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Sykes M, Rosenberg-Yunger ZRS, Quigley M, Gupta L, Thomas O, Robinson L, Caulfield K, Ivers N, Alderson S. Exploring the content and delivery of feedback facilitation co-interventions: a systematic review. Implement Sci 2024; 19:37. [PMID: 38807219 PMCID: PMC11134935 DOI: 10.1186/s13012-024-01365-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 05/13/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Policymakers and researchers recommend supporting the capabilities of feedback recipients to increase the quality of care. There are different ways to support capabilities. We aimed to describe the content and delivery of feedback facilitation interventions delivered alongside audit and feedback within randomised controlled trials. METHODS We included papers describing feedback facilitation identified by the latest Cochrane review of audit and feedback. The piloted extraction proforma was based upon a framework to describe intervention content, with additional prompts relating to the identification of influences, selection of improvement actions and consideration of priorities and implications. We describe the content and delivery graphically, statistically and narratively. RESULTS We reviewed 146 papers describing 104 feedback facilitation interventions. Across included studies, feedback facilitation contained 26 different implementation strategies. There was a median of three implementation strategies per intervention and evidence that the number of strategies per intervention is increasing. Theory was used in 35 trials, although the precise role of theory was poorly described. Ten studies provided a logic model and six of these described their mechanisms of action. Both the exploration of influences and the selection of improvement actions were described in 46 of the feedback facilitation interventions; we describe who undertook this tailoring work. Exploring dose, there was large variation in duration (15-1800 min), frequency (1 to 42 times) and number of recipients per site (1 to 135). There were important gaps in reporting, but some evidence that reporting is improving over time. CONCLUSIONS Heterogeneity in the design of feedback facilitation needs to be considered when assessing the intervention's effectiveness. We describe explicit feedback facilitation choices for future intervention developers based upon choices made to date. We found the Expert Recommendations for Implementing Change to be valuable when describing intervention components, with the potential for some minor clarifications in terms and for greater specificity by intervention providers. Reporting demonstrated extensive gaps which hinder both replication and learning. Feedback facilitation providers are recommended to close reporting gaps that hinder replication. Future work should seek to address the 'opportunity' for improvement activity, defined as factors that lie outside the individual that make care or improvement behaviour possible. REVIEW REGISTRATION The study protocol was published at: https://www.protocols.io/private/4DA5DE33B68E11ED9EF70A58A9FEAC02 .
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Affiliation(s)
| | | | | | | | | | - Lisa Robinson
- Newcastle Upon Tyne NHS Foundation Trust, Newcastle Upon Tyne, UK
| | - Karen Caulfield
- Newcastle Upon Tyne NHS Foundation Trust, Newcastle Upon Tyne, UK
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Kasher Meron M, Eizenstein S, Cukierman-Yaffe T, Oieru D. Missed diagnosis-a major barrier to patient access to obesity healthcare in the primary care setting. Int J Obes (Lond) 2024:10.1038/s41366-024-01514-6. [PMID: 38649487 DOI: 10.1038/s41366-024-01514-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 04/25/2024]
Abstract
OBJECTIVE To investigate whether individuals with an elevated BMI measurement, for whom a diagnosis of overweight or obesity (OW/OB) is not recorded, are less likely to be offered clinical care for obesity compared to those with a recorded diagnosis. SUBJECTS A retrospective cohort study using the electronic medical record database of Maccabi Healthcare Services (MHS) in Israel. Included were 200,000 adults with BMI ≥ 25 kg/m2 measurement recorded during a primary care visit between 2014 and 2020, and no prior diagnosis of OW/OB or related co-morbidities. METHODS The relationships between a recorded diagnosis of OW/OB and two composite outcomes: 1. A composite of referrals to screening tests for metabolic complications; 2. A composite of weight loss intervention and follow up, were analyzed using multivariate logistic regression models. RESULTS In only 18% of individuals, a diagnosis of OW/OB was recorded. After adjusting for multiple potential confounding factors, individuals who received a recorded diagnosis were 18% more likely to be offered an evaluation for obesity-related metabolic complication, (OR 1.18, 95% CI 1.15-1.21, p < 0.001), and almost twice as likely to be offered intervention and follow up for their excess body weight (OR 1.84, 95% CI 1.76-1.94, p < 0.001) compared to individuals with missed diagnosis. These results persisted after adjusting for inter-physician variability. In addition, male sex, older age, and Arab sector were all associated with lower rates of weight loss intervention and follow up, while young individuals were less likely to be screened for metabolic complications. CONCLUSION Beyond BMI measurement, a recorded diagnosis of OW/OB is associated with statistically and clinically significant higher rates of performance of obesity care and intervention. Undiagnosed OW/OB presents a significant clinical opportunity, as recording a diagnosis of OW/OB would predict improved patient access to obesity healthcare and improved clinical outcomes.
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Affiliation(s)
- Michal Kasher Meron
- Meir Medical Center, Clalit Health Services, Kfar Saba, Israel.
- Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel.
| | - Sapir Eizenstein
- Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Tali Cukierman-Yaffe
- Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel
- Division of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Tel-HaShomer, Israel
| | - Dan Oieru
- Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel
- Maccabi Healthcare Services, Tel Aviv-Yafo, Israel
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Gupta A, Chouhdry H, Ellis SD, Young K, Mahnken J, Comfort B, Shanks D, McGreevy S, Rudy C, Zufer T, Mabry S, Woodward J, Wilson A, Anderson H, Loucks J, Chandaka S, Abu-El-Rub N, Mazzotti DR, Song X, Schmitz N, Conroy M, Supiano MA, Waitman LR, Burns JM. Design of a pragmatic randomized implementation effectiveness trial testing a health system wide hypertension program for older adults. Contemp Clin Trials 2024; 138:107466. [PMID: 38331381 DOI: 10.1016/j.cct.2024.107466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/22/2024] [Accepted: 02/05/2024] [Indexed: 02/10/2024]
Abstract
Hypertension control remains poor. Multiple barriers at the level of patients, providers, and health systems interfere with implementation of hypertension guidelines and effective lowering of BP. Some strategies such as self-measured blood pressure (SMBP) and remote management by pharmacists are safe and effectively lower BP but have not been effectively implemented. In this study, we combine such evidence-based strategies to build a remote hypertension program and test its effectiveness and implementation in large health systems. This randomized, controlled, pragmatic type I hybrid implementation effectiveness trial will examine the virtual collaborative care clinic (vCCC), a hypertension program that integrates automated patient identification, SMBP, remote BP monitoring by trained health system pharmacists, and frequent patient-provider communication. We will randomize 1000 patients with uncontrolled hypertension from two large health systems in a 1:1 ratio to either vCCC or control (usual care with education) groups for a 2-year intervention. Outcome measures including BP measurements, cognitive function, and a symptom checklist will be completed during study visits. Other outcome measures of cardiovascular events, mortality, and health care utilization will be assessed using Medicare data. For the primary outcome of proportion achieving BP control (defined as systolic BP < 130 mmHg) in the two groups, we will use a generalized linear mixed model analysis. Implementation outcomes include acceptability and feasibility of the program. This study will guide implementation of a hypertension program within large health systems to effectively lower BP.
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Affiliation(s)
- Aditi Gupta
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States; Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States.
| | - Hira Chouhdry
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Shellie D Ellis
- Department of Population Health, University of Kansas Medical Center, Kansas City, KS, United States
| | - Kate Young
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jonathan Mahnken
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Branden Comfort
- Division of General Internal Medicine, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Denton Shanks
- Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Sheila McGreevy
- Division of General Internal Medicine, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Courtney Rudy
- Division of General Internal Medicine, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Tahira Zufer
- Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Sharissa Mabry
- Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jennifer Woodward
- Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Amber Wilson
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Heidi Anderson
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jennifer Loucks
- Department of Pharmacy, University of Kansas Health System, Kansas City, KS, United States
| | - Sravani Chandaka
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Noor Abu-El-Rub
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Diego R Mazzotti
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States; Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Xing Song
- Department of Biomedical Informatics, Biostatistics, and Medical Epidemiology, University of Missouri, Columbia, MO, United States
| | - Nolan Schmitz
- Department of Pharmacy, University of Kansas Health System, Kansas City, KS, United States
| | - Molly Conroy
- Division of General Internal Medicine, Department of Internal Medicine, University of Utah Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Mark A Supiano
- Geriatrics Division, Department of Internal Medicine, University of Utah Spencer Fox Eccles School of Medicine and Center on Aging, University of Utah, Salt Lake City, UT, United States
| | - Lemuel R Waitman
- Department of Biomedical Informatics, Biostatistics, and Medical Epidemiology, University of Missouri, Columbia, MO, United States
| | - Jeffrey M Burns
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
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Haff N, Sreedhara SK, Wood W, Yom-Tov E, Horn DM, Hoover M, Low G, Lauffenburger JC, Chaitoff A, Russo M, Hanken K, Crum KL, Fontanet CP, Choudhry NK. Testing interventions to reduce clinical inertia in the treatment of hypertension: rationale and design of a pragmatic randomized controlled trial. Am Heart J 2024; 268:18-28. [PMID: 37967641 PMCID: PMC10843752 DOI: 10.1016/j.ahj.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 11/17/2023]
Abstract
BACKGROUND Clinical inertia, or failure to intensify treatment when indicated, leads to suboptimal blood pressure control. Interventions to overcome inertia and increase antihypertensive prescribing have been modestly successful in part because their effectiveness varies based on characteristics of the provider, the patient, or the provider-patient interaction. Understanding for whom each intervention is most effective could help target interventions and thus increase their impact. METHODS This three-arm, randomized trial tests the effectiveness of 2 interventions to reduce clinical inertia in hypertension prescribing compared to usual care. Forty five primary care providers (PCPs) caring for patients with hypertension in need of treatment intensification completed baseline surveys that assessed behavioral traits and were randomized to one of three arms: 1) Pharmacist e-consult, in which a clinical pharmacist provided patient-specific recommendations for hypertension medication management to PCPs in advance of upcoming visits, 2) Social norming dashboards that displayed PCP's hypertension control rates compared to those of their peers, or 3) Usual care (no intervention). The primary outcome was the rate of intensification of hypertension treatment. We will compare this outcome between study arms and then evaluate the association between characteristics of providers, patients, their clinical interactions, and intervention responsiveness. RESULTS Forty-five primary care providers were enrolled and randomized: 16 providers and 173 patients in the social norming dashboards arm, 15 providers and 143 patients in the pharmacist e-consult arm, and 14 providers and 150 patients in the usual care arm. On average, the mean patient age was 64 years, 47% were female, and 73% were white. Baseline demographic and clinical characteristics of patients were similar across arms, with the exception of more Hispanic patients in the usual care arm and fewest in the pharmacist e-consult arm. CONCLUSIONS This study can help identify interventions to reduce inertia in hypertension care and potentially identify the characteristics of patients, providers, or patient-provider interactions to understand for whom each intervention would be most beneficial. TRIAL REGISTRATION Clinicaltrials.gov (NCT, Registered: NCT04603560).
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Affiliation(s)
- Nancy Haff
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA.
| | - Sushama Kattinakere Sreedhara
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Wendy Wood
- Department of Psychology & Marshall School of Business, University of Southern California, Los Angeles, CA
| | | | - Daniel M Horn
- Department of Medicine, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Melissa Hoover
- Mass General Physicians Organization, Massachusetts General Hospital, Boston, MA
| | - Greg Low
- Mass General Physicians Organization, Massachusetts General Hospital, Boston, MA
| | - Julie C Lauffenburger
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Alexander Chaitoff
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Massimiliano Russo
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Kaitlin Hanken
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Katherine L Crum
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Constance P Fontanet
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Niteesh K Choudhry
- Center for Healthcare Delivery Sciences (C4HDS), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, MA
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Jain RK, Weiner M, Polley E, Iwamaye A, Huang E, Vokes T. Electronic Health Records (EHRs) Can Identify Patients at High Risk of Fracture but Require Substantial Race Adjustments to Currently Available Fracture Risk Calculators. J Gen Intern Med 2023; 38:3451-3459. [PMID: 37715097 PMCID: PMC10713897 DOI: 10.1007/s11606-023-08347-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 07/21/2023] [Indexed: 09/17/2023]
Abstract
BACKGROUND Osteoporotic fracture prediction calculators are poorly utilized in primary care, leading to underdiagnosis and undertreatment of those at risk for fracture. The use of these calculators could be improved if predictions were automated using the electronic health record (EHR). However, this approach is not well validated in multi-ethnic populations, and it is not clear if the adjustments for race or ethnicity made by calculators are appropriate. OBJECTIVE To investigate EHR-generated fracture predictions in a multi-ethnic population. DESIGN Retrospective cohort study using data from the EHR. SETTING An urban, academic medical center in Philadelphia, PA. PARTICIPANTS 12,758 White, 7,844 Black, and 3,587 Hispanic patients seeking routine care from 2010 to 2018 with mean 3.8 years follow-up. INTERVENTIONS None. MEASUREMENTS FRAX and QFracture, two of the most used fracture prediction tools, were studied. Risk for major osteoporotic fracture (MOF) and hip fracture were calculated using data from the EHR at baseline and compared to the number of fractures that occurred during follow-up. RESULTS MOF rates varied from 3.2 per 1000 patient-years in Black men to 7.6 in White women. FRAX and QFracture had similar discrimination for MOF prediction (area under the curve, AUC, 0.69 vs. 0.70, p=0.08) and for hip fracture prediction (AUC 0.77 vs 0.79, p=0.21) and were similar by race or ethnicity. FRAX had superior calibration than QFracture (calibration-in-the-large for FRAX 0.97 versus QFracture 2.02). The adjustment factors used in MOF prediction were generally accurate in Black women, but underestimated risk in Black men, Hispanic women, and Hispanic men. LIMITATIONS Single center design. CONCLUSIONS Fracture predictions using only EHR inputs can discriminate between high and low risk patients, even in Black and Hispanic patients, and could help primary care physicians identify patients who need screening or treatment. However, further refinements to the calculators may better adjust for race-ethnicity.
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Affiliation(s)
- Rajesh K Jain
- Department of Medicine, Section of Endocrinology, Diabetes, and Metabolism, The University of Chicago, 5841 South Maryland Ave, MC 1027, Chicago, IL, 60637, USA.
| | - Mark Weiner
- Weill Cornell Medicine, Clinical Population Health Sciences, New York, USA
| | - Eric Polley
- Department of Public Health Sciences, The University of Chicago, Chicago, USA
| | - Amy Iwamaye
- Section of Endocrinology, Diabetes, and Metabolism, Lewis Katz School of Medicine at Temple University, Philadelphia, USA
| | - Elbert Huang
- Department of Medicine and Department of Public Health Sciences, The University of Chicago, Chicago, USA
| | - Tamara Vokes
- Department of Medicine, Section of Endocrinology, Diabetes, and Metabolism, The University of Chicago, 5841 South Maryland Ave, MC 1027, Chicago, IL, 60637, USA
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Amin K, Bethel G, Jackson LR, Essien UR, Sloan CE. Eliminating Health Disparities in Atrial Fibrillation, Heart Failure, and Dyslipidemia: A Path Toward Achieving Pharmacoequity. Curr Atheroscler Rep 2023; 25:1113-1127. [PMID: 38108997 PMCID: PMC11044811 DOI: 10.1007/s11883-023-01180-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/25/2023] [Indexed: 12/19/2023]
Abstract
PURPOSE OF REVIEW Pharmacoequity refers to the goal of ensuring that all patients have access to high-quality medications, regardless of their race, ethnicity, gender, or other characteristics. The goal of this article is to review current evidence on disparities in access to cardiovascular drug therapies across sociodemographic subgroups, with a focus on heart failure, atrial fibrillation, and dyslipidemia. RECENT FINDINGS Considerable and consistent disparities to life-prolonging heart failure, atrial fibrillation, and dyslipidemia medications exist in clinical trial representation, access to specialist care, prescription of guideline-based therapy, drug affordability, and pharmacy accessibility across racial, ethnic, gender, and other sociodemographic subgroups. Researchers, health systems, and policy makers can take steps to improve pharmacoequity by diversifying clinical trial enrollment, increasing access to inpatient and outpatient cardiology care, nudging clinicians to increase prescription of guideline-directed medical therapy, and pursuing system-level reforms to improve drug access and affordability.
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Affiliation(s)
- Krunal Amin
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Garrett Bethel
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Larry R Jackson
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Utibe R Essien
- Department of Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
- Center for the Study of Healthcare Innovation, Implementation & Policy, Greater Los Angeles VA Healthcare System, Los Angeles, CA, USA
| | - Caroline E Sloan
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.
- Duke-Margolis Center for Health Policy, Duke University, Durham, NC, USA.
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Parikh RB, Schriver E, Ferrell WJ, Wakim J, Williamson J, Khan N, Kopinsky M, Balachandran M, Gabriel PE, Schuchter LM, Patel MS, Shulman LN, Manz CR. Remote Patient-Reported Outcomes and Activity Monitoring to Improve Patient-Clinician Communication Regarding Symptoms and Functional Status: A Randomized Controlled Trial. JCO Oncol Pract 2023; 19:1143-1151. [PMID: 37816198 PMCID: PMC10732505 DOI: 10.1200/op.23.00048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/08/2023] [Accepted: 08/29/2023] [Indexed: 10/12/2023] Open
Abstract
PURPOSE Routine collection of patient-generated health data (PGHD) may promote earlier recognition of symptomatic and functional decline. This trial assessed the impact of an intervention integrating remote PGHD collection with patient nudges on symptom and functional status understanding between patients with advanced cancer and their oncology team. METHODS This three-arm randomized controlled trial was conducted from November 19, 2020, to December 17, 2021, at a large tertiary oncology practice. We enrolled patients with stage IV GI and lung cancers undergoing chemotherapy. Over 6 months, patients in two intervention arms received PROStep-weekly text message-based symptom surveys and passive activity monitoring using a wearable accelerometer. PGHD were summarized in dashboards given to patients' oncology team before appointments. One intervention arm received an additional text-based active choice prompt to discuss worsening symptoms or functional status with their clinician. Control patients did not receive PROStep. The coprimary outcomes patient perceptions of oncology team symptom and functional understanding at 6 months were measured on a 1-5 Likert scale (5 = high understanding). RESULTS One hundred eight patients enrolled: 55% male, 81% White, and 77% had GI cancers. Patient-reported clinician understanding did not differ between control and intervention arms for symptoms (4.5 v 4.5; P = .87) or functional status (4.5 v 4.3; P = .31). In the intervention arms, combined patient adherence to weekly symptom reports and daily activity monitoring was 64% and 53%, respectively. Intervention patients in the PROStep versus PROStep + active choice arms reported low burden from wearing the accelerometer (mean burden [standard deviation], 2.7 [1.3] v 2.1 [1.3]; P = .15) and completing surveys (2.1 [1.2] v 1.9 [1.3]; P = .44). CONCLUSION Patients receiving PROStep reported high understanding of symptoms and functional status from their oncology team, although this did not differ from controls.
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Affiliation(s)
- Ravi B. Parikh
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
- Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
| | - Emily Schriver
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA
- Penn Medicine Predictive Healthcare, University of Pennsylvania Health System, Philadelphia, PA
| | - William J. Ferrell
- Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jonathan Wakim
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Joelle Williamson
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Neda Khan
- Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Center for Health Care Innovation, Penn Medicine, Philadelphia, PA
| | - Michael Kopinsky
- Center for Health Care Innovation, Penn Medicine, Philadelphia, PA
| | | | - Peter E. Gabriel
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Lynn M. Schuchter
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | | | | | - Christopher R. Manz
- Division of Population Sciences, Dana-Farber Cancer Institute, Boston, MA
- Harvard Medical School, Harvard University, Boston, MA
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McCormick C, Ahluwalia S, Segon A. Effect of a Performance Feedback Dashboard on Hospitalist Laboratory Test Utilization. Am J Med Qual 2023; 38:273-278. [PMID: 37908029 DOI: 10.1097/jmq.0000000000000150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
BACKGROUND Healthcare spending continues to be an area of improvement across all forms of medicine. Overtreatment or low-value care, including overutilization of laboratory testing, has an estimated annual cost of waste of $75.7-$101.2 billion annually. Providing performance feedback to hospitalists has been shown to be an effective way to encourage the practice of quality-improvement-focused medicine. There remains limited data regarding the implementation of performance feedback and direct results on hospital laboratory testing spending in the short term. OBJECTIVE The objective of this project was to identify whether performance-based feedback on laboratory utilization between both hospitalists and resident teams results in more conservative utilization of laboratory testing. DESIGN, SETTING, PARTICIPANTS This quality improvement project was conducted at a tertiary academic medical center, including both direct-care and house-staff teams. INTERVENTION OR EXPOSURE A weekly performance feedback report was generated and distributed to providers detailing laboratory test utilization by all hospitalists in a ranked system, normalized by the census of patients, for 3 months. MAIN OUTCOMES AND MEASURES The outcome measure was cumulative laboratory utilization during the intervention period compared to baseline utilization during the corresponding 3 months in the year prior and the weekly trend in laboratory utilization over 52 weeks. The aggregate laboratory utilization rate during intervention and control time periods was defined as the total number of laboratory tests ordered divided by the total number of patient encounters. Additionally, the cost difference was averaged per quarter and reported. The week-by-week trend in laboratory utilization was evaluated using a statistical process control (SPC) chart. RESULTS We found that following intervention during January-March 2020, the cumulative complete blood count utilization rate decreased from 5.54 to 4.83 per patient encounter and the basic metabolic panels/CMP utilization rate decreased from 6.65 to 6.11 per patient encounter compared with January-March 2019. This equated to cost savings of ~$42,700 in total for the quarter. Nonrandom variation was seen on SPC charts in weekly laboratory utilization rates for common laboratory tests during the intervention period. CONCLUSIONS We found that our intervention did result in a decrease in laboratory test utilization rates across direct-care and house-staff teams. This study lays promising groundwork for one tool that can be used to eliminate a source of hospital waste and improve the quality and efficiency of patient care.
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Affiliation(s)
| | | | - Ankur Segon
- Medicine, University of Texas Health Science Center, San Antonio, TX
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9
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Laur C, Ladak Z, Hall A, Solbak NM, Nathan N, Buzuayne S, Curran JA, Shelton RC, Ivers N. Sustainability, spread, and scale in trials using audit and feedback: a theory-informed, secondary analysis of a systematic review. Implement Sci 2023; 18:54. [PMID: 37885018 PMCID: PMC10604689 DOI: 10.1186/s13012-023-01312-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 10/05/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Audit and feedback (A&F) is a widely used implementation strategy to influence health professionals' behavior that is often tested in implementation trials. This study examines how A&F trials describe sustainability, spread, and scale. METHODS This is a theory-informed, descriptive, secondary analysis of an update of the Cochrane systematic review of A&F trials, including all trials published since 2011. Keyword searches related to sustainability, spread, and scale were conducted. Trials with at least one keyword, and those identified from a forward citation search, were extracted to examine how they described sustainability, spread, and scale. Results were qualitatively analyzed using the Integrated Sustainability Framework (ISF) and the Framework for Going to Full Scale (FGFS). RESULTS From the larger review, n = 161 studies met eligibility criteria. Seventy-eight percent (n = 126) of trials included at least one keyword on sustainability, and 49% (n = 62) of those studies (39% overall) frequently mentioned sustainability based on inclusion of relevant text in multiple sections of the paper. For spread/scale, 62% (n = 100) of trials included at least one relevant keyword and 51% (n = 51) of those studies (31% overall) frequently mentioned spread/scale. A total of n = 38 studies from the forward citation search were included in the qualitative analysis. Although many studies mentioned the need to consider sustainability, there was limited detail on how this was planned, implemented, or assessed. The most frequent sustainability period duration was 12 months. Qualitative results mapped to the ISF, but not all determinants were represented. Strong alignment was found with the FGFS for phases of scale-up and support systems (infrastructure), but not for adoption mechanisms. New spread/scale themes included (1) aligning affordability and scalability; (2) balancing fidelity and scalability; and (3) balancing effect size and scalability. CONCLUSION A&F trials should plan for sustainability, spread, and scale so that if the trial is effective, the benefits can continue. A deeper empirical understanding of the factors impacting A&F sustainability is needed. Scalability planning should go beyond cost and infrastructure to consider other adoption mechanisms, such as leadership, policy, and communication, that may support further scalability. TRIAL REGISTRATION Registered with Prospero in May 2022. CRD42022332606.
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Affiliation(s)
- Celia Laur
- Women's College Hospital Institute for Health System Solutions and Virtual Care, 76 Grenville Street, Toronto, ON, M5S 1B2, Canada.
- Institute of Health Policy, Management and Evaluation, Health Sciences Building, University of Toronto, 155 College Street, Suite 425, Toronto, ON, M5T 3M6, Canada.
| | - Zeenat Ladak
- Women's College Hospital Institute for Health System Solutions and Virtual Care, 76 Grenville Street, Toronto, ON, M5S 1B2, Canada
- Ontario Institute for Studies in Education, University of Toronto, 252 Bloor Street West, Toronto, ON, M5S 1V6, Canada
| | - Alix Hall
- School of Medicine and Public Health, The University of Newcastle, Newcastle, NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Newcastle, NSW, Australia
| | - Nathan M Solbak
- Physician Learning Program, Continuing Medical Education and Professional Development, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada
- Health Quality Programs, Queen's University, 92 Barrie Street, Kingston, ON, K7L 3N6, Canada
| | - Nicole Nathan
- School of Medicine and Public Health, The University of Newcastle, Newcastle, NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Newcastle, NSW, Australia
| | - Shewit Buzuayne
- Women's College Hospital Institute for Health System Solutions and Virtual Care, 76 Grenville Street, Toronto, ON, M5S 1B2, Canada
| | - Janet A Curran
- School of Nursing, Faculty of Health, Dalhousie University, Halifax, NS, B3H 4R2, Canada
| | - Rachel C Shelton
- Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Noah Ivers
- Women's College Hospital Institute for Health System Solutions and Virtual Care, 76 Grenville Street, Toronto, ON, M5S 1B2, Canada
- Institute of Health Policy, Management and Evaluation, Health Sciences Building, University of Toronto, 155 College Street, Suite 425, Toronto, ON, M5T 3M6, Canada
- Department of Family and Community Medicine, University of Toronto, 500 University Ave, Toronto, M5G 1V7, Canada
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10
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Jenssen BP, Schnoll R, Beidas RS, Bekelman J, Bauer AM, Evers-Casey S, Fisher T, Scott C, Nicoloso J, Gabriel P, Asch DA, Buttenheim AM, Chen J, Melo J, Grant D, Horst M, Oyer R, Shulman LN, Clifton AB, Lieberman A, Salam T, Rendle KA, Chaiyachati KH, Shelton RC, Fayanju O, Wileyto EP, Ware S, Blumenthal D, Ragusano D, Leone FT. Cluster Randomized Pragmatic Clinical Trial Testing Behavioral Economic Implementation Strategies to Improve Tobacco Treatment for Patients With Cancer Who Smoke. J Clin Oncol 2023; 41:4511-4521. [PMID: 37467454 PMCID: PMC10552951 DOI: 10.1200/jco.23.00355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/25/2023] [Accepted: 06/15/2023] [Indexed: 07/21/2023] Open
Abstract
PURPOSE Few cancer centers systematically engage patients with evidence-based tobacco treatment despite its positive effect on quality of life and survival. Implementation strategies directed at patients, clinicians, or both may increase tobacco use treatment (TUT) within oncology. METHODS We conducted a four-arm cluster-randomized pragmatic trial across 11 clinical sites comparing the effect of strategies informed by behavioral economics on TUT engagement during oncology encounters with cancer patients. We delivered electronic health record (EHR)-based nudges promoting TUT across four nudge conditions: patient only, clinician only, patient and clinician, or usual care. Nudges were designed to counteract cognitive biases that reduce TUT engagement. The primary outcome was TUT penetration, defined as the proportion of patients with documented TUT referral or a medication prescription in the EHR. Generalized estimating equations were used to estimate the parameters of a linear model. RESULTS From June 2021 to July 2022, we randomly assigned 246 clinicians in 95 clusters, and collected TUT penetration data from their encounters with 2,146 eligible patients who smoke receiving oncologic care. Intent-to-treat (ITT) analysis showed that the clinician nudge led to a significant increase in TUT penetration versus usual care (35.6% v 13.5%; OR = 3.64; 95% CI, 2.52 to 5.24; P < .0001). Completer-only analysis (N = 1,795) showed similar impact (37.7% clinician nudge v 13.5% usual care; OR = 3.77; 95% CI, 2.73 to 5.19; P < .0001). Clinician type affected TUT penetration, with physicians less likely to provide TUT than advanced practice providers (ITT OR = 0.67; 95% CI, 0.51 to 0.88; P = .004). CONCLUSION EHR nudges, informed by behavioral economics and aimed at oncology clinicians, appear to substantially increase TUT penetration. Adding patient nudges to the implementation strategy did not affect TUT penetration rates.
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Affiliation(s)
- Brian P. Jenssen
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Robert Schnoll
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Rinad S. Beidas
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Justin Bekelman
- Department of Radiation Oncology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Anna-Marika Bauer
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Sarah Evers-Casey
- Comprehensive Smoking Treatment Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Tierney Fisher
- Comprehensive Smoking Treatment Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Callie Scott
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jody Nicoloso
- Comprehensive Smoking Treatment Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Peter Gabriel
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - David A. Asch
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Alison M. Buttenheim
- Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia, PA
| | - Jessica Chen
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Julissa Melo
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Dwayne Grant
- Penn Medicine Lancaster General Health, Lancaster, PA
| | - Michael Horst
- Penn Medicine Lancaster General Health, Lancaster, PA
| | - Randall Oyer
- Penn Medicine Lancaster General Health, Lancaster, PA
| | - Lawrence N. Shulman
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Alicia B.W. Clifton
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Adina Lieberman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Tasnim Salam
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Katharine A. Rendle
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Krisda H. Chaiyachati
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Verily Life Sciences, San Francisco, CA
| | - Rachel C. Shelton
- Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY
| | - Oluwadamilola Fayanju
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - E. Paul Wileyto
- Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Sue Ware
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Daniel Blumenthal
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Daniel Ragusano
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Frank T. Leone
- Pulmonary, Allergy, & Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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11
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Ito Suffert SC, Motke BB, Linhares AB, Vargens AF, Alano TS, Lutz AT, Boff Borges R, Bica CG, Vargas Alves RJ. Evaluation of Direct Medical Costs and Associated Factors Within the Last 30 days of Life of Hospitalized Cancer Patients. Am J Hosp Palliat Care 2023; 40:1098-1105. [PMID: 36564870 DOI: 10.1177/10499091221147906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Background: An estimated 9.6 million people died from cancer globally in 2018, which is a reflection of the quality of patients' end-of-life care and its costs. Aim: To estimate direct medical costs of the last 30 days of oncology patients admitted to an inpatient clinic and to evaluate factors associated with medical costs at the end of life. Design: Cost-of-illness study with data from a retrospective cohort. Setting/Participants: We included patients aged 18 and older who were diagnosed with incurable cancer and who were admitted to a tertiary hospital in Brazil between January 1, 2018 and December 31, 2019. Results: Our sample included 109 patients with an average age of 69 (61‒76). The median overall survival was 4.3 (.9‒12.9) months. The median cost per patient per day related to hospitalization was BRL 119 (73‒181)/United States dollars [USD] 21 (13‒33). The cost of medication was BRL 66 (40‒105)/USD 12 (7‒19), representing 55.46% of costs while that of materials and supplies was BRL 30 (18‒49)/USD 5 (3‒9). In the multivariate analysis, when the limitation of interventions was recorded in the medical record, the median cost is reduced by BRL 50 (USD 9) per patient per day. Conclusions: The median cost per patient per day was BRL 119 (73‒181). The recording of limitations of therapeutic interventions in the medical record was a predictor variable that influenced the final medical cost of patients, suggesting that medical practice and decision-making in end-of-life care impact costs.
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Affiliation(s)
- Soraya C Ito Suffert
- Programa de Pós Graduação em Patologia, Universidade Federal de Ciências da Saúde de Porto Alegre-UFCSPA, Porto Alegre, Brasil
| | - Bruna B Motke
- Hospital Santa Rita, Irmandade da Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, Brasil
| | - Armani B Linhares
- Undergraduate Program in Medicine. Universidade Federal de Ciências da Saúde de Porto Alegre-UFCSPA, Porto Alegre, Brasil
| | - André F Vargens
- Undergraduate Program in Medicine. Universidade Federal de Ciências da Saúde de Porto Alegre-UFCSPA, Porto Alegre, Brasil
| | - Tainá S Alano
- Undergraduate Program in Medicine. Universidade Federal de Ciências da Saúde de Porto Alegre-UFCSPA, Porto Alegre, Brasil
| | - Andreas T Lutz
- Hospital Santa Rita, Irmandade da Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, Brasil
| | - Rogério Boff Borges
- Unidade de Bioestatística, Diretoria de Pesquisa, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Claudia G Bica
- Programa de Pós Graduação em Patologia, Universidade Federal de Ciências da Saúde de Porto Alegre-UFCSPA, Porto Alegre, Brasil
| | - Rafael José Vargas Alves
- Hospital Santa Rita, Irmandade da Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, Brasil
- Departamento de Clínica Médica, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Brasil
- National Institute for Health Technology Assessment-IATS/CNPq, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil
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12
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Sreepada RS, Chang AC, West NC, Sujan J, Lai B, Poznikoff AK, Munk R, Froese NR, Chen JC, Görges M. Dashboard of Short-Term Postoperative Patient Outcomes for Anesthesiologists: Development and Preliminary Evaluation. JMIR Perioper Med 2023; 6:e47398. [PMID: 37725426 PMCID: PMC10548316 DOI: 10.2196/47398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 08/08/2023] [Accepted: 08/16/2023] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Anesthesiologists require an understanding of their patients' outcomes to evaluate their performance and improve their practice. Traditionally, anesthesiologists had limited information about their surgical outpatients' outcomes due to minimal contact post discharge. Leveraging digital health innovations for analyzing personal and population outcomes may improve perioperative care. BC Children's Hospital's postoperative follow-up registry for outpatient surgeries collects short-term outcomes such as pain, nausea, and vomiting. Yet, these data were previously not available to anesthesiologists. OBJECTIVE This quality improvement study aimed to visualize postoperative outcome data to allow anesthesiologists to reflect on their care and compare their performance with their peers. METHODS The postoperative follow-up registry contains nurse-reported postoperative outcomes, including opioid and antiemetic administration in the postanesthetic care unit (PACU), and family-reported outcomes, including pain, nausea, and vomiting, within 24 hours post discharge. Dashboards were iteratively co-designed with 5 anesthesiologists, and a department-wide usability survey gathered anesthesiologists' feedback on the dashboards, allowing further design improvements. A final dashboard version has been deployed, with data updated weekly. RESULTS The dashboard contains three sections: (1) 24-hour outcomes, (2) PACU outcomes, and (3) a practice profile containing individual anesthesiologist's case mix, grouped by age groups, sex, and surgical service. At the time of evaluation, the dashboard included 24-hour data from 7877 cases collected from September 2020 to February 2023 and PACU data from 8716 cases collected from April 2021 to February 2023. The co-design process and usability evaluation indicated that anesthesiologists preferred simpler designs for data summaries but also required the ability to explore details of specific outcomes and cases if needed. Anesthesiologists considered security and confidentiality to be key features of the design and most deemed the dashboard information useful and potentially beneficial for their practice. CONCLUSIONS We designed and deployed a dynamic, personalized dashboard for anesthesiologists to review their outpatients' short-term postoperative outcomes. This dashboard facilitates personal reflection on individual practice in the context of peer and departmental performance and, hence, the opportunity to evaluate iterative practice changes. Further work is required to establish their effect on improving individual and department performance and patient outcomes.
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Affiliation(s)
- Rama Syamala Sreepada
- Department of Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia, Vancouver, BC, Canada
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
| | - Ai Ching Chang
- Department of Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia, Vancouver, BC, Canada
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
| | - Nicholas C West
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
| | - Jonath Sujan
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
| | - Brendan Lai
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
| | - Andrew K Poznikoff
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
- Department of Anesthesia, BC Children's Hospital, Vancouver, BC, Canada
| | - Rebecca Munk
- Department of Anesthesiology, Kelowna General Hospital, Kelowna, BC, Canada
| | - Norbert R Froese
- Department of Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia, Vancouver, BC, Canada
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
- Department of Anesthesia, BC Children's Hospital, Vancouver, BC, Canada
| | - James C Chen
- Department of Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesia, BC Children's Hospital, Vancouver, BC, Canada
| | - Matthias Görges
- Department of Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia, Vancouver, BC, Canada
- Research Institute, BC Children's Hospital, Vancouver, BC, Canada
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13
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Ose D, Adediran E, Owens R, Gardner E, Mervis M, Turner C, Carlson E, Forbes D, Jasumback CL, Stuligross J, Pohl S, Kiraly B. Electronic Health Record-Driven Approaches in Primary Care to Strengthen Hypertension Management Among Racial and Ethnic Minoritized Groups in the United States: Systematic Review. J Med Internet Res 2023; 25:e42409. [PMID: 37713256 PMCID: PMC10541643 DOI: 10.2196/42409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 06/01/2023] [Accepted: 07/04/2023] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND Managing hypertension in racial and ethnic minoritized groups (eg, African American/Black patients) in primary care is highly relevant. However, evidence on whether or how electronic health record (EHR)-driven approaches in primary care can help improve hypertension management for patients of racial and ethnic minoritized groups in the United States remains scarce. OBJECTIVE This review aims to examine the role of the EHR in supporting interventions in primary care to strengthen the hypertension management of racial and ethnic minoritized groups in the United States. METHODS A search strategy based on the PICO (Population, Intervention, Comparison, and Outcome) guidelines was utilized to query and identify peer-reviewed articles on the Web of Science and PubMed databases. The search strategy was based on terms related to racial and ethnic minoritized groups, hypertension, primary care, and EHR-driven interventions. Articles were excluded if the focus was not hypertension management in racial and ethnic minoritized groups or if there was no mention of health record data utilization. RESULTS A total of 29 articles were included in this review. Regarding populations, Black/African American patients represented the largest population (26/29, 90%) followed by Hispanic/Latino (18/29, 62%), Asian American (7/29, 24%), and American Indian/Alaskan Native (2/29, 7%) patients. No study included patients who identified as Native Hawaiian/Pacific Islander. The EHR was used to identify patients (25/29, 86%), drive the intervention (21/29, 72%), and monitor results and outcomes (7/29, 59%). Most often, EHR-driven approaches were used for health coaching interventions, disease management programs, clinical decision support (CDS) systems, and best practice alerts (BPAs). Regarding outcomes, out of 8 EHR-driven health coaching interventions, only 3 (38%) reported significant results. In contrast, all the included studies related to CDS and BPA applications reported some significant results with respect to improving hypertension management. CONCLUSIONS This review identified several use cases for the integration of the EHR in supporting primary care interventions to strengthen hypertension management in racial and ethnic minoritized patients in the United States. Some clinical-based interventions implementing CDS and BPA applications showed promising results. However, more research is needed on community-based interventions, particularly those focusing on patients who are Asian American, American Indian/Alaskan Native, and Native Hawaiian/Pacific Islander. The developed taxonomy comprising "identifying patients," "driving intervention," and "monitoring results" to classify EHR-driven approaches can be a helpful tool to facilitate this.
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Affiliation(s)
- Dominik Ose
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Emmanuel Adediran
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Robert Owens
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Elena Gardner
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Matthew Mervis
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Cindy Turner
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Emily Carlson
- Community Physicians Group, University of Utah, Salt Lake City, UT, United States
| | - Danielle Forbes
- Utah Department of Health and Human Services, Salt Lake City, UT, United States
| | | | - John Stuligross
- Utah Department of Health and Human Services, Salt Lake City, UT, United States
| | - Susan Pohl
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Bernadette Kiraly
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
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14
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Chatur S, Ezekowitz JA. Give a nudge a shot: NUDGE-FLU bridging the cardiovascular quality chasm. Eur J Heart Fail 2023; 25:1459-1463. [PMID: 37401529 DOI: 10.1002/ejhf.2959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 06/22/2023] [Indexed: 07/05/2023] Open
Affiliation(s)
- Safia Chatur
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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15
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Triebwasser JE, Lewey J, Walheim L, Sehdev HM, Srinivas SK. Electronic Reminder to Transition Care After Hypertensive Disorders of Pregnancy: A Randomized Controlled Trial. Obstet Gynecol 2023; 142:91-98. [PMID: 37294089 DOI: 10.1097/aog.0000000000005237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/20/2023] [Indexed: 06/10/2023]
Abstract
OBJECTIVE Scalable interventions are needed to improve preventive care for those with increased cardiovascular disease (CVD) risk identified during pregnancy. We hypothesized that an automated reminder message for clinicians (nudge) would increase counseling at the postpartum visit on patient transitions of care. METHODS We conducted a single-center, randomized controlled trial including birthing people with a hypertensive disorder of pregnancy evaluating a nudge compared with usual care. The nudge, including counseling phrases and patient-specific information on hypertensive diagnosis, was sent to the obstetric clinician through the electronic medical record up to 7 days before the postpartum visit. The primary outcome was documentation of counseling on transitions of care to primary care or cardiology. Secondary outcomes were documentation of CVD risk, use of counseling phrases, and preventive care visit within 6 months. A sample size of 94 per group (n=188) was planned to compare the nudge intervention with usual care; given the anticipated loss to follow-up, the sample size was increased to 222. Intention-to-treat analyses were performed, with P <.05 considered significant. RESULTS From February to June 2021, 392 patients were screened, and 222 were randomized and analyzed. Of these, 205 (92.3%) attended a postpartum visit. Groups were similar, but more women in the usual care group had diabetes (16.1% vs 6.7%, P =.03). After adjustment for diabetes, patients in the nudge group were more likely to have documented counseling on transitions of care (38.8% vs 26.2%, adjusted relative risk [aRR] 1.53, 95% CI 1.02-2.31), CVD risk (21.4% vs 8.4%, aRR 2.57, 95% CI 1.20-5.49), and use of aspirin in a future pregnancy (14.3% vs 1.9%, aRR 7.49, 95% CI 1.66-33.93). Counseling phrases were used more often in the nudge group (11.2% vs 0.9%, aRR 12.27, 95% CI 1.50-100.28). Preventive care visit attendance did not differ by group (22.1% vs 24.6%, aRR 0.91, 95% CI 0.57-1.47). CONCLUSION A timely electronic reminder to obstetric clinicians improved counseling about transitions of care after hypertensive disorders of pregnancy but did not result in increased preventive care visit attendance. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov , NCT04660032.
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Affiliation(s)
- Jourdan E Triebwasser
- Divisions of Maternal-Fetal Medicine and Cardiology, University of Pennsylvania Perelman School of Medicine, and the Department of Obstetrics & Gynecology, Pennsylvania Hospital, Philadelphia, Pennsylvania; and the Division of Maternal Fetal Medicine, University of Michigan, Ann Arbor, Michigan
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16
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McCleary N, Desveaux L, Presseau J, Reis C, Witteman HO, Taljaard M, Linklater S, Thavorn K, Dobell G, Mulhall CL, Lam JMC, Grimshaw JM, Ivers NM. Engagement is a necessary condition to test audit and feedback design features: results of a pragmatic, factorial, cluster-randomized trial with an embedded process evaluation. Implement Sci 2023; 18:13. [PMID: 37165413 PMCID: PMC10173488 DOI: 10.1186/s13012-023-01271-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 04/06/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND While audit & feedback (A&F) is an effective implementation intervention, the design elements which maximize effectiveness are unclear. Partnering with a healthcare quality advisory organization already delivering feedback, we conducted a pragmatic, 2 × 2 factorial, cluster-randomized trial to test the impact of variations in two factors: (A) the benchmark used for comparison and (B) information framing. An embedded process evaluation explored hypothesized mechanisms of effect. METHODS Eligible physicians worked in nursing homes in Ontario, Canada, and had voluntarily signed up to receive the report. Groups of nursing homes sharing physicians were randomized to (A) physicians' individual prescribing rates compared to top-performing peers (the top quartile) or the provincial median and (B) risk-framed information (reporting the number of patients prescribed high-risk medication) or benefit-framed information (reporting the number of patients not prescribed). We hypothesized that the top quartile comparator and risk-framing would lead to greater practice improvements. The primary outcome was the mean number of central nervous system-active medications per resident per month. Primary analyses compared the four arms at 6 months post-intervention. Factorial analyses were secondary. The process evaluation comprised a follow-up questionnaire and semi-structured interviews. RESULTS Two hundred sixty-seven physicians (152 clusters) were randomized: 67 to arm 1 (median benchmark, benefit framing), 65 to arm 2 (top quartile benchmark, benefit framing), 75 to arm 3 (median benchmark, risk framing), and 60 to arm 4 (top quartile benchmark, risk framing). There were no significant differences in the primary outcome across arms or for each factor. However, engagement was low (27-31% of physicians across arms downloaded the report). The process evaluation indicated that both factors minimally impacted the proposed mechanisms. However, risk-framed feedback was perceived as more actionable and more compatible with current workflows, whilst a higher target might encourage behaviour change when physicians identified with the comparator. CONCLUSIONS Risk framing and a top quartile comparator have the potential to achieve change. Further work to establish the strategies most likely to enhance A&F engagement, particularly with physicians who may be most likely to benefit from feedback, is required to support meaningfully addressing intricate research questions concerning the design of A&F. TRIAL REGISTRATION ClinicalTrials.gov, NCT02979964 . Registered 29 November 2016.
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Affiliation(s)
- Nicola McCleary
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada.
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
| | - Laura Desveaux
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
- Institute for Better Health, Trillium Health Partners, Mississauga, Canada
| | - Justin Presseau
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
- School of Psychology, University of Ottawa, Ottawa, Canada
| | - Catherine Reis
- Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, Canada
| | - Holly O Witteman
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada
- Department of Family and Emergency Medicine, Laval University, Québec City, Canada
| | - Monica Taljaard
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Stefanie Linklater
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada
| | - Kednapa Thavorn
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Gail Dobell
- Health System Performance, Ontario Health, Toronto, Canada
| | - Cara L Mulhall
- Health System Performance, Ontario Health, Toronto, Canada
| | | | - Jeremy M Grimshaw
- Centre for Implementation Research, Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Room L1202, Box 711, Ottawa, ON, K1H 8L6, Canada
- Department of Medicine, University of Ottawa, Ottawa, Canada
| | - Noah M Ivers
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
- Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, Canada
- Department of Family and Community Medicine, Women's College Hospital, Toronto, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
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Gupta A, Ellis SD, Burkhardt C, Young K, Mazzotti DR, Mahnken J, Abu-el-rub N, Chandaka S, Comfort B, Shanks D, Woodward J, Unrein A, Anderson H, Loucks J, Song X, Waitman LR, Burns JM. Implementing a home-based virtual hypertension programme-a pilot feasibility study. Fam Pract 2023; 40:414-422. [PMID: 35994031 PMCID: PMC10047620 DOI: 10.1093/fampra/cmac084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Implementing a health system-based hypertension programme may lower blood pressure (BP). METHODS We performed a randomized, controlled pilot study to assess feasibility, acceptability, and safety of a home-based virtual hypertension programme integrating evidence-based strategies to overcome current barriers to BP control. Trained clinical pharmacists staffed the virtual collaborative care clinic (vCCC) to remotely manage hypertension using a BP dashboard and phone "visits" to monitor BP, adherence, side effects of medications, and prescribe anti-hypertensives. Patients with uncontrolled hypertension were identified via electronic health records. Enrolled patients were randomized to either vCCC or usual care for 3 months. We assessed patients' home BP monitoring behaviour, and patients', physicians', and pharmacists' perspectives on feasibility and acceptability of individual programme components. RESULTS Thirty-one patients (vCCC = 17, usual care = 14) from six physician clinics completed the pilot study. After 3 months, average BP decreased in the vCCC arm (P = 0.01), but not in the control arm (P = 0.45). The vCCC participants measured BP more (9.9 vs. 1.2 per week, P < 0.001). There were no intervention-related adverse events. Participating physicians (n = 6), pharmacists (n = 5), and patients (n = 31) rated all programme components with average scores of >4.0, a pre-specified benchmark. Nine adaptations in vCCC design and delivery were made based on potential barriers to implementing the programme and suggestions. CONCLUSION A home-based virtual hypertension programme using team-based care, technology, and a logical integration of evidence-based strategies is safe, acceptable, and feasible to intended users. These pilot data support studies to assess the effectiveness of this programme at a larger scale.
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Affiliation(s)
- Aditi Gupta
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
- KU Alzheimer’s Disease Research Center, Kansas City, KS, United States
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Shellie D Ellis
- Department of Population Health, University of Kansas Medical Center, Kansas City, KS, United States
| | - Crystal Burkhardt
- Department of Pharmacy, University of Kansas, Lawrence, KS, United States
| | - Kate Young
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Diego R Mazzotti
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jonathan Mahnken
- KU Alzheimer’s Disease Research Center, Kansas City, KS, United States
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Noor Abu-el-rub
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Sravani Chandaka
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Branden Comfort
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Denton Shanks
- Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jennifer Woodward
- Department of Family Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Amber Unrein
- KU Alzheimer’s Disease Research Center, Kansas City, KS, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Heidi Anderson
- KU Alzheimer’s Disease Research Center, Kansas City, KS, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jennifer Loucks
- Department of Pharmacy, University of Kansas Health System, Kansas City, KS, United States
| | - Xing Song
- Health Management and Informatics, University of Missouri, Columbia, MO, United States
| | - Lemuel R Waitman
- Health Management and Informatics, University of Missouri, Columbia, MO, United States
| | - Jeffrey M Burns
- KU Alzheimer’s Disease Research Center, Kansas City, KS, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
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18
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Manz CR, Zhang Y, Chen K, Long Q, Small DS, Evans CN, Chivers C, Regli SH, Hanson CW, Bekelman JE, Braun J, Rareshide CAL, O'Connor N, Kumar P, Schuchter LM, Shulman LN, Patel MS, Parikh RB. Long-term Effect of Machine Learning-Triggered Behavioral Nudges on Serious Illness Conversations and End-of-Life Outcomes Among Patients With Cancer: A Randomized Clinical Trial. JAMA Oncol 2023; 9:414-418. [PMID: 36633868 PMCID: PMC9857721 DOI: 10.1001/jamaoncol.2022.6303] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Importance Serious illness conversations (SICs) between oncology clinicians and patients are associated with improved quality of life and may reduce aggressive end-of-life care. However, most patients with cancer die without a documented SIC. Objective To test the impact of behavioral nudges to clinicians to prompt SICs on the SIC rate and end-of-life outcomes among patients at high risk of death within 180 days (high-risk patients) as identified by a machine learning algorithm. Design, Setting, and Participants This prespecified 40-week analysis of a stepped-wedge randomized clinical trial conducted between June 17, 2019, and April 20, 2020 (including 16 weeks of intervention rollout and 24 weeks of follow-up), included 20 506 patients with cancer representing 41 021 encounters at 9 tertiary or community-based medical oncology clinics in a large academic health system. The current analyses were conducted from June 1, 2021, to May 31, 2022. Intervention High-risk patients were identified using a validated electronic health record machine learning algorithm to predict 6-month mortality. The intervention consisted of (1) weekly emails to clinicians comparing their SIC rates for all patients against peers' rates, (2) weekly lists of high-risk patients, and (3) opt-out text messages to prompt SICs before encounters with high-risk patients. Main Outcomes and Measures The primary outcome was SIC rates for all and high-risk patient encounters; secondary end-of-life outcomes among decedents included inpatient death, hospice enrollment and length of stay, and intensive care unit admission and systemic therapy close to death. Intention-to-treat analyses were adjusted for clinic and wedge fixed effects and clustered at the oncologist level. Results The study included 20 506 patients (mean [SD] age, 60.0 [14.0] years) and 41 021 patient encounters: 22 259 (54%) encounters with female patients, 28 907 (70.5%) with non-Hispanic White patients, and 5520 (13.5%) with high-risk patients; 1417 patients (6.9%) died by the end of follow-up. There were no meaningful differences in demographic characteristics in the control and intervention periods. Among high-risk patient encounters, the unadjusted SIC rates were 3.4% (59 of 1754 encounters) in the control period and 13.5% (510 of 3765 encounters) in the intervention period. In adjusted analyses, the intervention was associated with increased SICs for all patients (adjusted odds ratio, 2.09 [95% CI, 1.53-2.87]; P < .001) and decreased end-of-life systemic therapy (7.5% [72 of 957 patients] vs 10.4% [24 of 231 patients]; adjusted odds ratio, 0.25 [95% CI, 0.11-0.57]; P = .001) relative to controls, but there was no effect on hospice enrollment or length of stay, inpatient death, or end-of-life ICU use. Conclusions and Relevance In this randomized clinical trial, a machine learning-based behavioral intervention and behavioral nudges to clinicans led to an increase in SICs and reduction in end-of-life systemic therapy but no changes in other end-of-life outcomes among outpatients with cancer. These results suggest that machine learning and behavioral nudges can lead to long-lasting improvements in cancer care delivery. Trial Registration ClinicalTrials.gov Identifier: NCT03984773.
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Affiliation(s)
- Christopher R Manz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Yichen Zhang
- Division of Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Kan Chen
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Qi Long
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Dylan S Small
- Wharton School of the University of Pennsylvania, Philadelphia
| | - Chalanda N Evans
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | | | | | - Justin E Bekelman
- Division of Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | | | - Charles A L Rareshide
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Nina O'Connor
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Pallavi Kumar
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Lynn M Schuchter
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | - Lawrence N Shulman
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | | | - Ravi B Parikh
- Division of Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
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19
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Provider perspectives on clinical decision support to improve HIV prevention in pediatric primary care: a multiple methods study. Implement Sci Commun 2023; 4:18. [PMID: 36810099 PMCID: PMC9945664 DOI: 10.1186/s43058-023-00394-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/25/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Clinical decision support (CDS) is a promising intervention for improving uptake of HIV testing and pre-exposure prophylaxis (PrEP). However, little is known regarding provider perspectives on acceptability, appropriateness, and feasibility of CDS for HIV prevention in pediatric primary care, a key implementation setting. METHODS This was a cross-sectional multiple methods study utilizing surveys and in-depth interviews with pediatricians to assess acceptability, appropriateness, and feasibility of CDS for HIV prevention, as well as to identify contextual barriers and facilitators to CDS. Qualitative analysis utilized work domain analysis and a deductive coding approach grounded in the Consolidated Framework of Implementation Research. Quantitative and qualitative data were merged to develop an Implementation Research Logic Model to conceptualize implementation determinants, strategies, mechanisms, and outcomes of potential CDS use. RESULTS Participants (n = 26) were primarily white (92%), female (88%), and physicians (73%). Using CDS to improve HIV testing and PrEP delivery was perceived as highly acceptable (median score 5), IQR [4-5]), appropriate (5, IQR [4-5]), and feasible (4, IQR [3.75-4.75]) using a 5-point Likert scale. Providers identified confidentiality and time constraints as two key barriers to HIV prevention care spanning every workflow step. With respect to desired CDS features, providers sought interventions that were integrated into the primary care workflow, standardized to promote universal testing yet adaptable to the level of a patient's HIV risk, and addressed providers' knowledge gaps and bolstered self-efficacy in providing HIV prevention services. CONCLUSIONS This multiple methods study indicates that clinical decision support in the pediatric primary care setting may be an acceptable, feasible, and appropriate intervention for improving the reach and equitable delivery of HIV screening and PrEP services. Design considerations for CDS in this setting should include deploying CDS interventions early in the visit workflow and prioritizing standardized but flexible designs.
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Adusumalli S, Kanter GP, Small DS, Asch DA, Volpp KG, Park SH, Gitelman Y, Do D, Leri D, Rhodes C, VanZandbergen C, Howell JT, Epps M, Cavella AM, Wenger M, Harrington TO, Clark K, Westover JE, Snider CK, Patel MS. Effect of Nudges to Clinicians, Patients, or Both to Increase Statin Prescribing: A Cluster Randomized Clinical Trial. JAMA Cardiol 2023; 8:23-30. [PMID: 36449275 PMCID: PMC9713674 DOI: 10.1001/jamacardio.2022.4373] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 09/29/2022] [Indexed: 12/02/2022]
Abstract
Importance Statins reduce the risk of major adverse cardiovascular events, but less than one-half of individuals in America who meet guideline criteria for a statin are actively prescribed this medication. Objective To evaluate whether nudges to clinicians, patients, or both increase initiation of statin prescribing during primary care visits. Design, Setting, and Participants This cluster randomized clinical trial evaluated statin prescribing of 158 clinicians from 28 primary care practices including 4131 patients. The design included a 12-month preintervention period and a 6-month intervention period between October 19, 2019, and April 18, 2021. Interventions The usual care group received no interventions. The clinician nudge combined an active choice prompt in the electronic health record during the patient visit and monthly feedback on prescribing patterns compared with peers. The patient nudge was an interactive text message delivered 4 days before the visit. The combined nudge included the clinician and patient nudges. Main Outcomes and Measures The primary outcome was initiation of a statin prescription during the visit. Results The sample comprised 4131 patients with a mean (SD) age of 65.5 (10.5) years; 2120 (51.3%) were male; 1210 (29.3%) were Black, 106 (2.6%) were Hispanic, 2732 (66.1%) were White, and 83 (2.0%) were of other race or ethnicity, and 933 (22.6%) had atherosclerotic cardiovascular disease. In unadjusted analyses during the preintervention period, statins were prescribed to 5.6% of patients (105 of 1876) in the usual care group, 4.8% (97 of 2022) in the patient nudge group, 6.0% (104 of 1723) in the clinician nudge group, and 4.7% (82 of 1752) in the combined group. During the intervention, statins were prescribed to 7.3% of patients (75 of 1032) in the usual care group, 8.5% (100 of 1181) in the patient nudge group, 13.0% (128 of 981) in the clinician nudge arm, and 15.5% (145 of 937) in the combined group. In the main adjusted analyses relative to usual care, the clinician nudge significantly increased statin prescribing alone (5.5 percentage points; 95% CI, 3.4 to 7.8 percentage points; P = .01) and when combined with the patient nudge (7.2 percentage points; 95% CI, 5.1 to 9.1 percentage points; P = .001). The patient nudge alone did not change statin prescribing relative to usual care (0.9 percentage points; 95% CI, -0.8 to 2.5 percentage points; P = .32). Conclusions and Relevance Nudges to clinicians with and without a patient nudge significantly increased initiation of a statin prescription during primary care visits. The patient nudge alone was not effective. Trial Registration ClinicalTrials.gov Identifier: NCT04307472.
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Affiliation(s)
| | | | - Dylan S. Small
- Wharton School, University of Pennsylvania, Philadelphia
| | - David A. Asch
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Wharton School, University of Pennsylvania, Philadelphia
| | - Kevin G. Volpp
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Wharton School, University of Pennsylvania, Philadelphia
- Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Sae-Hwan Park
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Yevgeniy Gitelman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - David Do
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Damien Leri
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Corinne Rhodes
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | - John T. Howell
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Mika Epps
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Ann M. Cavella
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Michael Wenger
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | - Kayla Clark
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
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Racicot M, Cardinal AM, Tremblay D, Vaillancourt JP. Technologies monitoring and improving biosecurity compliance in barn anterooms. Front Vet Sci 2022; 9:1005144. [PMID: 36406088 PMCID: PMC9673170 DOI: 10.3389/fvets.2022.1005144] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/14/2022] [Indexed: 10/29/2023] Open
Abstract
People can act as mechanical vectors, and introduce and spread infectious diseases on farms. Preventive measures, such as changing boots and washing hands, need systematic implementation to manage this risk. Unfortunately, biosecurity compliance regarding biosecurity measures in barn anterooms has been shown to be generally low in all animal production systems. Indeed, the main challenge with biosecurity is maintaining compliance. The development of an effective on-farm biosecurity program requires several elements. These include farm and barn designs facilitating implementation of biosecurity measures; consistently communicating with all personnel and visitors informing them about threats and biosecurity; training programs for all farm personnel, explaining why biosecurity is effective in preventing infectious disease transmission, which measures are needed, and how to best implement them. All these components would be further optimized if automated monitoring systems were implemented with feedback mechanisms. Technologies are now available and are being adapted to the farm context to monitor biosecurity compliance. Two pilot projects using radio-frequency-identification-based (RFID) real-time continuous automated monitoring system quantifying hand sanitizing and boot compliance were conducted. The first one (MediHand Trace system) was a system designed to monitor and provide real-time feedback for handwashing in a hospital environment. It was functional for this task, although not sturdy enough for long-term use in a farm environment. The second system was a prototype designed for barns and with foot mats allowing the monitoring of footwear management as well as handwashing. These pilot studies have shown that real-time feedback helps improve compliance. However, the efficacy of the systems was very dependent on the physical set-up of the anteroom.
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Affiliation(s)
- Manon Racicot
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Montreal, QC, Canada
| | - Anne-Marie Cardinal
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Montreal, QC, Canada
| | - Dominic Tremblay
- Institut de technologie Agroalimentaire du Québec, Programme de technologie des productions animales, St-Hyacinthe, QC, Canada
| | - Jean-Pierre Vaillancourt
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Montreal, QC, Canada
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Vandenplas Y, Simoens S, Turk F, Vulto AG, Huys I. Applications of Behavioral Economics to Pharmaceutical Policymaking: A Scoping Review with Implications for Best-Value Biological Medicines. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2022; 20:803-817. [PMID: 35972683 PMCID: PMC9379236 DOI: 10.1007/s40258-022-00751-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND AND OBJECTIVE Pharmaceutical policies are generally based on the assumption that involved stakeholders make rational decisions. However, behavioral economics has taught us that this is not always the case as people deviate from rational behavior in rather predictable patterns. This scoping review examined to what extent behavioral concepts have already been applied in the pharmaceutical domain and what evidence exists about their effectiveness, with the aim of formulating future applications and research hypotheses on policymaking for best-value biologicals. METHODS A scoping literature review was conducted on the evidence of behavioral applications to pharmaceuticals. Scientific databases (Embase, MEDLINE, APA PsycArticles, and Scopus) were searched up to 20 October, 2021. RESULTS Forty-four full-text scientific articles were identified and narratively described in this article. Pharmaceutical domains where behavioral concepts have been investigated relate to influencing prescribing behavior, improving medication adherence, and increasing vaccination uptake. Multiple behavioral concepts were examined in the identified studies, such as social norms, defaults, framing, loss aversion, availability, and present bias. The effectiveness of the applied interventions was generally positive, but depended on the context. Some of the examined interventions can easily be translated into effective policy interventions for best-value biological medicines. However, some applications require further investigation in a research context. CONCLUSIONS Applications of behavioral economics to pharmaceutical policymaking are promising. However, further research is required to investigate the effect of behavioral applications on policy interventions for a more sustainable market environment for best-value biological medicines.
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Affiliation(s)
- Yannick Vandenplas
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
| | - Steven Simoens
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | | | - Arnold G Vulto
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
- Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Isabelle Huys
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
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23
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Wolf A, Sant'Anna A, Vilhelmsson A. Using nudges to promote clinical decision making of healthcare professionals: A scoping review. Prev Med 2022; 164:107320. [PMID: 36283484 DOI: 10.1016/j.ypmed.2022.107320] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/25/2022] [Accepted: 10/18/2022] [Indexed: 10/31/2022]
Abstract
Nudging has been discussed in the context of policy and public health, but not so much within healthcare. This scoping review aimed to assess the empirical evidence on how nudging techniques can be used to affect the behavior of healthcare professionals (HCPs) in clinical settings. A systematic database search was conducted for the period January 2010-December 2020 using the PRISMA extension for Scoping Review checklist. Two reviewers independently screened each article for inclusion. Included articles were reviewed to extract key information about each intervention, including purpose, target behavior, measured outcomes, key findings, nudging strategies, intervention objectives and their theoretical underpinnings. Two independent dimensions, building on Kahneman's System 1 and System 2, were used to describe nudging strategies according to user action and timing of their implementation. Of the included 51 articles, 40 reported statistically significant results, six were not significant and two reported mixed results. Thirteen different nudging strategies were identified aimed at modifying four types of HPCs' behavior: prescriptions and orders, procedure, hand hygiene, and vaccination. The most common nudging strategy employed were defaults or pre-orders, followed by alerts or reminders, and active choice. Many interventions did not require any deliberate action from users, here termed passive interventions, such as automatically changing prescriptions to their generic equivalent unless indicated by the user. Passive nudges may be successful in changing the target outcome but may go unnoticed by the user. Future work should consider the broader ethical implications of passive nudges.
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Affiliation(s)
- Axel Wolf
- University of Gothenburg, Centre for Person-Centred Care (GPCC), Sweden; University of Gothenburg, Institute of Health and Care Sciences, Sahlgrenska Academy, Sweden
| | | | - Andreas Vilhelmsson
- Lund University, Department of Laboratory Medicine, Division of Occupational and Environmental Medicine, Sweden.
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Applying Behavioral Nudges in a Dietary Comparator for Surgical Trials: Developing the MediDiet. J Surg Res 2022; 279:540-547. [DOI: 10.1016/j.jss.2022.06.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 06/09/2022] [Accepted: 06/28/2022] [Indexed: 11/20/2022]
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Vock DM, Neprash HT, Hanson AV, Elert BA, Satin DJ, Rothman AJ, Short S, Karaca-Mandic P, Markowitz R, Melton GB, Golberstein E. PRescribing Interventions for Chronic pain using the Electronic health record (PRINCE): Study protocol. Contemp Clin Trials 2022; 121:106905. [PMID: 36057376 DOI: 10.1016/j.cct.2022.106905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 06/23/2022] [Accepted: 08/28/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Primary care is a frequent source of pain treatment and opioid prescribing. The objective of the Prescribing Interventions for Chronic Pain using the Electronic health record (PRINCE) study is to assess the effects of two behavioral economics-informed interventions embedded within the electronic health record (EHR) on guideline-concordant pain treatment and opioid prescribing decisions in primary care settings. METHODS Setting: The setting for this study is 43 primary care clinics in Minnesota. DESIGN The PRINCE study uses a cluster-randomized 2 × 2 factorial design to test the effects of two interventions. An adaptive design allows for the possibility of secondary randomization to test if interventions can be titrated while maintaining efficacy. INTERVENTIONS One intervention alters the "choice architecture" within the EHR to nudge clinicians toward non-opioid treatments for opioid-naïve patients and toward tapering for patients currently receiving a "high risk" opioid. The other intervention integrates the prescription drug monitoring program (PDMP) directly within the EHR. OUTCOME The primary outcome for opioid-naïve patients is whether an opioid is prescribed in a primary care visit without a non-opioid alternative pain treatment. The primary outcome for current opioid-using patients is whether opioid prescriptions were tapered with a documented rationale. DISCUSSION The PRINCE study will provide real-world evidence on two approaches to improving pain treatment in primary care using the EHR. The adaptive study design strikes a balance between establishing intervention efficacy and testing whether efficacy varies with intervention intensity.
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Affiliation(s)
- David M Vock
- Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Hannah T Neprash
- Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | | | | | - David J Satin
- Department of Family Medicine and Community Health, University of Minnesota Medical School, Minneapolis, MN, USA
| | | | - Sonja Short
- Fairview Health Services, Minneapolis, MN, USA
| | | | - Rebecca Markowitz
- Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Genevieve B Melton
- Fairview Health Services, Minneapolis, MN, USA; Department of Surgery, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Ezra Golberstein
- Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, USA.
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Hallek M, Ockenfels A, Wiesen D. Behavioral Economics Interventions to Improve Medical Decision-Making. DEUTSCHES ARZTEBLATT INTERNATIONAL 2022; 119:633-639. [PMID: 35912421 PMCID: PMC9764346 DOI: 10.3238/arztebl.m2022.0275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 09/30/2021] [Accepted: 04/07/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND In medicine, a wide gap exists between the medical care that ought to be possible in the light of the current state of medical research and the care that is actually provided. Behavioral biases and noise are two major reasons for this. METHODS We present the findings of a selective literature review and illustrate how interventions based on behavioral economics can help physicians make better decisions and thereby improve treatment outcomes. RESULTS A number of behavioral economics interventions, making use of, for example, default settings, active decision rules, social norms, and self-commitments, may improve physicians' clinical decision-making. Evidence on long-term effects is, however, mostly lacking. CONCLUSION Despite their apparent potential, the application of behavioral economic interventions to improve medical decisionmaking is still in its infancy, particularly in Germany.
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Affiliation(s)
- Michael Hallek
- University Hospital of Cologne, Internal Medicine Clinic I and Center for Integrated Oncology Aachen Bonn Cologne Dusseldorf (CIO)
| | - Axel Ockenfels
- Cologne University, Department of Economics, Center for Social and Economic Behavior (C-SEB) and Cluster of Excellence ECONtribute
| | - Daniel Wiesen
- Cologne University, Seminar for General Business Administration and Management in Healthcare and Center for Social and Economic Behavior (C-SEB),*Seminar for General Business Administration and Management in Healthcare University of Cologne Albertus-Magnus-Platz 50931 Cologne
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Xie CX, Chen Q, Hincapié CA, Hofstetter L, Maher CG, Machado GC. Effectiveness of clinical dashboards as audit and feedback or clinical decision support tools on medication use and test ordering: a systematic review of randomized controlled trials. J Am Med Inform Assoc 2022; 29:1773-1785. [PMID: 35689652 PMCID: PMC9471705 DOI: 10.1093/jamia/ocac094] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/04/2022] [Accepted: 05/31/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Clinical dashboards used as audit and feedback (A&F) or clinical decision support systems (CDSS) are increasingly adopted in healthcare. However, their effectiveness in changing the behavior of clinicians or patients is still unclear. This systematic review aims to investigate the effectiveness of clinical dashboards used as CDSS or A&F tools (as a standalone intervention or part of a multifaceted intervention) in primary care or hospital settings on medication prescription/adherence and test ordering. METHODS Seven major databases were searched for relevant studies, from inception to August 2021. Two authors independently extracted data, assessed the risk of bias using the Cochrane RoB II scale, and evaluated the certainty of evidence using GRADE. Data on trial characteristics and intervention effect sizes were extracted. A narrative synthesis was performed to summarize the findings of the included trials. RESULTS Eleven randomized trials were included. Eight trials evaluated clinical dashboards as standalone interventions and provided conflicting evidence on changes in antibiotic prescribing and no effects on statin prescribing compared to usual care. Dashboards increased medication adherence in patients with inflammatory arthritis but not in kidney transplant recipients. Three trials investigated dashboards as part of multicomponent interventions revealing decreased use of opioids for low back pain, increased proportion of patients receiving cardiovascular risk screening, and reduced antibiotic prescribing for upper respiratory tract infections. CONCLUSION There is limited evidence that dashboards integrated into electronic medical record systems and used as feedback or decision support tools may be associated with improvements in medication use and test ordering.
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Affiliation(s)
- Charis Xuan Xie
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Qiuzhe Chen
- Institute for Musculoskeletal Health, Sydney, NSW, Australia.,Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Cesar A Hincapié
- Department of Chiropractic Medicine, Faculty of Medicine, University of Zurich and Balgrist University Hospital, Zurich, Switzerland.,Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Léonie Hofstetter
- Department of Chiropractic Medicine, Faculty of Medicine, University of Zurich and Balgrist University Hospital, Zurich, Switzerland
| | - Chris G Maher
- Institute for Musculoskeletal Health, Sydney, NSW, Australia.,Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Gustavo C Machado
- Institute for Musculoskeletal Health, Sydney, NSW, Australia.,Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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Tudor K, Brooks J, Howick J, Fox R, Aveyard P. Unblinded and Blinded N-of-1 Trials Versus Usual Care: A Randomized Controlled Trial to Increase Statin Uptake in Primary Care. Circ Cardiovasc Qual Outcomes 2022; 15:e007793. [PMID: 35698974 DOI: 10.1161/circoutcomes.120.007793] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The aim was to assess whether an intervention incorporating a practicable open-label n-of-1 trial would lead to greater uptake of statin than usual care and comparable uptake to a closed-label gold-standard n-of-1 trial. METHODS We enrolled patients who had stopped or declined statins into a 3-arm trial (usual care, unblinded, and blinded n-of-1 intervention arms). Physicians advised participants randomized to usual care to take statin therapy to prevent cardiovascular disease. In both intervention arms, physicians delivered a theoretically informed informed intervention endorsing the value of experimenting with medication in n-of-1 trials to assess whether it caused side-effects. In these trials, participants alternated between 4 weeks of medication and no medication (unblinded arm) or randomly sorted active and placebo (blinded arm) and recorded symptoms and symptom attributions for 6 months. Thereafter, physicians discussed participants' symptom reports during active/inactive treatment periods and asked participants to resume statins if appropriate. RESULTS Seventy-three were randomized to the intervention arms and 20 to the control group. Fifty-six of 73 (77%) attempted the n-of-1 experiment; 28/36 (78%) in the unblinded arm; and 28/37 (76%) in the blinded arm. Forty-three of 56 (77%) completed the 6-month experiment and received feedback from the physician; 20/28 (71%) in the unblinded arm and 23/28 (82%) in the blinded arm. Thirty-three of 76 (45%) people restarted statins in the n-of-1 arms compared with 4/20 (20%) in the control arm, difference 24% (95% CI, 5%-43%; P=0.041). There was no evidence this differed between blinded and unblinded arms, difference 2% (95% CI, -20% to 24%; P=0.86). Adverse events occurred at a similar rate on and off statin. CONCLUSIONS In patients refusing or intolerant of statin, supporting experimentation with n-of-1 trials increases medication uptake compared with usual care. Alternating on-off medication in unblinded n-of-1 experiments appears as effective as a blinded experiment. REGISTRATION URL: https://doi.org/10.1186/ISRCTN11142694; Unique identifier: ISRCTN11142694.
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Affiliation(s)
- Kate Tudor
- Nuffield Department of Primary Care Health Sciences (K.T., J.B., P.A.), University of Oxford, Radcliffe Observatory Quarter, United Kingdom.,Department of Psychiatry, University of Oxford, Warneford Hospital, United Kingdom (K.T.)
| | - Jenny Brooks
- Nuffield Department of Primary Care Health Sciences (K.T., J.B., P.A.), University of Oxford, Radcliffe Observatory Quarter, United Kingdom
| | - Jeremy Howick
- Faculty of Philosophy (J.H.), University of Oxford, Radcliffe Observatory Quarter, United Kingdom
| | - Robin Fox
- Bicester Health Centre, Coker Close, Bicester, United Kingdom (R.F.)
| | - Paul Aveyard
- Nuffield Department of Primary Care Health Sciences (K.T., J.B., P.A.), University of Oxford, Radcliffe Observatory Quarter, United Kingdom.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals, NHS Foundation Trust, United Kingdom (P.A.)
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Parikh RB, Ferrell W, Wakim J, Williamson J, Khan N, Kopinsky M, Balachandran M, Gabriel PE, Zhang Y, Schuchter LM, Shulman LN, Chen J, Patel MS, Manz CR. Patient and clinician nudges to improve symptom management in advanced cancer using patient-generated health data: study protocol for the PROStep randomised controlled trial. BMJ Open 2022; 12:e054675. [PMID: 35551088 PMCID: PMC9109034 DOI: 10.1136/bmjopen-2021-054675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
INTRODUCTION Patients with advanced cancers often face significant symptoms from their cancer and adverse effects from cancer-associated therapy. Patient-generated health data (PGHD) are routinely collected information about symptoms and activity levels that patients either directly report or passively record using devices such as wearable accelerometers. The objective of this study was to test the impact of an intervention integrating remote collection of PGHD with clinician and patient nudges to inform communication between patients with advanced cancer and their oncology team regarding symptom burden and functional status. METHODS AND ANALYSIS This single-centre prospective randomised controlled trial randomises patients with metastatic gastrointestinal or lung cancers into one of three arms: (A) usual care, (B) an intervention that integrates PGHD (including weekly text-based symptom surveys and passively recorded step counts) into a dashboard delivered to oncology clinicians at each visit and (C) the same intervention as arm B but with an additional text-based active choice intervention to patients to encourage discussing their symptoms with their oncology team. The study will enrol approximately 125 participants. The coprimary outcomes are patient perceptions of their oncology team's understanding of their symptoms and their functional status. Secondary outcomes are intervention utility and adherence. ETHICS AND DISSEMINATION This study has been approved by the institutional review board at the University of Pennsylvania. Study results will be disseminated using methods that describe the results in ways that key stakeholders can best understand and implement. TRIAL REGISTRATION NUMBERS NCT04616768 and 843 616.
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Affiliation(s)
- Ravi B Parikh
- Abramson Cancer Center, Philadelphia, Pennsylvania, USA
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - William Ferrell
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jonathan Wakim
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Joelle Williamson
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Neda Khan
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Center for Health Care Innovation, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA
| | - Michael Kopinsky
- Center for Health Care Innovation, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA
| | - Mohan Balachandran
- Center for Health Care Innovation, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA
| | | | - Yichen Zhang
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | | | | | - Jinbo Chen
- Abramson Cancer Center, Philadelphia, Pennsylvania, USA
| | - Mitesh S Patel
- Departments of Medical Ethics and Health Policy and Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Christopher R Manz
- Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Medical Oncology, Harvard Medical School, Boston, Massachusetts, USA
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Zhuang M, Concannon D, Manley E. A Framework for Evaluating Dashboards in Healthcare. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2022; 28:1715-1731. [PMID: 35213306 DOI: 10.1109/tvcg.2022.3147154] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In the era of 'information overload', effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse information sources, dashboards have become an indispensable tool, providing fast, effective, adaptable, and personalized access to information for professionals and the general public alike. However, these objectives place heavy requirements on dashboards as information systems in usability and effective design. Understanding these issues is challenging given the absence of consistent and comprehensive approaches to dashboard evaluation. In this article we systematically review literature on dashboard implementation in healthcare, where dashboards have been employed widely, and where there is widespread interest for improving the current state of the art, and subsequently analyse approaches taken towards evaluation. We draw upon consolidated dashboard literature and our own observations to introduce a general definition of dashboards which is more relevant to current trends, together with seven evaluation scenarios - task performance, behaviour change, interaction workflow, perceived engagement, potential utility, algorithm performance and system implementation. These scenarios distinguish different evaluation purposes which we illustrate through measurements, example studies, and common challenges in evaluation study design. We provide a breakdown of each evaluation scenario, and highlight some of the more subtle questions. We demonstrate the use of the proposed framework by a design study guided by this framework. We conclude by comparing this framework with existing literature, outlining a number of active discussion points and a set of dashboard evaluation best practices for the academic, clinical and software development communities alike.
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Navathe AS, Liao JM, Yan XS, Delgado MK, Isenberg WM, Landa HM, Bond BL, Small DS, Rareshide CAL, Shen Z, Pepe RS, Refai F, Lei VJ, Volpp KG, Patel MS. The Effect Of Clinician Feedback Interventions On Opioid Prescribing. Health Aff (Millwood) 2022; 41:424-433. [PMID: 35254932 DOI: 10.1377/hlthaff.2021.01407] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
An initial opioid prescription with a greater number of pills is associated with a greater risk for future long-term opioid use, yet few interventions have reliably influenced individual clinicians' prescribing. Our objective was to evaluate the effect of feedback interventions for clinicians in reducing opioid prescribing. The interventions included feedback on a clinician's outlier prescribing (individual audit feedback), peer comparison, and both interventions combined. We conducted a four-arm factorial pragmatic cluster randomized trial at forty-eight emergency department (ED) and urgent care (UC) sites in the western US, including 263 ED and 175 UC clinicians with 294,962 patient encounters. Relative to usual care, there was a significant decrease in pills per prescription both for peer comparison feedback (-0.8) and for the combination of peer comparison and individual audit feedback (-1.2). This decrease was sustained during follow-up. There were no significant changes for individual audit feedback alone, and no interventions changed the proportion of encounters with an opioid prescription.
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Affiliation(s)
- Amol S Navathe
- Amol S. Navathe , Corporal Michael J. Cresencz Veterans Affairs Medical Center and University of Pennsylvania, Philadelphia, Pennsylvania
| | - Joshua M Liao
- Joshua M. Liao, University of Washington, Seattle, Washington, and University of Pennsylvania
| | - Xiaowei S Yan
- Xiaowei S. Yan, Sutter Health, Walnut Creek, California
| | | | | | | | - Barbara L Bond
- Barbara L. Bond, Sutter Health, Castro Valley, California
| | | | | | - Zijun Shen
- Zijun Shen, Sutter Health, San Francisco
| | | | | | | | | | - Mitesh S Patel
- Mitesh S. Patel, Corporal Michael J. Cresencz Veterans Affairs Medical Center and University of Pennsylvania
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Scofi J, Parwani V, Rothenberg C, Patel A, Ravi S, Sevilla M, D'Onofrio G, Ulrich A, Venkatesh AK. Improving Emergency Department Throughput Using Audit-and-Feedback With Peer Comparison Among Emergency Department Physicians. J Healthc Qual 2022; 44:69-77. [PMID: 34570029 DOI: 10.1097/jhq.0000000000000329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION We sought to determine if audit-and-feedback with peer comparison among emergency physicians is associated with improved emergency department (ED) throughput and decreased variation in physician performance. METHODS We implemented an audit-and-feedback with peer comparison tool at a single urban academic ED from March 1, 2013, to July 1, 2018. In the first study period, physicians received no reports. In the second period, they received daily reports. In the third period, they received daily, quarterly, and annual reports. Outcomes included patients per hour, admission rate, time to admission, and time to discharge. RESULTS A total of 272,032 patient visits and 36 ED physicians were included. The mean admission rate decreased 6.8%; the mean time to admission decreased 43.8 minutes; and the mean time to discharge decreased 40.6 minutes. Variation among physicians decreased for admission rate, time to admission, and time to discharge. Low-performing outliers showed disproportionately larger improvements in patients per hour, admission rate, time to admission, and time to discharge. CONCLUSIONS Automated peer comparison reports for academic emergency physicians was associated with lower admission rates, shorter times to admission, and shorter times to discharge at the departmental level, as well as decreased practice variation at the individual level.
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Talat U, Schmidtke KA, Khanal S, Chan A, Turner A, Horne R, Chadborn T, Gold N, Sallis A, Vlaev I. A Systematic Review of Nudge Interventions to Optimize Medication Prescribing. Front Pharmacol 2022; 13:798916. [PMID: 35145411 PMCID: PMC8822212 DOI: 10.3389/fphar.2022.798916] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/04/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The benefits of medication optimization are largely uncontroversial but difficult to achieve. Behavior change interventions aiming to optimize prescriber medication-related decisions, which do not forbid any option and that do not significantly change financial incentives, offer a promising way forward. These interventions are often referred to as nudges. Objective: The current systematic literature review characterizes published studies describing nudge interventions to optimize medication prescribing by the behavioral determinants they intend to influence and the techniques they apply. Methods: Four databases were searched (MEDLINE, Embase, PsychINFO, and CINAHL) to identify studies with nudge-type interventions aiming to optimize prescribing decisions. To describe the behavioral determinants that interventionists aimed to influence, data were extracted according to the Theoretical Domains Framework (TDF). To describe intervention techniques applied, data were extracted according to the Behavior Change Techniques (BCT) Taxonomy version 1 and MINDSPACE. Next, the recommended TDF-BCT mappings were used to appraise whether each intervention applied a sufficient array of techniques to influence all identified behavioral determinants. Results: The current review located 15 studies comprised of 20 interventions. Of the 20 interventions, 16 interventions (80%) were effective. The behavior change techniques most often applied involved prompts (n = 13). The MINDSPACE contextual influencer most often applied involved defaults (n = 10). According to the recommended TDF-BCT mappings, only two interventions applied a sufficient array of behavior change techniques to address the behavioral determinants the interventionists aimed to influence. Conclusion: The fact that so many interventions successfully changed prescriber behavior encourages the development of future behavior change interventions to optimize prescribing without mandates or financial incentives. The current review encourages interventionists to understand the behavioral determinants they are trying to affect, before the selection and application of techniques to change prescribing behaviors. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42020168006].
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Affiliation(s)
- Usman Talat
- Alliance Manchester Business School, The University of Manchester, Manchester, United Kingdom
| | - Kelly Ann Schmidtke
- Warwick Medical School, Coventry, United Kingdom
- *Correspondence: Kelly Ann Schmidtke, ; Ivo Vlaev,
| | - Saval Khanal
- Warwick Business School, Coventry, United Kingdom
| | - Amy Chan
- School of Pharmacy, University of Auckland, Auckland, New Zealand
| | - Alice Turner
- Institute for Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Robert Horne
- UCL School of Pharmacy, University College London, London, United Kingdom
| | | | - Natalie Gold
- London School of Economics and Political Science, Public Health England, London, United Kingdom
- Kantar Public, London, United Kingdom
| | - Anna Sallis
- Public Health England, London, United Kingdom
| | - Ivo Vlaev
- Warwick Business School, Coventry, United Kingdom
- *Correspondence: Kelly Ann Schmidtke, ; Ivo Vlaev,
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Chen Y, Harris S, Rogers Y, Ahmad T, Asselbergs FW. OUP accepted manuscript. Eur Heart J 2022; 43:1296-1306. [PMID: 35139182 PMCID: PMC8971005 DOI: 10.1093/eurheartj/ehac030] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 01/11/2022] [Accepted: 01/17/2022] [Indexed: 12/15/2022] Open
Abstract
The increasing volume and richness of healthcare data collected during routine clinical
practice have not yet translated into significant numbers of actionable insights that have
systematically improved patient outcomes. An evidence-practice gap continues to exist in
healthcare. We contest that this gap can be reduced by assessing the use of nudge theory
as part of clinical decision support systems (CDSS). Deploying nudges to modify clinician
behaviour and improve adherence to guideline-directed therapy represents an underused tool
in bridging the evidence-practice gap. In conjunction with electronic health records
(EHRs) and newer devices including artificial intelligence algorithms that are
increasingly integrated within learning health systems, nudges such as CDSS alerts should
be iteratively tested for all stakeholders involved in health decision-making: clinicians,
researchers, and patients alike. Not only could they improve the implementation of known
evidence, but the true value of nudging could lie in areas where traditional randomized
controlled trials are lacking, and where clinical equipoise and variation dominate. The
opportunity to test CDSS nudge alerts and their ability to standardize behaviour in the
face of uncertainty may generate novel insights and improve patient outcomes in areas of
clinical practice currently without a robust evidence base.
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Affiliation(s)
- Yang Chen
- Institute of Health Informatics, University College London,
222 Euston Road, London NW1 2DA, UK
- Clinical Research Informatics Unit, University College London Hospitals NHS
Healthcare Trust, London, UK
- Barts Heart Centre, St Bartholomew’s Hospital, London,
UK
| | - Steve Harris
- Institute of Health Informatics, University College London,
222 Euston Road, London NW1 2DA, UK
| | - Yvonne Rogers
- UCL Interaction Centre, University College London, London,
UK
| | - Tariq Ahmad
- Section of Cardiovascular Medicine, School of Medicine, Yale
University, New Haven, CT, USA
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Rendle KA, Beidas RS. Four strategic areas to advance equitable implementation of evidence-based practices in cancer care. Transl Behav Med 2021; 11:1980-1988. [PMID: 34850931 PMCID: PMC8634319 DOI: 10.1093/tbm/ibab105] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Affiliation(s)
- Katharine A Rendle
- Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104,USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA 19104,USA
| | - Rinad S Beidas
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104,USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA 19104,USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104,USA
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Implementation Science Center at the Leonard Davis Institute (PISCE@LDI), University of Pennsylvania, Philadelphia, PA 19104,USA
- Center for Health Incentives and Behavioral Economics (CHIBE), University of Pennsylvania, Philadelphia, PA 19104, USA
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Belli HM, Troxel AB, Blecker SB, Anderman J, Wong C, Martinez TR, Mann DM. A Behavioral Economics-Electronic Health Record Module to Promote Appropriate Diabetes Management in Older Adults: Protocol for a Pragmatic Cluster Randomized Controlled Trial. JMIR Res Protoc 2021; 10:e28723. [PMID: 34704959 PMCID: PMC8581753 DOI: 10.2196/28723] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 07/28/2021] [Accepted: 08/24/2021] [Indexed: 11/13/2022] Open
Abstract
Background The integration of behavioral economics (BE) principles and electronic health records (EHRs) using clinical decision support (CDS) tools is a novel approach to improving health outcomes. Meanwhile, the American Geriatrics Society has created the Choosing Wisely (CW) initiative to promote less aggressive glycemic targets and reduction in pharmacologic therapy in older adults with type 2 diabetes mellitus. To date, few studies have shown the effectiveness of combined BE and EHR approaches for managing chronic conditions, and none have addressed guideline-driven deprescribing specifically in type 2 diabetes. We previously conducted a pilot study aimed at promoting appropriate CW guideline adherence using BE nudges and EHRs embedded within CDS tools at 5 clinics within the New York University Langone Health (NYULH) system. The BE-EHR module intervention was tested for usability, adoption, and early effectiveness. Preliminary results suggested a modest improvement of 5.1% in CW compliance. Objective This paper presents the protocol for a study that will investigate the effectiveness of a BE-EHR module intervention that leverages BE nudges with EHR technology and CDS tools to reduce overtreatment of type 2 diabetes in adults aged 76 years and older, per the CW guideline. Methods A pragmatic, investigator-blind, cluster randomized controlled trial was designed to evaluate the BE-EHR module. A total of 66 NYULH clinics will be randomized 1:1 to receive for 18 months either (1) a 6-component BE-EHR module intervention + standard care within the NYULH EHR, or (2) standard care only. The intervention will be administered to clinicians during any patient encounter (eg, in person, telemedicine, medication refill, etc). The primary outcome will be patient-level CW compliance. Secondary outcomes will measure the frequency of intervention component firings within the NYULH EHR, and provider utilization and interaction with the BE-EHR module components. Results Study recruitment commenced on December 7, 2020, with the activation of all 6 BE-EHR components in the NYULH EHR. Conclusions This study will test the effectiveness of a previously developed, iteratively refined, user-tested, and pilot-tested BE-EHR module aimed at providing appropriate diabetes care to elderly adults, compared to usual care via a cluster randomized controlled trial. This innovative research will be the first pragmatic randomized controlled trial to use BE principles embedded within the EHR and delivered using CDS tools to specifically promote CW guideline adherence in type 2 diabetes. The study will also collect valuable information on clinician workflow and interaction with the BE-EHR module, guiding future research in optimizing the timely delivery of BE nudges within CDS tools. This work will address the effectiveness of BE-inspired interventions in diabetes and chronic disease management. Trial Registration ClinicalTrials.gov NCT04181307; https://clinicaltrials.gov/ct2/show/NCT04181307 International Registered Report Identifier (IRRID) DERR1-10.2196/28723
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Affiliation(s)
- Hayley M Belli
- Division of Biostatistics, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States
| | - Andrea B Troxel
- Division of Biostatistics, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States
| | - Saul B Blecker
- Division of Healthcare Delivery Science, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States.,Department of Medicine, Grossman School of Medicine, New York University, New York, NY, United States
| | - Judd Anderman
- Medical Center Information Technology, New York University Langone Health, New York, NY, United States
| | - Christina Wong
- Medical Center Information Technology, New York University Langone Health, New York, NY, United States
| | - Tiffany R Martinez
- Division of Healthcare Delivery Science, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States
| | - Devin M Mann
- Division of Healthcare Delivery Science, Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States.,Department of Medicine, Grossman School of Medicine, New York University, New York, NY, United States.,Medical Center Information Technology, New York University Langone Health, New York, NY, United States
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Khazanov GK, Forbes CN, Dunn BD, Thase ME. Addressing anhedonia to increase depression treatment engagement. BRITISH JOURNAL OF CLINICAL PSYCHOLOGY 2021; 61:255-280. [PMID: 34625993 DOI: 10.1111/bjc.12335] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 08/30/2021] [Indexed: 12/14/2022]
Abstract
Anhedonia, or reward system dysfunction, is associated with poorer treatment outcomes among depressed individuals. The role of anhedonia in treatment engagement, however, has not yet been explored. We review research on components of reward functioning impaired in depression, including effort valuation, reward anticipation, initial responsiveness, reward learning, reward probability, and reward delay, highlighting potential barriers to treatment engagement associated with these components. We then propose interventions to improve treatment initiation and continuation by addressing deficits in each component of reward functioning, focusing on modifications of existing evidence-based interventions to meet the needs of individuals with heightened anhedonia. We describe potential settings for these interventions and times at which they can be delivered during the process of referring individuals to mental health treatment, conducting intakes or assessments, and providing treatment. Additionally, we note the advantages of using screening processes already in place in primary care, workplace, school, and online settings to identify individuals with heightened anhedonia who may benefit from these interventions. We conclude with suggestions for future research on the impact of anhedonia on treatment engagement and the efficacy of interventions to address it. PRACTITIONER POINTS: Many depressed individuals who might benefit from treatment do not initiate it or discontinue early. One barrier to treatment engagement may be anhedonia, a core symptom of depression characterized by loss of interest or pleasure in usual activities. We describe brief interventions to improve treatment engagement in individuals with anhedonia that can be implemented during the referral process or early in treatment. We argue that interventions aiming to improve treatment engagement in depressed individuals that target anhedonia may be particularly effective.
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Affiliation(s)
- Gabriela K Khazanov
- Mental Illness Research, Education, and Clinical Center of the Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
| | | | | | - Michael E Thase
- Mental Illness Research, Education, and Clinical Center of the Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
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Abstract
PURPOSE OF REVIEW Behavioral economics represents a promising set of principles to inform the design of health-promoting interventions. Techniques from the field have the potential to increase quality of cardiovascular care given suboptimal rates of guideline-directed care delivery and patient adherence to optimal health behaviors across the spectrum of cardiovascular care delivery. RECENT FINDINGS Cardiovascular health-promoting interventions have demonstrated success in using a wide array of principles from behavioral economics, including loss framing, social norms, and gamification. Such approaches are becoming increasingly sophisticated and focused on clinical cardiovascular outcomes in addition to health behaviors as a primary endpoint. Many approaches can be used to improve patient decisions remotely, which is particularly useful given the shift to virtual care in the context of the COVID-19 pandemic. Numerous applications for behavioral economics exist in the cardiovascular care delivery space, though more work is needed before we will have a full understanding of ways to best leverage such applications in each clinical context.
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Takvorian SU, Bekelman J, Beidas RS, Schnoll R, Clifton ABW, Salam T, Gabriel P, Wileyto EP, Scott CA, Asch DA, Buttenheim AM, Rendle KA, Chaiyachati K, Shelton RC, Ware S, Chivers C, Schuchter LM, Kumar P, Shulman LN, O'Connor N, Lieberman A, Zentgraf K, Parikh RB. Behavioral economic implementation strategies to improve serious illness communication between clinicians and high-risk patients with cancer: protocol for a cluster randomized pragmatic trial. Implement Sci 2021; 16:90. [PMID: 34563227 PMCID: PMC8466719 DOI: 10.1186/s13012-021-01156-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/06/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Serious illness conversations (SICs) are an evidence-based approach to eliciting patients' values, goals, and care preferences that improve patient outcomes. However, most patients with cancer die without a documented SIC. Clinician-directed implementation strategies informed by behavioral economics ("nudges") that identify high-risk patients have shown promise in increasing SIC documentation among clinicians. It is unknown whether patient-directed nudges that normalize and prime patients towards SIC completion-either alone or in combination with clinician nudges that additionally compare performance relative to peers-may improve on this approach. Our objective is to test the effect of clinician- and patient-directed nudges as implementation strategies for increasing SIC completion among patients with cancer. METHODS We will conduct a 2 × 2 factorial, cluster randomized pragmatic trial to test the effect of nudges to clinicians, patients, or both, compared to usual care, on SIC completion. Participants will include 166 medical and gynecologic oncology clinicians practicing at ten sites within a large academic health system and their approximately 5500 patients at high risk of predicted 6-month mortality based on a validated machine-learning prognostic algorithm. Data will be obtained via the electronic medical record, clinician survey, and semi-structured interviews with clinicians and patients. The primary outcome will be time to SIC documentation among high-risk patients. Secondary outcomes will include time to SIC documentation among all patients (assessing spillover effects), palliative care referral among high-risk patients, and aggressive end-of-life care utilization (composite of chemotherapy within 14 days before death, hospitalization within 30 days before death, or admission to hospice within 3 days before death) among high-risk decedents. We will assess moderators of the effect of implementation strategies and conduct semi-structured interviews with a subset of clinicians and patients to assess contextual factors that shape the effectiveness of nudges with an eye towards health equity. DISCUSSION This will be the first pragmatic trial to evaluate clinician- and patient-directed nudges to promote SIC completion for patients with cancer. We expect the study to yield insights into the effectiveness of clinician and patient nudges as implementation strategies to improve SIC rates, and to uncover multilevel contextual factors that drive response to these strategies. TRIAL REGISTRATION ClinicalTrials.gov , NCT04867850 . Registered on April 30, 2021. FUNDING National Cancer Institute P50CA244690.
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Affiliation(s)
- Samuel U Takvorian
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA.
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA.
| | - Justin Bekelman
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Rinad S Beidas
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Penn Implementation Science Center, Leonard Davis Institute of Health Economics, Philadelphia, PA, USA
- Penn Medicine Nudge Unit, Center for Healthcare Innovation, Penn Medicine, Philadelphia, PA, USA
| | - Robert Schnoll
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Center for Interdisciplinary Research on Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Alicia B W Clifton
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Tasnim Salam
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Peter Gabriel
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - E Paul Wileyto
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Center for Interdisciplinary Research on Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Callie A Scott
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - David A Asch
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Alison M Buttenheim
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
| | - Katharine A Rendle
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Krisda Chaiyachati
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
| | - Rachel C Shelton
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Sue Ware
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Center for Interdisciplinary Research on Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Corey Chivers
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
| | - Lynn M Schuchter
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Pallavi Kumar
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
| | - Lawrence N Shulman
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Nina O'Connor
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
| | - Adina Lieberman
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Implementation Science Center, Leonard Davis Institute of Health Economics, Philadelphia, PA, USA
- Penn Medicine Nudge Unit, Center for Healthcare Innovation, Penn Medicine, Philadelphia, PA, USA
| | - Kelly Zentgraf
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Implementation Science Center, Leonard Davis Institute of Health Economics, Philadelphia, PA, USA
- Penn Medicine Nudge Unit, Center for Healthcare Innovation, Penn Medicine, Philadelphia, PA, USA
| | - Ravi B Parikh
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, 10S-113, Philadelphia, PA, 19104, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
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Beidas RS, Ahmedani BK, Linn KA, Marcus SC, Johnson C, Maye M, Westphal J, Wright L, Beck AL, Buttenheim AM, Daley MF, Davis M, Elias ME, Jager-Hyman S, Hoskins K, Lieberman A, McArdle B, Ritzwoller DP, Small DS, Wolk CB, Williams NJ, Boggs JM. Study protocol for a type III hybrid effectiveness-implementation trial of strategies to implement firearm safety promotion as a universal suicide prevention strategy in pediatric primary care. Implement Sci 2021; 16:89. [PMID: 34551811 PMCID: PMC8456701 DOI: 10.1186/s13012-021-01154-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 08/24/2021] [Indexed: 01/23/2023] Open
Abstract
Background Insights from behavioral economics, or how individuals’ decisions and behaviors are shaped by finite cognitive resources (e.g., time, attention) and mental heuristics, have been underutilized in efforts to increase the use of evidence-based practices in implementation science. Using the example of firearm safety promotion in pediatric primary care, which addresses an evidence-to-practice gap in universal suicide prevention, we aim to determine: is a less costly and more scalable behavioral economic-informed implementation strategy (i.e., “Nudge”) powerful enough to change clinician behavior or is a more intensive and expensive facilitation strategy needed to overcome implementation barriers? Methods The Adolescent and child Suicide Prevention in Routine clinical Encounters (ASPIRE) hybrid type III effectiveness-implementation trial uses a longitudinal cluster randomized design. We will test the comparative effectiveness of two implementation strategies to support clinicians’ use of an evidence-based firearm safety practice, S.A.F.E. Firearm, in 32 pediatric practices across two health systems. All pediatric practices in the two health systems will receive S.A.F.E. Firearm materials, including training and cable locks. Half of the practices (k = 16) will be randomized to receive Nudge; the other half (k = 16) will be randomized to receive Nudge plus 1 year of facilitation to target additional practice and clinician implementation barriers (Nudge+). The primary implementation outcome is parent-reported clinician fidelity to the S.A.F.E Firearm program. Secondary implementation outcomes include reach and cost. To understand how the implementation strategies work, the primary mechanism to be tested is practice adaptive reserve, a self-report practice-level measure that includes relationship infrastructure, facilitative leadership, sense-making, teamwork, work environment, and culture of learning. Discussion The ASPIRE trial will integrate implementation science and behavioral economic approaches to advance our understanding of methods for implementing evidence-based firearm safety promotion practices in pediatric primary care. The study answers a question at the heart of many practice change efforts: which strategies are sufficient to support change, and why? Results of the trial will offer valuable insights into how best to implement evidence-based practices that address sensitive health matters in pediatric primary care. Trial registration ClinicalTrials.gov, NCT04844021. Registered 14 April 2021. Supplementary Information The online version contains supplementary material available at 10.1186/s13012-021-01154-8.
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Affiliation(s)
- Rinad S Beidas
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Brian K Ahmedani
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA
| | - Kristin A Linn
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven C Marcus
- School of Social Policy and Practice, University of Pennsylvania, Philadelphia, PA, USA
| | - Christina Johnson
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Melissa Maye
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA
| | - Joslyn Westphal
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA
| | - Leslie Wright
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Arne L Beck
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | | | - Matthew F Daley
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Molly Davis
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marisa E Elias
- Department of Pediatrics, Henry Ford Health System, Detroit, MI, USA
| | - Shari Jager-Hyman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katelin Hoskins
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Adina Lieberman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bridget McArdle
- Department of Pediatrics, Henry Ford Health System, Detroit, MI, USA
| | - Debra P Ritzwoller
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Dylan S Small
- Wharton School of Business, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Jennifer M Boggs
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
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Van Den Bulck S, Spitaels D, Vaes B, Goderis G, Hermens R, Vankrunkelsven P. The effect of electronic audits and feedback in primary care and factors that contribute to their effectiveness: a systematic review. Int J Qual Health Care 2021; 32:708-720. [PMID: 33057648 DOI: 10.1093/intqhc/mzaa128] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 09/21/2020] [Accepted: 10/06/2020] [Indexed: 12/14/2022] Open
Abstract
PURPOSE The aim of this systematic review was (i) to assess whether electronic audit and feedback (A&F) is effective in primary care and (ii) to evaluate important features concerning content and delivery of the feedback in primary care, including the use of benchmarks, the frequency of feedback, the cognitive load of feedback and the evidence-based aspects of the feedback. DATA SOURCES The MEDLINE, Embase, CINAHL and CENTRAL databases were searched for articles published since 2010 by replicating the search strategy used in the last Cochrane review on A&F. STUDY SELECTION Two independent reviewers assessed the records for their eligibility, performed the data extraction and evaluated the risk of bias. Our search resulted in 8744 records, including the 140 randomized controlled trials (RCTs) from the last Cochrane Review. The full texts of 431 articles were assessed to determine their eligibility. Finally, 29 articles were included. DATA EXTRACTION Two independent reviewers extracted standard data, data on the effectiveness and outcomes of the interventions, data on the kind of electronic feedback (static versus interactive) and data on the aforementioned feedback features. RESULTS OF DATA SYNTHESIS Twenty-two studies (76%) showed that electronic A&F was effective. All interventions targeting medication safety, preventive medicine, cholesterol management and depression showed an effect. Approximately 70% of the included studies used benchmarks and high-quality evidence in the content of the feedback. In almost half of the studies, the cognitive load of feedback was not reported. Due to high heterogeneity in the results, no meta-analysis was performed. CONCLUSION This systematic review included 29 articles examining electronic A&F interventions in primary care, and 76% of the interventions were effective. Our findings suggest electronic A&F is effective in primary care for different conditions such as medication safety and preventive medicine. Some of the benefits of electronic A&F include its scalability and the potential to be cost effective. The use of benchmarks as comparators and feedback based on high-quality evidence are widely used and important features of electronic feedback in primary care. However, other important features such as the cognitive load of feedback and the frequency of feedback provision are poorly described in the design of many electronic A&F intervention, indicating that a better description or implementation of these features is needed. Developing a framework or methodology for automated A&F interventions in primary care could be useful for future research.
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Affiliation(s)
- Steve Van Den Bulck
- Academic Center for General Practice, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33, blok J, 3000, Leuven, Belgium
| | - David Spitaels
- Academic Center for General Practice, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33, blok J, 3000, Leuven, Belgium
| | - Bert Vaes
- Academic Center for General Practice, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33, blok J, 3000, Leuven, Belgium
| | - Geert Goderis
- Academic Center for General Practice, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33, blok J, 3000, Leuven, Belgium
| | - Rosella Hermens
- Academic Center for General Practice, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33, blok J, 3000, Leuven, Belgium.,Scientific Institute for Quality of Healthcare (IQ Healthcare), Radboud Institute for Health Science (RIHS), Radboud University Medical Center, Radboud University Nijmegen, PO Box 9101, Nijmegen, 6500, HB, The Netherlands
| | - Patrik Vankrunkelsven
- Academic Center for General Practice, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33, blok J, 3000, Leuven, Belgium
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Abstract
OBJECTIVE Nudges are interventions that alter the way options are presented, enabling individuals to more easily select the best option. Health systems and researchers have tested nudges to shape clinician decision-making with the aim of improving healthcare service delivery. We aimed to systematically study the use and effectiveness of nudges designed to improve clinicians' decisions in healthcare settings. DESIGN A systematic review was conducted to collect and consolidate results from studies testing nudges and to determine whether nudges directed at improving clinical decisions in healthcare settings across clinician types were effective. We systematically searched seven databases (EBSCO MegaFILE, EconLit, Embase, PsycINFO, PubMed, Scopus and Web of Science) and used a snowball sampling technique to identify peer-reviewed published studies available between 1 January 1984 and 22 April 2020. Eligible studies were critically appraised and narratively synthesised. We categorised nudges according to a taxonomy derived from the Nuffield Council on Bioethics. Included studies were appraised using the Cochrane Risk of Bias Assessment Tool. RESULTS We screened 3608 studies and 39 studies met our criteria. The majority of the studies (90%) were conducted in the USA and 36% were randomised controlled trials. The most commonly studied nudge intervention (46%) framed information for clinicians, often through peer comparison feedback. Nudges that guided clinical decisions through default options or by enabling choice were also frequently studied (31%). Information framing, default and enabling choice nudges showed promise, whereas the effectiveness of other nudge types was mixed. Given the inclusion of non-experimental designs, only a small portion of studies were at minimal risk of bias (33%) across all Cochrane criteria. CONCLUSIONS Nudges that frame information, change default options or enable choice are frequently studied and show promise in improving clinical decision-making. Future work should examine how nudges compare to non-nudge interventions (eg, policy interventions) in improving healthcare.
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Affiliation(s)
- Briana S Last
- Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alison M Buttenheim
- Department of Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
- Center for Health Incentives and Behavioral Economics (CHIBE), University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Penn Implementation Science Center at the Leonard Davis Institute of Health Economics (PISCE@LDI), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Carter E Timon
- College of Liberal and Professional Studies, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nandita Mitra
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Rinad S Beidas
- Center for Health Incentives and Behavioral Economics (CHIBE), University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Penn Implementation Science Center at the Leonard Davis Institute of Health Economics (PISCE@LDI), University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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Sant'Anna A, Vilhelmsson A, Wolf A. Nudging healthcare professionals in clinical settings: a scoping review of the literature. BMC Health Serv Res 2021; 21:543. [PMID: 34078358 PMCID: PMC8170624 DOI: 10.1186/s12913-021-06496-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 05/07/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Healthcare organisations are in constant need of improvement and change. Nudging has been proposed as a strategy to affect people's choices and has been used to affect patients' behaviour in healthcare settings. However, little is known about how nudging is being interpreted and applied to change the behaviour of healthcare professionals (HCPs). The objective of this review is to identify interventions using nudge theory to affect the behaviour of HCPs in clinical settings. METHODS A scoping review. We searched PubMed and PsycINFO for articles published from 2010 to September 2019, including terms related to "nudging" in the title or abstract. Two reviewers screened articles for inclusion based on whether the articles described an intervention to change the behaviour of HCPs. Two reviewers extracted key information and categorized included articles. Descriptive analyses were performed on the data. RESULTS Search results yielded 997 unique articles, of which 25 articles satisfied the inclusion criteria. Five additional articles were selected from the reference lists of the included articles. We identified 11 nudging strategies: accountable justification, goal setting, suggested alternatives, feedback, information transparency, peer comparison, active choice, alerts and reminders, environmental cueing/priming, defaults/pre-orders, and education. These strategies were employed to affect the following 4 target behaviours: vaccination of staff, hand hygiene, clinical procedures, prescriptions and orders. To compare approaches across so many areas, we introduced two independent dimensions to describe nudging strategies: synchronous/asynchronous, and active/passive. CONCLUSION There are relatively few studies published referring to nudge theory aimed at changing HCP behaviour in clinical settings. These studies reflect a diverse set of objectives and implement nudging strategies in a variety of ways. We suggest distinguishing active from passive nudging strategies. Passive nudging strategies may achieve the desired outcome but go unnoticed by the clinician thereby not really changing a behaviour and raising ethical concerns. Our review indicates that there are successful active strategies that engage with clinicians in a more deliberate way. However, more research is needed on how different nudging strategies impact HCP behaviour in the short and long term to improve clinical decision making.
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Affiliation(s)
| | - Andreas Vilhelmsson
- Centre for Person-Centred Care (GPCC), University of Gothenburg, Box 100, 40530, Gothenburg, SE, Sweden
| | - Axel Wolf
- Centre for Person-Centred Care (GPCC), University of Gothenburg, Box 100, 40530, Gothenburg, SE, Sweden.
- Institute of Health and Care Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
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Charleston L, Ovbiagele B. Diversity in neurology leadership: Nuances and nudges. J Neurol Sci 2021; 426:117475. [PMID: 33965794 DOI: 10.1016/j.jns.2021.117475] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 04/08/2021] [Accepted: 04/30/2021] [Indexed: 10/21/2022]
Abstract
Underrepresented in medicine (UIM) academic physicians are poorly represented among medical school faculty when compared with their proportion in the US population, receive NIH research awards less frequently, are promoted less often, indicate lower career satisfaction, and report higher social isolation, than faculty who are not under-represented. Supporting a successful and sustainable workforce of UIM academic physicians is essential in neurology, because such neurologists are more likely to engage in research to reduce disparities in neurological outcomes that affect underserved and/or low-income communities, and help improve the paucity of diverse race-ethnic participation in clinical trials. Having more diverse academic neurologists serve in such roles could bolster their careers and model possibilities for others who share similar cultures and backgrounds. Beyond leading/joining diversity affairs committees, more UIM are needed in mainstream leadership roles. In this work, we explore self-application vs. appointment/nomination opportunities and how this play a role in leadership opportunities. In addition to considering appropriate weighing of self-applications vs. appointments based opportunities, we highlight approaches and introduce the concept of nudging. Nudging, which refers to purposely increasing the visibility and appeal of particular items with the goal of boosting the odds of selecting those items, has been shown to successfully influence the process of selection, and may help level the leadership playing field for UIM in neurology.
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Affiliation(s)
- Larry Charleston
- Department of Neurology and Ophthalmology, Michigan State University College of Human Medicine, East Lansing, MI, United States of America.
| | - Bruce Ovbiagele
- Department of Neurology, University of California, San Francisco, CA, United States of America
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Lamprell K, Tran Y, Arnolda G, Braithwaite J. Nudging clinicians: A systematic scoping review of the literature. J Eval Clin Pract 2021; 27:175-192. [PMID: 32342613 DOI: 10.1111/jep.13401] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 03/19/2020] [Accepted: 03/23/2020] [Indexed: 11/30/2022]
Abstract
BACKGROUND While the quality of medical care delivered by physicians can be very good, it can also be inconsistent and feature behaviours that are entrenched despite updated information and evidence. The "nudge" paradigm for behaviour change is being used to bring clinical practice in line with desired standards. The premise is that behaviour can be voluntarily shifted by making particular choices instinctively appealing. We reviewed studies that are explicit about their use of nudge theory in influencing clinician behaviour. METHODS Databases were searched from April 2008 (the publication date of the book that introduced nudge theory to a wider audience) to November 2018, inclusive. The search strategy and narrative review of results addressed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. RESULTS 22 studies were identified. Randomized trials or pre-post comparisons were generally used in community-based settings; single-site pre-post studies were favoured in hospitals. The studies employed eight intervention types: active choice; patient chart redesign; default and default alerts; partitioning of prescription menus; audit and feedback; commitment messages; peer comparisons; and redirection of workflow. Three core cognitive factors underpinned the eight interventions: bias towards prominent choices (salience); predisposition to social norms; and bias towards time or cost savings. CONCLUSIONS Published studies that are explicit about their use of nudge theory are few in number and diverse in their settings, targets, and results. Default and chart re-design interventions reported the most substantial improvements in adherence to evidence and guideline-based practice. Studies that are explicit in their use of nudge theory address the widespread failure of clinical practice studies to identify theoretical frameworks for interventions. However, few studies identified in our review engaged in research to understand the contextual and site-specific barriers to a desired behaviour before designing a nudge intervention.
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Affiliation(s)
- Klay Lamprell
- Macquarie University, Australian Institute of Health Innovation, Sydney, New South Wales, Australia
| | - Yvonne Tran
- Macquarie University, Australian Institute of Health Innovation, Sydney, New South Wales, Australia
| | - Gaston Arnolda
- Macquarie University, Australian Institute of Health Innovation, Sydney, New South Wales, Australia
| | - Jeffrey Braithwaite
- Macquarie University, Australian Institute of Health Innovation, Sydney, New South Wales, Australia
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Yang CC, Kang BH, Liu WS, Yin CH, Lee CC. Association of a multiple-step action with cervical lymph node yield of oral cancer patients in an Asian country. BMC Oral Health 2021; 21:29. [PMID: 33441108 PMCID: PMC7805045 DOI: 10.1186/s12903-021-01389-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 01/04/2021] [Indexed: 11/10/2022] Open
Abstract
Background High quality lymph node (LN) yield could increase survival, however strategies to improve LN yield have been seldom reported. This study aimed to assess the multiple-step action to promote quality of neck dissection in oral cancer. Methods A total of 400 patients with oral cancer who underwent primary tumor resection and neck dissection, including elective and radical neck dissection, were recruited after propensity score matching by clinical T and N categories between January 2009 and September 2018. Patients were treated by two independent departments in our institute. A multiple-step action was initiated in October 2015 in one department, and another department was as a control group. The impact of multiple-step action on LN yield and regional recurrence were analyzed using multivariate analysis and difference-in-differences (DID) linear regression analysis. Results The mean patient age was 55.2 + 11.1 years, and 92% were male. A total of 180 (45%) patients had T3-4 disease, and 129 (32%) patients had N2-3 disease. The multivariate linear regression and DID analyses revealed that multiple-step action had a positive effect on LN yield. A net improvement of LN yield with a coefficient of 13.78 (p < 0.001) after launching multiple-step action (since October 2015) was observed. A borderline protective effect of multiple-step action for cN0 patients with a reduced regional recurrence rate of 11.6% (p = 0.072) through DID analysis was noted. Conclusions Multiple-step action was associated with increased LN yield and decreased regional recurrence in patients with oral cancer. The observed activity may promote surgeons to improve the quality of neck dissections, is feasible, and could be applied to a widespread patient population.
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Affiliation(s)
- Ching-Chieh Yang
- Department of Radiation Oncology, Chi-Mei Medical Center, Tainan, Taiwan.,Department of Pharmacy, Chia-Nan University of Pharmacy and Science, Tainan, Taiwan
| | - Bor-Hwang Kang
- Department of Otolaryngology, Head and Neck Surgery, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.,School of Medicine, National Defense Medical Center, Taipei, Taiwan.,Department of Pharmacy, Tajen University, Pingtung, Taiwan
| | - Wen-Shan Liu
- Department of Radiation Oncology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Chun-Hao Yin
- Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Ching-Chih Lee
- Department of Otolaryngology, Head and Neck Surgery, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. .,School of Medicine, National Defense Medical Center, Taipei, Taiwan. .,Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. .,Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei, Taiwan.
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Effectiveness of an automated feedback with dashboard on use of laboratory tests by neurology residents. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100767] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Rogers MM, Chambers B, Esch A, Meier DE, Bowman B. Use of an Online Palliative Care Clinical Curriculum to Train U.S. Hospital Staff: 2015-2019. J Palliat Med 2020; 24:488-495. [PMID: 33306934 DOI: 10.1089/jpm.2020.0514] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Most clinicians in the United States do not receive pre-professional education in pain and symptom management, communication skills, and caregiver support. The use of these skills by clinicians improves the quality of care for persons living with serious illness and enables the specialty-trained palliative care workforce to focus on patients whose needs are most complex. Objective: To review current trends in hospital use of the Center to Advance Palliative Care (CAPC) online clinical training curriculum. Description: Launched in 2015, CAPC clinical curriculum educates clinicians in the knowledge and skills necessary to improve care for patients with serious illness. CAPC currently offers 43 clinical courses and 4 Designations in recognition of successful completion of training by topic. Results: From January 15, 2015, to August 31, 2019, 26,535 clinicians working in hospitals completed 172,684 clinical courses. Registered nurses represented half of learners, and advanced practice providers were most likely to seek Designation. Physicians made up 22% of all learners; 85% of physician learners came from specialties beyond palliative care. Two of every five U.S. hospitals with more than 300 beds had at least one learner. In post-course evaluations, 84% reported that they will make practice changes as a result, and 70% reported that the content was new. Conclusions: The CAPC clinical curriculum is a widely used and valued method for education in clinical skills specific to the care of people living with serious illness. Findings suggest that an increasing number of hospital leaders recognize the importance of these skills in caring for patients with serious illness and support the necessary training.
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Affiliation(s)
- Maggie M Rogers
- Center to Advance Palliative Care of the Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Brittany Chambers
- Center to Advance Palliative Care of the Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Andrew Esch
- Center to Advance Palliative Care of the Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Diane E Meier
- Center to Advance Palliative Care of the Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Brynn Bowman
- Center to Advance Palliative Care of the Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Manz CR, Parikh RB, Small DS, Evans CN, Chivers C, Regli SH, Hanson CW, Bekelman JE, Rareshide CAL, O'Connor N, Schuchter LM, Shulman LN, Patel MS. Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial. JAMA Oncol 2020; 6:e204759. [PMID: 33057696 PMCID: PMC7563672 DOI: 10.1001/jamaoncol.2020.4759] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Importance Serious illness conversations (SICs) are structured conversations between clinicians and patients about prognosis, treatment goals, and end-of-life preferences. Interventions that increase the rate of SICs between oncology clinicians and patients may improve goal-concordant care and patient outcomes. Objective To determine the effect of a clinician-directed intervention integrating machine learning mortality predictions with behavioral nudges on motivating clinician-patient SICs. Design, Setting, and Participants This stepped-wedge cluster randomized clinical trial was conducted across 20 weeks (from June 17 to November 1, 2019) at 9 medical oncology clinics (8 subspecialty oncology and 1 general oncology clinics) within a large academic health system in Pennsylvania. Clinicians at the 2 smallest subspecialty clinics were grouped together, resulting in 8 clinic groups randomly assigned to the 4 intervention wedge periods. Included participants in the intention-to-treat analyses were 78 oncology clinicians who received SIC training and their patients (N = 14 607) who had an outpatient oncology encounter during the study period. Interventions (1) Weekly emails to oncology clinicians with SIC performance feedback and peer comparisons; (2) a list of up to 6 high-risk patients (≥10% predicted risk of 180-day mortality) scheduled for the next week, estimated using a validated machine learning algorithm; and (3) opt-out text message prompts to clinicians on the patient's appointment day to consider an SIC. Clinicians in the control group received usual care consisting of weekly emails with cumulative SIC performance. Main Outcomes and Measures Percentage of patient encounters with an SIC in the intervention group vs the usual care (control) group. Results The sample consisted of 78 clinicians and 14 607 patients. The mean (SD) age of patients was 61.9 (14.2) years, 53.7% were female, and 70.4% were White. For all encounters, SICs were conducted among 1.3% in the control group and 4.6% in the intervention group, a significant difference (adjusted difference in percentage points, 3.3; 95% CI, 2.3-4.5; P < .001). Among 4124 high-risk patient encounters, SICs were conducted among 3.6% in the control group and 15.2% in the intervention group, a significant difference (adjusted difference in percentage points, 11.6; 95% CI, 8.2-12.5; P < .001). Conclusions and Relevance In this stepped-wedge cluster randomized clinical trial, an intervention that delivered machine learning mortality predictions with behavioral nudges to oncology clinicians significantly increased the rate of SICs among all patients and among patients with high mortality risk who were targeted by the intervention. Behavioral nudges combined with machine learning mortality predictions can positively influence clinician behavior and may be applied more broadly to improve care near the end of life. Trial Registration ClinicalTrials.gov Identifier: NCT03984773.
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Affiliation(s)
- Christopher R Manz
- Department of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ravi B Parikh
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia.,Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Dylan S Small
- Wharton School of the University of Pennsylvania, Philadelphia
| | - Chalanda N Evans
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Medicine Nudge Unit, Philadelphia, Pennsylvania
| | - Corey Chivers
- University of Pennsylvania Health System, Philadelphia
| | - Susan H Regli
- University of Pennsylvania Health System, Philadelphia
| | | | - Justin E Bekelman
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | - Charles A L Rareshide
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Medicine Nudge Unit, Philadelphia, Pennsylvania
| | - Nina O'Connor
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Lynn M Schuchter
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | - Lawrence N Shulman
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia
| | - Mitesh S Patel
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.,Penn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia.,Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.,Penn Medicine Nudge Unit, Philadelphia, Pennsylvania
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50
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Belli HM, Chokshi SK, Hegde R, Troxel AB, Blecker S, Testa PA, Anderman J, Wong C, Mann DM. Implementation of a Behavioral Economics Electronic Health Record (BE-EHR) Module to Reduce Overtreatment of Diabetes in Older Adults. J Gen Intern Med 2020; 35:3254-3261. [PMID: 32885374 PMCID: PMC7661670 DOI: 10.1007/s11606-020-06119-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Accepted: 08/06/2020] [Indexed: 01/17/2023]
Abstract
BACKGROUND Intensive glycemic control is of unclear benefit and carries increased risk for older adults with diabetes. The American Geriatrics Society's (AGS) Choosing Wisely (CW) guideline promotes less aggressive glycemic targets and reduction in pharmacologic therapy for older adults with type II diabetes. Meanwhile, behavioral economic (BE) approaches offer promise in influencing hard-to-change behavior, and previous studies have shown the benefits of using electronic health record (EHR) technology to encourage guideline adherence. OBJECTIVE This study aimed to develop and pilot test an intervention that leverages BE with EHR technology to promote appropriate diabetes management in older adults. DESIGN A pilot study within the New York University Langone Health (NYULH) EHR and Epic system to deliver BE-inspired nudges at five NYULH clinics at varying time points from July 12, 2018, through October 31, 2019. PARTICIPANTS Clinicians across five practices in the NYULH system whose patients were older adults (age 76 and older) with type II diabetes. INTERVENTIONS A BE-EHR module comprising six nudges was developed through a series of design workshops, interviews, user-testing sessions, and clinic visits. BE principles utilized in the nudges include framing, social norming, accountable justification, defaults, affirmation, and gamification. MAIN MEASURES Patient-level CW compliance. KEY RESULTS CW compliance increased 5.1% from a 16-week interval at baseline to a 16-week interval post intervention. From February 14 to June 5, 2018 (prior to the first nudge launch in Vanguard clinics), CW compliance for 1278 patients was mean (95% CI)-16.1% (14.1%, 18.1%). From July 3 to October 22, 2019 (after BE-EHR module launch at all five clinics), CW compliance for 680 patients was 21.2% (18.1%, 24.3%). CONCLUSIONS The BE-EHR module shows promise for promoting the AGS CW guideline and improving diabetes management in older adults. A randomized controlled trial will commence to test the effectiveness of the intervention across 66 NYULH clinics. NIH TRIAL REGISTRY NUMBER NCT03409523.
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Affiliation(s)
- Hayley M Belli
- Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY, USA.
| | - Sara K Chokshi
- Division of Healthcare Delivery Science, Department of Population Health, New York University School of Medicine, New York, NY, USA
| | | | - Andrea B Troxel
- Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY, USA
| | - Saul Blecker
- Division of Healthcare Delivery Science, Department of Population Health, New York University School of Medicine, New York, NY, USA.,Department of Medicine, New York University School of Medicine, New York, NY, USA
| | - Paul A Testa
- Medical Center Information Technology, NYU Langone Health, New York, NY, USA.,Department of Emergency Medicine, New York University School of Medicine, New York, NY, USA
| | - Judd Anderman
- Medical Center Information Technology, NYU Langone Health, New York, NY, USA
| | - Christina Wong
- Medical Center Information Technology, NYU Langone Health, New York, NY, USA
| | - Devin M Mann
- Division of Healthcare Delivery Science, Department of Population Health, New York University School of Medicine, New York, NY, USA.,Department of Medicine, New York University School of Medicine, New York, NY, USA.,Medical Center Information Technology, NYU Langone Health, New York, NY, USA
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