int J Cancer 2018; 144:1460-1473. [PMID: 30353911 DOI: 10.1002/ijc.31940] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 09/24/2018] [Accepted: 09/28/2018] [Indexed: 11/09/2022]
Abstract
Little is known about the effect of evolving risk-based cervical cancer screening and management guidelines on United States (US) clinical practice and patient outcomes. We describe the National Cancer Institute's Population-based Research Optimizing Screening through Personalized Regimens (PROSPR I) consortium, methods and baseline findings from its cervical sites: Kaiser Permanente Washington, Kaiser Permanente Northern California, Kaiser Permanente Southern California, Parkland Health & Hospital System/University of Texas Southwestern (Parkland-UTSW) and New Mexico HPV Pap Registry housed by University of New Mexico (UNM-NMHPVPR). Across these diverse healthcare settings, we collected data on human papillomavirus (HPV) vaccinations, screening tests/results, diagnostic and treatment procedures/results and cancer diagnoses on nearly 4.7 million women aged 18-89 years from 2010 to 2014. We calculated baseline (2012 for UNM-NMHPVPR; 2010 for other sites) frequencies for sociodemographics, cervical cancer risk factors and key screening process measures for each site's cohort. Healthcare delivery settings, cervical cancer screening strategy, race/ethnicity and insurance status varied among sites. The proportion of women receiving a Pap test during the baseline year was similar across sites (26.1-36.1%). Most high-risk HPV tests were performed either reflexively or as cotests, and utilization pattern varied by site. Prevalence of colposcopy or biopsy was higher at Parkland-UTSW (3.6%) than other sites (1.3-1.4%). Incident cervical cancer was rare. HPV vaccination among age-eligible women not already immunized was modest across sites (0.1-7.2%). Cervical PROSPR I makes available high-quality, multilevel, longitudinal screening process data from a large and diverse cohort of women to evaluate and improve the effectiveness of US cervical cancer screening delivery.
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Affiliation(s)
- Aruna Kamineni
- Kaiser Permanente Washington Health Research Institute, Seattle, WA
| | - Jasmin A Tiro
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX.,Simmons Comprehensive Cancer Center, Dallas, TX
| | - Elisabeth F Beaber
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | | | - Cosette M Wheeler
- University of New Mexico Comprehensive Cancer Center, Albuquerque, NM
| | - Chun R Chao
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA
| | - Jessica Chubak
- Kaiser Permanente Washington Health Research Institute, Seattle, WA
| | - Celette Sugg Skinner
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX.,Simmons Comprehensive Cancer Center, Dallas, TX
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Jane J Kim
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Bijal A Balasubramanian
- Simmons Comprehensive Cancer Center, Dallas, TX.,UTHealth School of Public Health in Dallas, Dallas, TX
| | - V Paul Doria-Rose
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
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Lee SJC, Jetelina KK, Marks E, Shaw E, Oeffinger K, Cohen D, Santini NO, Cox JV, Balasubramanian BA. Care coordination for complex cancer survivors in an integrated safety-net system: a study protocol. BMC Cancer 2018; 18:1204. [PMID: 30514267 PMCID: PMC6278055 DOI: 10.1186/s12885-018-5118-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 11/20/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The growing numbers of cancer survivors challenge delivery of high-quality survivorship care by healthcare systems. Innovative ways to improve care coordination for patients with cancer and multiple chronic conditions ("complex cancer survivors") are needed to achieve better care outcomes, improve patient experience of care, and lower cost. Our study, Project CONNECT, will adapt and implement three evidence-based care coordination strategies, shown to be effective for primary care conditions, among complex cancer survivors. Specifically, the purpose of this study is to: 1) Implement a system-level EHR-driven intervention for 500 complex cancer survivors at Parkland; 2) Test effectiveness of the strategies on system- and patient-level outcomes measured before and after implementation; and 3) Elucidate system and patient factors that facilitate or hinder implementation and result in differences in experiences of care coordination between complex patients with and without cancer. METHODS Project CONNECT is a quasi-experimental implementation study among 500 breast and colorectal cancer survivors with at least one of the following chronic conditions: diabetes, hypertension, chronic lung disease, chronic kidney disease, or heart disease. We will implement three evidence-based care coordination strategies in a large, county integrated safety-net health system: 1) an EHR-driven registry to facilitate patient transitions between primary and oncology care; 2) co-locating a nurse practitioner trained in care coordination within a complex care team; 3) and enhancing teamwork through coaching. Segmented regression analysis will evaluate change in system-level (i.e. composite care quality score) and patient-level outcomes (i.e. self-reported care coordination). To evaluate implementation, we will merge quantitative findings with structured observations and physician and patient interviews. DISCUSSION This study will result in an evaluation toolkit identifying key model elements, barriers, and facilitators that can be used to guide care coordination interventions in other safety-net settings. Because Parkland is a vanguard of safety-net healthcare nationally, findings will be widely applicable as other safety-nets move toward increased integration, enhanced EHR capability, and experience with growing patient diversity. Our proposal recognizes the complexity of interventions and scaffolds evidence-based strategies together to meet the needs of complex patients, systems of care, and service integration. TRIAL REGISTRATION ClinicalTrials.gov, NCT02943265 . Registered 24 October 2016.
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Affiliation(s)
- Simon J. Craddock Lee
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, E5.506, Dallas, TX 75390-9066 USA
- Harold C. Simmons Comprehensive Cancer Center, 2201 Inwood Road, Dallas, TX 75235 USA
| | - Katelyn K. Jetelina
- Department of Epidemiology, University of Texas Health Science Center, School of Public Health, 6011 Harry Hines Blvd, V8.112, Dallas, TX 75235 USA
| | - Emily Marks
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, E5.506, Dallas, TX 75390-9066 USA
| | - Eric Shaw
- Department of Community Medicine, Mercer University, 1250 E. 66th St, Savannah, GA 31404 USA
| | - Kevin Oeffinger
- Department of Medicine, Division of Medical Oncology, Duke Cancer Institute and Duke University Medical Center, 20 Duke Medicine Cir, Durham, NC 27710 USA
| | - Deborah Cohen
- Department of Family Medicine, Oregon Health and Science Center, 3181 SW Sam Jackson Park Rd, Portland, OR 97239-3098 USA
| | - Noel O. Santini
- Parkland Health and Hospital System, 5201 Harry Hines Blvd, Dallas, TX 75235 USA
| | - John V. Cox
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, E5.506, Dallas, TX 75390-9066 USA
- Parkland Health and Hospital System, 5201 Harry Hines Blvd, Dallas, TX 75235 USA
| | - Bijal A. Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, 2201 Inwood Road, Dallas, TX 75235 USA
- Department of Epidemiology, University of Texas Health Science Center, School of Public Health, 6011 Harry Hines Blvd, V8.112, Dallas, TX 75235 USA
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32
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Hughes AE, Tiro JA, Balasubramanian BA, Skinner CS, Pruitt SL. Social Disadvantage, Healthcare Utilization, and Colorectal Cancer Screening: Leveraging Longitudinal Patient Address and Health Records Data. Cancer Epidemiol Biomarkers Prev 2018; 27:1424-1432. [PMID: 30135072 PMCID: PMC6279539 DOI: 10.1158/1055-9965.epi-18-0446] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 07/11/2018] [Accepted: 08/17/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Social disadvantage predicts colorectal cancer outcomes across the cancer care continuum for many populations and places. For medically underserved populations, social disadvantage is likely intersectional-affecting individuals at multiple levels and through membership in multiple disadvantaged groups. However, most measures of social disadvantage are cross-sectional and limited to race, ethnicity, and income. Linkages between electronic health records (EHR) and external datasets offer rich, multilevel measures that may be more informative. METHODS We identified urban safety-net patients eligible and due for colorectal cancer screening from the Parkland-UT Southwestern PROSPR cohort. We assessed one-time screening receipt (via colonoscopy or fecal immunochemical test) in the 18 months following cohort entry via the EHR. We linked EHR data to housing and Census data to generate measures of social disadvantage at the parcel- and block-group level. We evaluated the association of these measures with screening using multilevel logistic regression models controlling for sociodemographics, comorbidity, and healthcare utilization. RESULTS Among 32,965 patients, 45.1% received screening. In adjusted models, residential mobility, residence type, and neighborhood majority race were associated with colorectal cancer screening. Nearly all measures of patient-level social disadvantage and healthcare utilization were significant. CONCLUSIONS Address-based linkage of EHRs to external datasets may have the potential to expand meaningful measurement of multilevel social disadvantage. Researchers should strive to use granular, specific data in investigations of social disadvantage. IMPACT Generating multilevel measures of social disadvantage through address-based linkages efficiently uses existing EHR data for applied, population-level research.
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Affiliation(s)
- Amy E Hughes
- Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, Texas.
| | - Jasmin A Tiro
- Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Bijal A Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
- Department of Epidemiology, Human Genetics, and Environmental Sciences UTHealth in Dallas, Dallas, Texas
| | - Celette Sugg Skinner
- Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Sandi L Pruitt
- Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, Texas
- Harold C. Simmons Comprehensive Cancer Center, Dallas, Texas
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Woodson TT, Gunn R, Clark KD, Balasubramanian BA, Jetelina KK, Muller B, Miller BF, Burdick TE, Cohen DJ. Designing health information technology tools for behavioral health clinicians integrated within a primary care team. J Innov Health Inform 2018; 25:158-168. [PMID: 30398459 PMCID: PMC6779316 DOI: 10.14236/jhi.v25i3.998] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 04/27/2018] [Accepted: 06/08/2018] [Indexed: 01/11/2023] Open
Abstract
Background Electronic health records (EHRs) are a key tool for primary care practice. However, the EHR functionality is not keeping pace with the evolving informational and decision-support needs of behavioural health clinicians (BHCs) working on integrated teams. Objective Describe the workflows and tasks of integrated BHCs working with adult patients identify their health information technology (health IT) needs and develop EHR tools to address them. Method A mixed-methods, comparative case study of six community health centres (CHCs) in Oregon, each with at least one BHC integrated into their primary care team. We observed clinical work and conducted interviews to understand workflows and clinical tasks, aiming to identify how effectively current EHRs supported integrated care delivery, including transitions, documentation, information sharing and decision-making. We analysed these data and employed a user-centred design process to develop EHR tools addressing the identified needs. Results BHCs used the primary care EHR for documentation and communication with other team members, but the EHR lacked the functionality to fully support integrated care. Needs include the ability to: (1) automate and track paper-based screening; (2) document behavioural health history; (3) access patient social and medical history relevant to behavioural health issues and (4) rapidly document and track progress on goals. To meet these needs, we engaged users and developed a set of EHR tools called the Behavioural Health e-Suite (BH e-Suite). Conclusion US-based integrated primary care teams, and particularly BHCs working with adult populations, have unique information needs, workflows and tasks. These needs can be met and supported by the EHR with a moderate level of modification.
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Affiliation(s)
- Tanisha Tate Woodson
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, USA.
| | - Rose Gunn
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, USA.
| | - Khaya D Clark
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, USA.
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas School of Public Health-Dallas Campus, Dallas, TX, USA.
| | - Katelyn K Jetelina
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas School of Public Health-Dallas Campus, Dallas, TX, USA.
| | - Brianna Muller
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, USA.
| | - Benjamin F Miller
- Eugene S. Farley, Jr. Health Policy Center, Department of Family Medicine, University of Colorado School of Medicine, Denver, CO, USA.
| | - Timothy E Burdick
- Department of Community & Family Medicine, Geisel School of Medicine at Dartmouth, Hanover, NH; Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH; Department of Medical Informatics & Clinical Epidemiology, OHSU School of Medicine, Portland, OR.
| | - Deborah J Cohen
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, USA.
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Pruitt SL, Werner CL, Borton EK, Sanders JM, Balasubramanian BA, Barnes A, Betts AC, Skinner CS, Tiro JA. Cervical Cancer Burden and Opportunities for Prevention in a Safety-Net Healthcare System. Cancer Epidemiol Biomarkers Prev 2018; 27:1398-1406. [PMID: 30185535 DOI: 10.1158/1055-9965.epi-17-0912] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 01/29/2018] [Accepted: 08/30/2018] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The high prevalence of cervical cancer at safety-net health systems requires careful analysis to best inform prevention and quality improvement efforts. We characterized cervical cancer burden and identified opportunities for prevention in a U.S. safety-net system. METHODS We reviewed tumor registry and electronic health record (EHR) data of women with invasive cervical cancer with ages 18+, diagnosed between 2010 and 2015, in a large, integrated urban safety-net. We developed an algorithm to: (i) classify whether women had been engaged in care (≥1 clinical encounter between 6 months and 5 years before cancer diagnosis); and (ii) identify missed opportunities (no screening, no follow-up, failure of a test to detect cancer, and treatment failure) and associated factors among engaged patients. RESULTS Of 419 women with cervical cancer, more than half (58%) were stage 2B or higher at diagnosis and 40% were uninsured. Most (69%) had no prior healthcare system contact; 47% were diagnosed elsewhere. Among 122 engaged in care prior to diagnosis, failure to screen was most common (63%), followed by lack of follow-up (21%), and failure of test to detect cancer (16%). Tumor stage, patient characteristics, and healthcare utilization differed across groups. CONCLUSIONS Safety-net healthcare systems face a high cervical cancer burden, mainly from women with no prior contact with the system. To prevent or detect cancer early, community-based efforts should encourage uninsured women to use safety-nets for primary care and preventive services. IMPACT Among engaged patients, strategies to increase screening and follow-up of abnormal screening tests could prevent over 80% of cervical cancer cases.
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Affiliation(s)
- Sandi L Pruitt
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Texas. .,Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
| | - Claudia L Werner
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, Dallas, Texas.,Parkland Health and Hospital System, Dallas, Texas
| | - Eric K Borton
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Texas
| | - Joanne M Sanders
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Texas
| | - Bijal A Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas
| | - Arti Barnes
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Andrea C Betts
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Texas.,Department of Health Promotion and Behavioral Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas
| | - Celette Sugg Skinner
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Texas.,Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
| | - Jasmin A Tiro
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Texas.,Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
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35
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Jetelina KK, Woodson TT, Gunn R, Muller B, Clark KD, DeVoe JE, Balasubramanian BA, Cohen DJ. Evaluation of an Electronic Health Record (EHR) Tool for Integrated Behavioral Health in Primary Care. J Am Board Fam Med 2018; 31:712-723. [PMID: 30201667 PMCID: PMC6261664 DOI: 10.3122/jabfm.2018.05.180041] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 05/21/2018] [Accepted: 05/25/2018] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Integrating behavioral health into primary care can improve care quality; however, most electronic health records are not designed to meet the needs of integrated teams. We worked with practices and behavioral health (BH) clinicians to design a suite of electronic health record tools to address these needs ("BH e-Suite"). The purpose of this article is to examine whether implementation of the BH e-Suite changes process of care, intermediate clinical outcomes, and patient experiences, and whether its use is acceptable to practice members and BH clinicians. METHODS We conducted a convergent mixed-methods proof-of-concept study, implementing the BH e-Suite across 6 Oregon federally qualified community health centers ("intervention clinics"). We matched intervention clinics to 6 control clinics, based on location and patient panel characteristics, to assess whether process of care (Patient Health Questionnaire-9 [PHQ-9] and Generalized Anxiety Disorder-7 screening) and intermediate outcomes (PHQ-9, Generalized Anxiety Disorder-7 scores) changed postimplementation. Prepost patient surveys were used to assess changes in patient experience. To elucidate factors influencing implementation, we merged quantitative findings with structured observations, surveys, and interviews with practice members. RESULTS Implementation improved process of care (PHQ-9 screening). During the course of the study, change in intermediate outcomes was not observed. Degree of BH e-Suite implementation varied: 2 clinics fully implemented, 2 partially implemented, and 2 practices did not implement at all. Initial practice conditions (eg, low resistance to change, higher capacity), process characteristics (eg, thoughtful planning), and individual characteristics (eg, high self-efficacy) were related to degree of implementation. CONCLUSIONS Health information technology tools designed for behavioral health integration must fit the needs of clinics for the successful uptake and improvement in patient experiences. Research is needed to further assess the effectiveness of this tool in improving patient outcomes and to optimize broader dissemination of this tool among primary care clinics integrating behavioral health.
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Affiliation(s)
- Katelyn K Jetelina
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED).
| | - Tanisha Tate Woodson
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
| | - Rose Gunn
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
| | - Brianna Muller
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
| | - Khaya D Clark
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
| | - Jennifer E DeVoe
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
| | - Bijal A Balasubramanian
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
| | - Deborah J Cohen
- From Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (KKJ, BAB); Department of Family Medicine, Oregon Health & Science University, Portland, OR (TTW, RG, BM, KDC, JED, DJC); OCHIN, Inc., Portland (JED)
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Balasubramanian BA, Jetelina KK, Bowen M, Santini NO, Lee SC. Surveillance for colorectal cancer survivors in an integrated safety-net health system in the United States. Int J Care Coord 2018; 21:26-35. [PMID: 30364563 DOI: 10.1177/2053434518764634] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Introduction Guideline-recommended surveillance reduces likelihood of colorectal cancer (CRC) recurrence, yet surveillance rates are low in the United States (US). Little is known about CRC surveillance rates among patients without health insurance and their primary care clinicians/oncologists' attitudes towards surveillance care. Methods A retrospective study of 205 patients diagnosed with Stage I-III CRC from 2008-2010 was conducted in an integrated system with a network of providers delivering care to patients lacking health insurance coverage. Surveillance patterns were characterized from medical records and logistic regression models examined correlates of guideline-concordant surveillance. 41 Parkland primary care physicians (PCPs) and 24 oncologists completed surveys to assess their attitudes and practices regarding CRC surveillance. Results 38% of CRC patients received guideline-concordant surveillance; those with early stage cancers were less likely to receive surveillance (OR=0.35; 95 CI: 0.14, 0.87). PCPs and oncologists differed markedly on who is responsible for cancer surveillance care. 77% of oncologists responded that PCPs evaluated patients for cancer recurrence while 76% of PCPs responded that these services were either ordered by oncologists or shared with PCPs. 67% of oncologists said they rarely provide a treatment and surveillance care plan to survivors and over half said that they infrequently communicate with patients' other physicians about who will follow patients for their cancer and other medical issues. Discussion Care coordination between PCP and oncologist is needed to improve CRC surveillance. New models of shared care clearly delineating roles for oncologists and PCPs are needed to improve CRC survivorship care.
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Affiliation(s)
- Bijal A Balasubramanian
- UTHealth School of Public Health in Dallas, Dallas, TX.,Harold C. Simmons Comprehensive Cancer Center, Dallas, TX
| | | | - Michael Bowen
- University of Texas Southwestern Medical Center, Dallas, TX
| | | | - Simon Craddock Lee
- University of Texas Southwestern Medical Center, Dallas, TX.,Harold C. Simmons Comprehensive Cancer Center, Dallas, TX
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Balasubramanian BA, Marino M, Cohen DJ, Ward RL, Preston A, Springer RJ, Lindner SR, Edwards S, McConnell KJ, Crabtree BF, Miller WL, Stange KC, Solberg LI. Use of Quality Improvement Strategies Among Small to Medium-Size US Primary Care Practices. Ann Fam Med 2018; 16:S35-S43. [PMID: 29632224 PMCID: PMC5891312 DOI: 10.1370/afm.2172] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 11/07/2017] [Accepted: 11/15/2017] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Improving primary care quality is a national priority, but little is known about the extent to which small to medium-size practices use quality improvement (QI) strategies to improve care. We examined variations in use of QI strategies among 1,181 small to medium-size primary care practices engaged in a national initiative spanning 12 US states to improve quality of care for heart health and assessed factors associated with those variations. METHODS In this cross-sectional study, practice characteristics were assessed by surveying practice leaders. Practice use of QI strategies was measured by the validated Change Process Capability Questionnaire (CPCQ) Strategies Scale (scores range from -28 to 28, with higher scores indicating more use of QI strategies). Multivariable linear regression was used to examine the association between practice characteristics and the CPCQ strategies score. RESULTS The mean CPCQ strategies score was 9.1 (SD = 12.2). Practices that participated in accountable care organizations and those that had someone in the practice to configure clinical quality reports from electronic health records (EHRs), had produced quality reports, or had discussed clinical quality data during meetings had higher CPCQ strategies scores. Health system-owned practices and those experiencing major disruptive changes, such as implementing a new EHR system or clinician turnover, had lower CPCQ strategies scores. CONCLUSION There is substantial variation in the use of QI strategies among small to medium-size primary care practices across 12 US states. Findings suggest that practices may need external support to strengthen their ability to do QI and to be prepared for new payment and delivery models.
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Affiliation(s)
- Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Miguel Marino
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Deborah J Cohen
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Rikki L Ward
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Alex Preston
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Rachel J Springer
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Stephan R Lindner
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Samuel Edwards
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - K John McConnell
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Benjamin F Crabtree
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - William L Miller
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Kurt C Stange
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
| | - Leif I Solberg
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, Texas (Balasubramanian, Ward, Preston); Department of Family Medicine, Oregon Health & Science University, Portland, Oregon (Marino, Cohen, Springer, Edwards); School of Public Health, Oregon Health & Science University - Portland State University, Portland, Oregon (Marino); Center for Health Systems Effectiveness, and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon (Lindner, McConnell); Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (Crabtree); Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania (Miller); Center for Community Health Integration, Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, Ohio (Stange); HealthPartners Institute, Minneapolis, Minnesota (Solberg); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, Oregon (Edwards)
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Lee SJC, Inrig SJ, Balasubramanian BA, Skinner CS, Higashi RT, McCallister K, Bishop WP, Santini NO, Tiro JA. Identifying quality improvement targets to facilitate colorectal cancer screening completion. Prev Med Rep 2018. [PMID: 29527466 PMCID: PMC5840842 DOI: 10.1016/j.pmedr.2018.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The colorectal cancer (CRC) screening process involves multiple interfaces (communication exchanges and transfers of responsibility for specific actions) among primary care and gastroenterology providers, laboratory, and administrative staff. After a retrospective electronic health record (EHR) analysis discovered substantial clinic variation and low CRC screening prevalence overall in an urban, integrated safety-net system, we launched a qualitative analysis to identify potential quality improvement targets to enhance fecal immunochemical test (FIT) completion, the system's preferred screening modality. Here, we report examination of organization-, clinic-, and provider-level interfaces over a three-year period (December 2011–October 2014). We deployed in parallel 3 qualitative data collection methods: (1) structured observation (90+ hours, 10 sites); (2) document analysis (n > 100); and (3) semi-structured interviews (n = 41) and conducted iterative thematic analysis in which findings from each method cross-informed subsequent data collection. Thematic analysis was guided by a conceptual model and applied deductive and inductive codes. There was substantial variation in protocols for distributing and returning FIT kits both within and across clinics. Providers, clinic and laboratory staff had differing access to important data about FIT results based on clinical information system used and this affected results reporting. Communication and coordination during electronic referrals for diagnostic colonoscopy was suboptimal particularly for co-morbid patients needing anesthesia clearance. Our multi-level approach elucidated organizational deficiencies not evident by quantitative analysis alone. Findings indicate potential quality improvement intervention targets including: (1) best-practices implementation across clinics; (2) detailed communication to providers about FIT results; and (3) creation of EHR alerts to resolve pending colonoscopy referrals before they expire. Multi-level qualitative approach identified challenges to 3 clinical processes Variation in fecal immunochemical testing (FIT) kit distribution and return Incomplete transfer of key FIT result data across clinical information systems Suboptimal communication and coordination during colonoscopy referrals
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Affiliation(s)
- Simon J Craddock Lee
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA
| | - Stephen J Inrig
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA.,Mount St. Mary's University, Los Angeles, CA, USA
| | - Bijal A Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA.,Department of Epidemiology, Human Genetics, and Environmental Sciences, UT Health School of Public Health - Dallas Campus, Dallas, TX, USA
| | - Celette Sugg Skinner
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA
| | - Robin T Higashi
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA
| | | | - Wendy Pechero Bishop
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA
| | | | - Jasmin A Tiro
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA
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Malhotra J, Rotter D, Tsui J, Llanos AAM, Balasubramanian BA, Demissie K. Impact of Patient-Provider Race, Ethnicity, and Gender Concordance on Cancer Screening: Findings from Medical Expenditure Panel Survey. Cancer Epidemiol Biomarkers Prev 2017; 26:1804-1811. [PMID: 29021217 DOI: 10.1158/1055-9965.epi-17-0660] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 09/08/2017] [Accepted: 10/03/2017] [Indexed: 11/16/2022] Open
Abstract
Background: Racial and ethnic minorities experience lower rates of cancer screening compared with non-Hispanic whites (NHWs). Previous studies evaluating the role of patient-provider race, ethnicity, or gender concordance in cancer screening have been inconclusive.Methods: In a cross-sectional analysis using the Medical Expenditure Panel Survey (MEPS), data from 2003 to 2010 were assessed for associations between patient-provider race, ethnicity, and/or gender concordance and, screening (American Cancer Society guidelines) for breast, cervical, and colorectal cancer. Multivariable logistic analyses were conducted to examine associations of interest.Results: Of the 32,041 patient-provider pairs in our analysis, more than 60% of the patients were NHW, 15% were non-Hispanic black (NHB), and 15% were Hispanic. Overall, patients adherent to cancer screening were more likely to be non-Hispanic, better educated, married, wealthier, and privately insured. Patient-provider gender discordance was associated with lower rates of breast [OR, 0.83; 95% confidence interval (CI), 0.76-0.90], cervical (OR, 0.83; 95% CI, 0.76-0.91), and colorectal cancer (OR, 0.84; 95% CI, 0.79-0.90) screening in all patients. This association was also significant after adjusting for racial and/or ethnic concordance. Conversely, among NHWs and NHBs, patient-provider racial and/or ethnic concordance was not associated with screening. Among Hispanics, patient-provider ethnic discordant pairs had higher breast (58% vs. 52%) and colorectal cancer (45% vs. 39%) screening rates compared with concordant pairs.Conclusions: Patient-provider gender concordance positively affected cancer screening. Patient-provider ethnic concordance was inversely associated with receipt of cancer screening among Hispanics. This counter-intuitive finding requires further study.Impact: Our findings highlight the importance of gender concordance in improving cancer screening rates. Cancer Epidemiol Biomarkers Prev; 26(12); 1804-11. ©2017 AACR.
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Affiliation(s)
- Jyoti Malhotra
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.
| | - David Rotter
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| | - Jennifer Tsui
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| | - Adana A M Llanos
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.,Department of Epidemiology, Rutgers School of Public Health, Piscataway, New Jersey
| | | | - Kitaw Demissie
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.,Department of Epidemiology, Rutgers School of Public Health, Piscataway, New Jersey
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Krist AH, Glasgow RE, Heurtin-Roberts S, Sabo RT, Roby DH, Gorin SNS, Balasubramanian BA, Estabrooks PA, Ory MG, Glenn BA, Phillips SM, Kessler R, Johnson SB, Rohweder CL, Fernandez ME. The impact of behavioral and mental health risk assessments on goal setting in primary care. Transl Behav Med 2017; 6:212-9. [PMID: 27356991 DOI: 10.1007/s13142-015-0384-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Patient-centered health risk assessments (HRAs) that screen for unhealthy behaviors, prioritize concerns, and provide feedback may improve counseling, goal setting, and health. To evaluate the effectiveness of routinely administering a patient-centered HRA, My Own Health Report, for diet, exercise, smoking, alcohol, drug use, stress, depression, anxiety, and sleep, 18 primary care practices were randomized to ask patients to complete My Own Health Report (MOHR) before an office visit (intervention) or continue usual care (control). Intervention practice patients were more likely than control practice patients to be asked about each of eight risks (range of differences 5.3-15.8 %, p < 0.001), set goals for six risks (range of differences 3.8-16.6 %, p < 0.01), and improve five risks (range of differences 5.4-13.6 %, p < 0.01). Compared to controls, intervention patients felt clinicians cared more for them and showed more interest in their concerns. Patient-centered health risk assessments improve screening and goal setting.Trial RegistrationClinicaltrials.gov identifier: NCT01825746.
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Affiliation(s)
- Alex H Krist
- Department of Family Medicine and Population Health, Virginia Commonwealth University, PO Box 980101, Richmond, VA, 23298, USA.
| | - Russell E Glasgow
- Department of Family Medicine, University of Colorado School of Medicine, Denver, CO, USA
| | - Suzanne Heurtin-Roberts
- Implementation Science Team, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Roy T Sabo
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA
| | - Dylan H Roby
- School of Public Health, University of Maryland, College Park, MD, USA
| | - Sherri N Sheinfeld Gorin
- Division of Cancer Control and Population Sciences (Leidos Biomedical Research, Inc.), National Cancer Institute, Rockville, MD, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Science, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX, USA
| | - Paul A Estabrooks
- Department of Family and Community Medicine, Carilion Clinic, Roanoke, VA, USA
- Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, USA
| | - Marcia G Ory
- Department of Health Promotion and Community Health Sciences, Texas A&M Health Sciences Center School of Public Health, College Station, TX, USA
| | - Beth A Glenn
- Department of Health Policy & Management, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Siobhan M Phillips
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Rodger Kessler
- Department of Family Medicine, University of Vermont, Burlington, VT, USA
| | - Sallie Beth Johnson
- Department of Family and Community Medicine, Carilion Clinic, Roanoke, VA, USA
- Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, USA
| | - Catherine L Rohweder
- Consortium for Implementation Science, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Maria E Fernandez
- School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
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Malhotra J, Rotter D, Tsui J, Llanos A, Balasubramanian BA, Demissie K. Impact of patient-provider race/ethnicity and gender concordance on cancer screening: Findings from medical expenditure panel survey. J Clin Oncol 2017. [DOI: 10.1200/jco.2017.35.15_suppl.1547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
1547 Background: Racial/ethnic minority groups experience lower rates of cancer screening compared to non-Hispanic (NH) whites. Previous studies evaluating the role of patient-provider race/ethnicity and gender concordance in cancer screening have been inconclusive. Methods: We conducted a cross-sectional study of 18,690 patient-provider pairs using the 2003-2010 Medical Expenditure Panel Survey (MEPS) data. We assessed association between patient-provider race/ethnicity and gender concordance and, screening adherence for breast, cervical, and colorectal cancer using American Cancer Society guidelines. Separate multivariable logistic regression adjusting for demographics, self-reported health and MEPS survey year were conducted to examine relationships of interest. Results: Seventy percent of patients were NH-white, 15% were NH-black and 15% were Hispanic. Patients adherent to cancer screening were more likely to be non-Hispanic, better educated, married, wealthier, and privately insured. Among NH-black and NH-whites, patient-provider racial/ethnic concordance was not associated with screening adherence. Among Hispanics, patient-provider racial/ethnic discordant pairs had higher colorectal cancer screening rates as compared to concordant pairs (OR 1.48; 95% CI 1.28-1.71). This association was significant even on adjusting for gender concordance and survey language (English vs. Spanish). Conversely, patient-provider gender discordance was associated with lower rates of breast (OR 0.81; 95% CI 0.74-0.89), cervical (OR 0.79; 95% CI 0.72-0.87) and colorectal cancer (OR 0.86; 95% CI 0.80-0.93) screening adherence in all patients. This association was also significant on restricting analysis to racial/ethnic concordant pairs. Conclusions: Patient-provider gender concordance positively impacts adherence to cancer screening and this finding may guide future interventions. Patient-provider racial/ethnic concordance is not associated with screening adherence among whites and blacks but Hispanic patients seen by Hispanic providers have lower colorectal cancer screening rates. This counter-intuitive finding requires further study.
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Affiliation(s)
- Jyoti Malhotra
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ
| | - David Rotter
- The State University of New Jersey, New Brunswck, NJ
| | - Jennifer Tsui
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ
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Balasubramanian BA, Garcia MP, Corley DA, Doubeni CA, Haas JS, Kamineni A, Quinn VP, Wernli K, Zheng Y, Skinner CS. Racial/ethnic differences in obesity and comorbidities between safety-net- and non safety-net integrated health systems. Medicine (Baltimore) 2017; 96:e6326. [PMID: 28296752 PMCID: PMC5369907 DOI: 10.1097/md.0000000000006326] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Previous research shows that patients in integrated health systems experience fewer racial disparities compared with more traditional healthcare systems. Little is known about patterns of racial/ethnic disparities between safety-net and non safety-net integrated health systems.We evaluated racial/ethnic differences in body mass index (BMI) and the Charlson comorbidity index from 3 non safety-net- and 1 safety-net integrated health systems in a cross-sectional study. Multinomial logistic regression modeled comorbidity and BMI on race/ethnicity and health care system type adjusting for age, sex, insurance, and zip-code-level incomeThe study included 1.38 million patients. Higher proportions of safety-net versus non safety-net patients had comorbidity score of 3+ (11.1% vs. 5.0%) and BMI ≥35 (27.7% vs. 15.8%). In both types of systems, blacks and Hispanics were more likely than whites to have higher BMIs. Whites were more likely than blacks or Hispanics to have higher comorbidity scores in a safety net system, but less likely to have higher scores in the non safety-nets. The odds of comorbidity score 3+ and BMI 35+ in blacks relative to whites were significantly lower in safety-net than in non safety-net settings.Racial/ethnic differences were present within both safety-net and non safety-net integrated health systems, but patterns differed. Understanding patterns of racial/ethnic differences in health outcomes in safety-net and non safety-net integrated health systems is important to tailor interventions to eliminate racial/ethnic disparities in health and health care.
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Affiliation(s)
- Bijal A. Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX
| | - Michael P. Garcia
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Douglas A. Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Chyke A. Doubeni
- Department of Family Medicine and Community Health, and the Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jennifer S. Haas
- Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA
| | | | - Virginia P. Quinn
- Research & Evaluation Department, Kaiser Permanente Southern California, Pasadena, CA
| | | | - Yingye Zheng
- Department of Biostatistics and Biomathematics, Division of Public Health Science, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Celette Sugg Skinner
- Department of Clinical Sciences and Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical School, Dallas, TX
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Martin J, Halm EA, Tiro JA, Merchant Z, Balasubramanian BA, McCallister K, Sanders JM, Ahn C, Bishop WP, Singal AG. Reasons for Lack of Diagnostic Colonoscopy After Positive Result on Fecal Immunochemical Test in a Safety-Net Health System. Am J Med 2017; 130:93.e1-93.e7. [PMID: 27591183 PMCID: PMC5164844 DOI: 10.1016/j.amjmed.2016.07.028] [Citation(s) in RCA: 80] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 07/26/2016] [Accepted: 07/26/2016] [Indexed: 12/14/2022]
Abstract
BACKGROUND Effective colorectal cancer screening depends on timely diagnostic evaluation in patients with abnormal results on fecal immunochemical tests (FITs). Although prior studies suggest low rates of follow-up colonoscopy, there is little information among patients in safety-net health systems and few data characterizing reasons for low follow-up rates. This study aimed to characterize factors contributing to lack of follow-up colonoscopy in a racially diverse and socioeconomically disadvantaged cohort of patients with abnormal results on FIT ("abnormal FIT" for brevity) receiving care in an integrated safety-net health system. METHODS We performed a retrospective electronic medical record review of patients aged 50-64 years with abnormal FIT at a population-based safety-net health system between January 2010 and July 2013. Review of electronic medical records focused on patients without follow-up colonoscopy to characterize patient-, provider-, and system-level reasons for lack of diagnostic evaluation. We used logistic regression analysis to identify predictors of follow-up colonoscopy within 12 months of abnormal FIT. RESULTS Of 1267 patients with abnormal FIT, 536 (42.3%) failed to undergo follow-up colonoscopy within 1 year. Failure was attributable to patient-level factors in 307 (57%) cases, provider factors in 97 (18%) cases, and system factors in 118 (22%) cases. In multivariate analysis, follow-up colonoscopy was less likely among those aged 61-64 years (odds ratio 0.63, 95% confidence interval 0.46-0.87) compared with 50-55 year olds. CONCLUSIONS Nearly half (42%) of patients with abnormal FIT failed to undergo follow-up colonoscopy within 1 year. Lack of diagnostic evaluation is related to a combination of patient-, provider-, and system-level factors, highlighting the need for multilevel interventions to improve follow-up colonoscopy completion rates.
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Affiliation(s)
- Jason Martin
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Tex; Parkland Health & Hospital System, Dallas, Tex
| | - Ethan A Halm
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Tex; Parkland Health & Hospital System, Dallas, Tex; Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Tex; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Tex
| | - Jasmin A Tiro
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Tex; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Tex
| | - Zahra Merchant
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Tex
| | - Bijal A Balasubramanian
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Tex; Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health - Dallas Campus, Dallas, Tex
| | | | - Joanne M Sanders
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Tex
| | - Chul Ahn
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Tex; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Tex
| | - Wendy Pechero Bishop
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Tex; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Tex
| | - Amit G Singal
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Tex; Parkland Health & Hospital System, Dallas, Tex; Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, Tex; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Tex.
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Barlow CE, Shuval K, Balasubramanian BA, Kendzor DE, Radford NB, DeFina LF, Gabriel KP. Association Between Sitting Time and Cardiometabolic Risk Factors After Adjustment for Cardiorespiratory Fitness, Cooper Center Longitudinal Study, 2010-2013. Prev Chronic Dis 2016; 13:E181. [PMID: 28033088 PMCID: PMC5201150 DOI: 10.5888/pcd13.160263] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Introduction Objective estimates, based on waist-worn accelerometers, indicate that adults spend over half their day (55%) in sedentary behaviors. Our study examined the association between sitting time and cardiometabolic risk factors after adjustment for cardiorespiratory fitness (CRF). Methods A cross-sectional analysis was conducted with 4,486 men and 1,845 women who reported daily estimated sitting time, had measures for adiposity, blood lipids, glucose, and blood pressure, and underwent maximal stress testing. We used a modeling strategy using logistic regression analysis to assess CRF as a potential effect modifier and to control for potential confounding effects of CRF. Results Men who sat almost all of the time (about 100%) were more likely to be obese whether defined by waist girth (OR, 2.61; 95% CI, 1.25–5.47) or percentage of body fat (OR, 3.33; 95% CI, 1.35–8.20) than were men who sat almost none of the time (about 0%). Sitting time was not significantly associated with other cardiometabolic risk factors after adjustment for CRF level. For women, no significant associations between sitting time and cardiometabolic risk factors were observed after adjustment for CRF and other covariates. Conclusion As health professionals struggle to find ways to combat obesity and its health effects, reducing sitting time can be an initial step in a total physical activity plan that includes strategies to reduce sedentary time through increases in physical activity among men. In addition, further research is needed to elucidate the relationships between sitting time and CRF for women as well as the underlying mechanisms involved in these relationships.
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Affiliation(s)
- Carolyn E Barlow
- The Cooper Institute, Dallas, Texas.,The Cooper Institute, 12330 Preston Rd, Dallas, TX 75230.
| | - Kerem Shuval
- Department of Intramural Research, American Cancer Society, Atlanta, Georgia
| | - Bijal A Balasubramanian
- University of Texas Health Science Center at Houston School of Public Health - Dallas Campus, Dallas, Texas.,University of Texas Southwestern Medical Center - Harold C. Simmons Cancer Center, Dallas, Texas
| | - Darla E Kendzor
- Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.,Oklahoma Tobacco Research Center, Stephenson Cancer Center, Oklahoma City, Oklahoma
| | | | | | - Kelley Pettee Gabriel
- University of Texas Health Science Center at Houston School of Public Health - Austin Campus, Austin, Texas
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Lee SJC, Clark MA, Cox JV, Needles BM, Seigel C, Balasubramanian BA. Achieving Coordinated Care for Patients With Complex Cases of Cancer: A Multiteam System Approach. J Oncol Pract 2016; 12:1029-1038. [PMID: 27577621 PMCID: PMC5356468 DOI: 10.1200/jop.2016.013664] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Patients with cancer with multiple chronic conditions pose a unique challenge to how primary care and specialty care teams provide well-coordinated, patient-centered care. Effectiveness of these care teams in providing optimal health care depends on the extent to which they coordinate their goals and knowledge as components of a multiteam system (MTS). This article outlines challenges of care coordination in the context of an MTS, illustrated through the care experience of "Mr Fuentes," a patient in the Dallas County integrated safety-net system, Parkland. As a continuing patient with chronic illnesses, the patient being discussed is managed through one of the Parkland community-oriented primary care clinics. However, a cancer diagnosis triggered an additional need for augmented coordination between his different provider teams. Further research and practice should investigate the relationships of MTS coordination for shared care management, transfer to and from specialty care, treatment compliance, barriers to care, and health outcomes of chronic comorbid conditions, as well as cancer control and surveillance.
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Affiliation(s)
- Simon J. Craddock Lee
- University of Texas Southwestern Medical Center; Harold C. Simmons Comprehensive Cancer Center; Parkland Health and Hospital System; University of Texas School of Public Health, Dallas, TX; Kogod School of Business, American University, Washington, DC; Mercy Hospital, St Louis, MO; and Massachusetts General Hospital Cancer Center, Boston, MA
| | - Mark A. Clark
- University of Texas Southwestern Medical Center; Harold C. Simmons Comprehensive Cancer Center; Parkland Health and Hospital System; University of Texas School of Public Health, Dallas, TX; Kogod School of Business, American University, Washington, DC; Mercy Hospital, St Louis, MO; and Massachusetts General Hospital Cancer Center, Boston, MA
| | - John V. Cox
- University of Texas Southwestern Medical Center; Harold C. Simmons Comprehensive Cancer Center; Parkland Health and Hospital System; University of Texas School of Public Health, Dallas, TX; Kogod School of Business, American University, Washington, DC; Mercy Hospital, St Louis, MO; and Massachusetts General Hospital Cancer Center, Boston, MA
| | - Burton M. Needles
- University of Texas Southwestern Medical Center; Harold C. Simmons Comprehensive Cancer Center; Parkland Health and Hospital System; University of Texas School of Public Health, Dallas, TX; Kogod School of Business, American University, Washington, DC; Mercy Hospital, St Louis, MO; and Massachusetts General Hospital Cancer Center, Boston, MA
| | - Carole Seigel
- University of Texas Southwestern Medical Center; Harold C. Simmons Comprehensive Cancer Center; Parkland Health and Hospital System; University of Texas School of Public Health, Dallas, TX; Kogod School of Business, American University, Washington, DC; Mercy Hospital, St Louis, MO; and Massachusetts General Hospital Cancer Center, Boston, MA
| | - Bijal A. Balasubramanian
- University of Texas Southwestern Medical Center; Harold C. Simmons Comprehensive Cancer Center; Parkland Health and Hospital System; University of Texas School of Public Health, Dallas, TX; Kogod School of Business, American University, Washington, DC; Mercy Hospital, St Louis, MO; and Massachusetts General Hospital Cancer Center, Boston, MA
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Halm EA, Beaber EF, McLerran D, Chubak J, Corley DA, Rutter CM, Doubeni CA, Haas JS, Balasubramanian BA. Association Between Primary Care Visits and Colorectal Cancer Screening Outcomes in the Era of Population Health Outreach. J Gen Intern Med 2016; 31:1190-7. [PMID: 27279097 PMCID: PMC5023609 DOI: 10.1007/s11606-016-3760-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Revised: 04/06/2016] [Accepted: 05/24/2016] [Indexed: 12/19/2022]
Abstract
BACKGROUND Population outreach strategies are increasingly used to improve colorectal cancer (CRC) screening. The influence of primary care on cancer screening in this context is unknown. OBJECTIVE To assess associations between primary care provider (PCP) visits and receipt of CRC screening and colonoscopy after a positive fecal immunochemical (FIT) or fecal occult blood test (FOBT). DESIGN Population-based cohort study. PARTICIPANTS A total of 968,072 patients ages 50-74 years who were not up to date with CRC screening in 2011 in four integrated healthcare systems (three with screening outreach programs using FIT kits) in the Population-Based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium. MEASURES Demographic, clinical, PCP visit, and CRC screening data were obtained from electronic health records and administrative databases. We examined associations between PCP visits in 2011 and receipt of FIT/FOBT, screening colonoscopy, or flexible sigmoidoscopy (CRC screening) in 2012 and follow-up colonoscopy within 3 months of a positive FIT/FOBT in 2012. We used multivariable logistic regression and propensity score models to adjust for confounding. RESULTS Fifty-eight percent of eligible patients completed a CRC screening test in 2012, most by FIT. Those with a greater number of PCP visits had higher rates of CRC screening at all sites. Patients with ≥1 PCP visit had nearly twice the adjusted-odds of CRC screening (OR = 1.88, 95 % CI: 1.86-1.89). Overall, 79.6 % of patients with a positive FIT/FOBT completed colonoscopy within 3 months. Patients with ≥1 PCP visit had 30 % higher adjusted odds of completing colonoscopy after positive FIT/FOBT (OR = 1.30; 95 % CI: 1.22-1.40). CONCLUSIONS Patients with a greater number of PCP visits had higher rates of both incident CRC screening and colonoscopy after positive FIT/FOBT, even in health systems with active population health outreach programs. In this era of virtual care and population outreach, primary care visits remain an important mechanism for engaging patients in cancer screening.
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Affiliation(s)
- Ethan A Halm
- Departments of Internal Medicine and Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Elisabeth F Beaber
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Dale McLerran
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | | | - Chyke A Doubeni
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer S Haas
- Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas School of Public Health, Dallas, TX, USA
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Cohen DJ, Balasubramanian BA, Gordon L, Marino M, Ono S, Solberg LI, Crabtree BF, Stange KC, Davis M, Miller WL, Damschroder LJ, McConnell KJ, Creswell J. A national evaluation of a dissemination and implementation initiative to enhance primary care practice capacity and improve cardiovascular disease care: the ESCALATES study protocol. Implement Sci 2016; 11:86. [PMID: 27358078 PMCID: PMC4928346 DOI: 10.1186/s13012-016-0449-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Accepted: 06/08/2016] [Indexed: 12/15/2022] Open
Abstract
Background The Agency for Healthcare Research and Quality (AHRQ) launched the EvidenceNOW Initiative to rapidly disseminate and implement evidence-based cardiovascular disease (CVD) preventive care in smaller primary care practices. AHRQ funded eight grantees (seven regional Cooperatives and one independent national evaluation) to participate in EvidenceNOW. The national evaluation examines quality improvement efforts and outcomes for more than 1500 small primary care practices (restricted to those with fewer than ten physicians per clinic). Examples of external support include practice facilitation, expert consultation, performance feedback, and educational materials and activities. This paper describes the study protocol for the EvidenceNOW national evaluation, which is called Evaluating System Change to Advance Learning and Take Evidence to Scale (ESCALATES). Methods This prospective observational study will examine the portfolio of EvidenceNOW Cooperatives using both qualitative and quantitative data. Qualitative data include: online implementation diaries, observation and interviews at Cooperatives and practices, and systematic assessment of context from the perspective of Cooperative team members. Quantitative data include: practice-level performance on clinical quality measures (aspirin prescribing, blood pressure and cholesterol control, and smoking cessation; ABCS) collected by Cooperatives from electronic health records (EHRs); practice and practice member surveys to assess practice capacity and other organizational and structural characteristics; and systematic tracking of intervention delivery. Quantitative, qualitative, and mixed methods analyses will be conducted to examine how Cooperatives organize to provide external support to practices, to compare effectiveness of the dissemination and implementation approaches they implement, and to examine how regional variations and other organization and contextual factors influence implementation and effectiveness. Discussion ESCALATES is a national evaluation of an ambitious large-scale dissemination and implementation effort focused on transforming smaller primary care practices. Insights will help to inform the design of national health care practice extension systems aimed at supporting practice transformation efforts in the USA. Clinical Trial Registration NCT02560428 (09/21/15)
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Affiliation(s)
- Deborah J Cohen
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA. .,Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.
| | - Bijal A Balasubramanian
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas School of Public Health, Dallas Regional Campus, Dallas, TX, USA
| | - Leah Gordon
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA
| | - Miguel Marino
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA
| | - Sarah Ono
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA.,Department of Veteran Affairs, Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, USA
| | | | - Benjamin F Crabtree
- Department of Family Medicine and Community Health, Rutgers-Robert Wood, Johnson Medical School, New Brunswick, NJ, USA
| | - Kurt C Stange
- Departments of Family Medicine and Community Health, Epidemiology and Biostatistics, Sociology and the Case Comprehensive Cancer Center, and Clinical and Translational Science Collaborative, Case Western Reserve University, Cleveland, OH, USA
| | - Melinda Davis
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA.,Oregon, Rural Practice-Based Research Network, Portland, OR, USA
| | - William L Miller
- Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA, USA
| | - Laura J Damschroder
- Center for Clinical Management Research and PROVE QUERI, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - K John McConnell
- Center for Health Systems Effectiveness and Department of Emergency Medicine, Oregon Health and Science University, Portland, OR, USA
| | - John Creswell
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA
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Murphy CC, Tiro JA, Jean G, Balasubramanian BA, Higashi RT, Le B, Teng H, Alvarez CA. Abstract C59: Initiation of adjuvant hormonal therapy among uninsured stage I-III breast cancer patients treated in a safety-net healthcare system. Cancer Epidemiol Biomarkers Prev 2016. [DOI: 10.1158/1538-7755.disp15-c59] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
Background: Adjuvant hormonal therapy (AHT) significantly improves the overall and disease-free survival of breast cancer patients with hormone receptor-positive disease. Despite the benefits of AHT, many patients do not initiate or complete therapy as recommended. Further, adherence and patterns of AHT use in low-income and minority populations has not been well-studied. This study 1) estimated the prevalence of AHT initiation among breast cancer patients receiving care at a large safety-net healthcare system from 2008 to 2012; and 2) examined patient sociodemographic, tumor/treatment, and health history characteristics associated with AHT initiation.
Methods: Patients diagnosed with stages I-III hormone receptor-positive breast cancer were identified from an academic cancer registry at Dallas' Parkland Health and Hospital System (Parkland), one of the largest integrated safety-net healthcare systems in the U.S. We excluded patients who had a prior diagnosis of breast cancer, previously used AHT, did not receive definitive treatment and/or cancer-directed surgery at Parkland, or had commercial or Medicaid insurance. Uninsured residents of Dallas County are eligible for Parkland HEALTHplus, an income-based medical assistance program that covers prescriptions filled and dispensed by Parkland outpatient pharmacies. In addition, Parkland oncology and primary care clinics use the same, comprehensive electronic medical record (EMR). Thus, Parkland's payor and clinical informatics infrastructure provides a unique opportunity to examine initiation of AHT in uninsured, low-income, and minority populations. We extracted and linked pharmacy claims, cancer registry, and patient EMR data to determine the prevalence of AHT Initiation. Initiation was defined as a new AHT prescription within 18 months of the incident breast cancer diagnosis. Descriptive statistics were used to examine characteristics of the study population by AHT initiation, and log-binomial regression was used to identify correlates of initiation.
Results: We identified 291 breast cancer patients eligible for the study. Most patients were Hispanic (42.6%), not married (66.3%), and postmenopausal (63.9%). The mean age was 52.9 years. The majority (72.2%) of patients had one or more comorbid conditions, and the most prevalent comorbidities were hypertension (51.2%), hyperlipidemia (25.1%), and diabetes (20.3%). Overall, 239 (82%) patients initiated AHT within 18 months of diagnosis, and 52 (18%) did not initiate therapy. Among initiators, tamoxifen (42.3%) and anastrozole (55.2%) were the most commonly prescribed types of AHT. The mean retail price of tamoxifen and anastrozole was $126.80 and $472.20, respectively, with a mean copay of $4.90 for tamoxifen and $6.00 for anastrozole. In univariable analysis, patients who were Hispanic (RR 1.29, 95% CI 1.04—1.61) and other (RR 1.31, 95% CI 1.02—1.68) race/ethnicity, diagnosed in year 2008 (vs. 2012, RR 1.24, 95% CI 1.07—1.44), and received primary care at Parkland prior to diagnosis (RR 1.14, 95% CI 1.01—1.28) were more likely to initiate AHT. Current smokers (vs. never, RR 0.78, 95% CI 0.65—0.94) were less likely to initiate AHT. No variables remained statistically significant in the final multivariable model.
Conclusion: This study is an important first step in understanding AHT adherence behaviors in low-income and uninsured breast cancer patients. Our results suggest the majority of patients receiving care in a safety-net setting initiate AHT, and there are few differences in initiation by patient characteristics. Safety-net systems that provide access to AHT (e.g., through reduced prescription copays) may have a positive impact on disparities in AHT initiation rates among breast cancer patients. Future work is needed to determine if pharmacy benefits improve completion of the AHT regimen.
Citation Format: Caitlin C. Murphy, Jasmin A. Tiro, Gary Jean, Bijal A. Balasubramanian, Robin T. Higashi, Brian Le, Hugh Teng, Carlos A. Alvarez. Initiation of adjuvant hormonal therapy among uninsured stage I-III breast cancer patients treated in a safety-net healthcare system. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr C59.
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Affiliation(s)
| | - Jasmin A. Tiro
- 2The University of Texas Southwestern Medical Center, Dallas, TX,
| | - Gary Jean
- 3Texas Tech University Health Sciences Center, Dallas, TX,
| | | | - Robin T. Higashi
- 2The University of Texas Southwestern Medical Center, Dallas, TX,
| | - Brian Le
- 3Texas Tech University Health Sciences Center, Dallas, TX,
| | - Hugh Teng
- 3Texas Tech University Health Sciences Center, Dallas, TX,
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Balasubramanian BA, Jetelina KK, Lee SC. Oncologist and primary care physician attitudes and practices toward cancer survivor follow-up care in an integrated health system. J Clin Oncol 2016. [DOI: 10.1200/jco.2016.34.3_suppl.105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
105 Background: Previous research using nationally representative data showed significant differences between primary care physician (PCP) and oncologists’ attitudes and practices with respect to care of cancer survivors and called for more effective communication and coordination to improve care. This study compared PCP and oncologists’ attitudes and practices for follow-up cancer care within an integrated health system sharing a common electronic health record and clinical infrastructure to examine whether the integrated setting facilitated communication and coordination between PCPs and oncologists. Methods: 41 PCPs and 24 oncologists (response rate = 52%) affiliated with an integrated safety-net health system completed a validated survey. The survey assessed PCP and oncologists’ preferred models for delivering care, attitudes towards follow-up care, and cancer surveillance practices in this setting. Results: 41% of PCPs preferred an oncologist-led care delivery model as compared to 21% of oncologists. More PCPs than oncologists (73% vs 58%) agreed that PCPs have the skills necessary to initiate cancer surveillance. Yet, PCPs more often disagreed (56% vs 42% of oncologists) that they should have primary responsibility for providing cancer follow-up care. PCPs and oncologists differed significantly over cancer surveillance practices. Oncologists more consistently reported that PCPs ordered tests for cancer surveillance, evaluated patients for cancer recurrence and for adverse physical and psychological effects of cancer or its treatment, as well as managed pain and adverse outcomes of cancer treatment. PCPs, however, did not report equivalent ordering for these services. Conclusions: Even within an integrated health system, we found significant uncertainty as to who is responsible for care of cancer survivors. Oncologists more commonly assigned responsibility for cancer survivorship care to PCPs than PCPs recognized. This imbalance indicates many cancer survivors may not be receiving recommended care. Consensus guidelines are needed to delineate shared responsibilities for cancer survivors between primary care and oncology specialty care physicians.
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Affiliation(s)
| | | | - Simon Craddock Lee
- Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, TX
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Kendzor DE, Finley CE, Barlow CE, Whitehurst TA, Businelle MS, Balasubramanian BA, Radford NB, Shuval K. The association of fitness with reduced cardiometabolic risk among smokers. Am J Prev Med 2015; 48:561-9. [PMID: 25891055 DOI: 10.1016/j.amepre.2014.12.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Revised: 11/24/2014] [Accepted: 12/08/2014] [Indexed: 11/26/2022]
Abstract
INTRODUCTION Despite the health benefits associated with smoking cessation, continued smoking and relapse following cessation are common. Physical activity is associated with reduced risk of cardiovascular disease in general, though less is known about how cardiorespiratory fitness may influence cardiometabolic risk among smokers. Strategies are needed to protect against the health consequences of smoking among those unwilling or unable to quit smoking. The purpose of this study is to determine whether greater cardiorespiratory fitness is associated with reduced metabolic risk among smokers. METHODS The prospective influence of estimated cardiorespiratory fitness (i.e., maximal METs) on the development of metabolic syndrome and its components were examined among adult smokers (N=1,249) who completed at least two preventive medical visits at the Cooper Clinic (Dallas TX) between 1979 and 2011. Statistical analyses were completed in 2013 and 2014. RESULTS The rate and risk for metabolic syndrome, as well as abnormal fasting glucose and high-density lipoprotein cholesterol levels declined linearly with increases in cardiorespiratory fitness (all p<0.05). Smokers in the moderate and high fitness categories had significantly reduced risk of developing metabolic syndrome and elevated fasting glucose relative to smokers in the lowest fitness category. In addition, smokers in the high fitness category were less likely to develop abnormal high-density lipoprotein cholesterol levels. CONCLUSIONS Moderate to high cardiorespiratory fitness among smokers is associated with a reduced likelihood of developing certain cardiovascular disease risk factors and metabolic syndrome.
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Affiliation(s)
- Darla E Kendzor
- University of Texas Health Science Center, School of Public Health; University of Texas Southwestern Medical Center, Harold C. Simmons Cancer Center, Population Science and Cancer Control Program.
| | | | - Carolyn E Barlow
- University of Texas Health Science Center, School of Public Health; Cooper Institute
| | | | - Michael S Businelle
- University of Texas Health Science Center, School of Public Health; University of Texas Southwestern Medical Center, Harold C. Simmons Cancer Center, Population Science and Cancer Control Program
| | - Bijal A Balasubramanian
- University of Texas Health Science Center, School of Public Health; University of Texas Southwestern Medical Center, Harold C. Simmons Cancer Center, Population Science and Cancer Control Program
| | | | - Kerem Shuval
- Intramural Research Department, The American Cancer Society, Atlanta, Georgia
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