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Munroe ES, Weinstein J, Gershengorn HB, Karlic KJ, Seelye S, Sjoding MW, Valley TS, Prescott HC. Understanding How Clinicians Personalize Fluid and Vasopressor Decisions in Early Sepsis Management. JAMA Netw Open 2024; 7:e247480. [PMID: 38639934 PMCID: PMC11031682 DOI: 10.1001/jamanetworkopen.2024.7480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 02/21/2024] [Indexed: 04/20/2024] Open
Abstract
Importance Recent sepsis trials suggest that fluid-liberal vs fluid-restrictive resuscitation has similar outcomes. These trials used generalized approaches to resuscitation, and little is known about how clinicians personalize fluid and vasopressor administration in practice. Objective To understand how clinicians personalize decisions about resuscitation in practice. Design, Setting, and Participants This survey study of US clinicians in the Society of Critical Care Medicine membership roster was conducted from November 2022 to January 2023. Surveys contained 10 vignettes of patients with sepsis where pertinent clinical factors (eg, fluid received and volume status) were randomized. Respondents selected the next steps in management. Data analysis was conducted from February to September 2023. Exposure Online Qualtrics clinical vignette survey. Main Outcomes and Measures Using multivariable logistic regression, the associations of clinical factors with decisions about fluid administration, vasopressor initiation, and vasopressor route were tested. Results are presented as adjusted proportions with 95% CIs. Results Among 11 203 invited clinicians, 550 (4.9%; 261 men [47.5%] and 192 women [34.9%]; 173 with >15 years of practice [31.5%]) completed at least 1 vignette and were included. A majority were physicians (337 respondents [61.3%]) and critical care trained (369 respondents [67.1%]). Fluid volume already received by a patient was associated with resuscitation decisions. After 1 L of fluid, an adjusted 82.5% (95% CI, 80.2%-84.8%) of respondents prescribed additional fluid and an adjusted 55.0% (95% CI, 51.9%-58.1%) initiated vasopressors. After 5 L of fluid, an adjusted 17.5% (95% CI, 15.1%-19.9%) of respondents prescribed more fluid while an adjusted 92.7% (95% CI, 91.1%-94.3%) initiated vasopressors. More respondents prescribed fluid when the patient examination found dry vs wet (ie, overloaded) volume status (adjusted proportion, 66.9% [95% CI, 62.5%-71.2%] vs adjusted proportion, 26.5% [95% CI, 22.3%-30.6%]). Medical history, respiratory status, lactate trend, and acute kidney injury had small associations with fluid and vasopressor decisions. In 1023 of 1127 vignettes (90.8%) where the patient did not have central access, respondents were willing to start vasopressors through a peripheral intravenous catheter. In cases where patients were already receiving peripheral norepinephrine, respondents were more likely to place a central line at higher norepinephrine doses of 0.5 µg/kg/min (adjusted proportion, 78.0%; 95% CI, 74.7%-81.2%) vs 0.08 µg/kg/min (adjusted proportion, 25.2%; 95% CI, 21.8%-28.5%) and after 24 hours (adjusted proportion, 59.5%; 95% CI, 56.6%-62.5%) vs 8 hours (adjusted proportion, 47.1%; 95% CI, 44.0%-50.1%). Conclusions and Relevance These findings suggest that fluid volume received is the predominant factor associated with ongoing fluid and vasopressor decisions, outweighing many other clinical factors. Peripheral vasopressor use is common. Future studies aimed at personalizing resuscitation must account for fluid volumes and should incorporate specific tools to help clinicians personalize resuscitation.
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Affiliation(s)
- Elizabeth S. Munroe
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor
| | - Julien Weinstein
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Hayley B. Gershengorn
- Division of Pulmonary, Critical Care, and Sleep Medicine, University of Miami Miller School of Medicine, Miami, Florida
- Division of Critical Care Medicine, Albert Einstein College of Medicine, Bronx, New York
| | | | - Sarah Seelye
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Michael W. Sjoding
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor
| | - Thomas S. Valley
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Hallie C. Prescott
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
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Hechtman RK, Kipnis P, Cano J, Seelye S, Liu VX, Prescott HC. Heterogeneity of Benefit from Earlier Time-to-Antibiotics for Sepsis. Am J Respir Crit Care Med 2024; 209:852-860. [PMID: 38261986 PMCID: PMC10995570 DOI: 10.1164/rccm.202310-1800oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/23/2024] [Indexed: 01/25/2024] Open
Abstract
Rationale: Shorter time-to-antibiotics improves survival from sepsis, particularly among patients in shock. There may be other subgroups for whom faster antibiotics are particularly beneficial.Objectives: Identify patient characteristics associated with greater benefit from shorter time-to-antibiotics.Methods: Observational cohort study of patients hospitalized with community-onset sepsis at 173 hospitals and treated with antimicrobials within 12 hours. We used three approaches to evaluate heterogeneity of benefit from shorter time-to-antibiotics: 1) conditional average treatment effects of shorter (⩽3 h) versus longer (>3-12 h) time-to-antibiotics on 30-day mortality using multivariable Poisson regression; 2) causal forest to identify characteristics associated with greatest benefit from shorter time-to-antibiotics; and 3) logistic regression with time-to-antibiotics modeled as a spline.Measurements and Main Results: Among 273,255 patients with community-onset sepsis, 131,094 (48.0%) received antibiotics within 3 hours. In Poisson models, shorter time-to-antibiotics was associated with greater absolute mortality reduction among patients with metastatic cancer (5.0% [95% confidence interval; CI: 4.3-5.7] vs. 0.4% [95% CI: 0.2-0.6] for patients without cancer, P < 0.001); patients with shock (7.0% [95% CI: 5.8-8.2%] vs. 2.8% [95% CI: 2.7-3.5%] for patients without shock, P = 0.005); and patients with more acute organ dysfunctions (4.8% [95% CI: 3.9-5.6%] for three or more dysfunctions vs. 0.5% [95% CI: 0.3-0.8] for one dysfunction, P < 0.001). In causal forest, metastatic cancer and shock were associated with greatest benefit from shorter time-to-antibiotics. Spline analysis confirmed differential nonlinear associations of time-to-antibiotics with mortality in patients with metastatic cancer and shock.Conclusions: In patients with community-onset sepsis, the mortality benefit of shorter time-to-antibiotics varied by patient characteristics. These findings suggest that shorter time-to-antibiotics for sepsis is particularly important among patients with cancer and/or shock.
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Affiliation(s)
- Rachel K. Hechtman
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Patricia Kipnis
- Division of Research, Kaiser Permanente, Oakland, California; and
| | - Jennifer Cano
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Sarah Seelye
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente, Oakland, California; and
| | - Hallie C. Prescott
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
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Iwashyna TJ, Smith VA, Seelye S, Bohnert ASB, Boyko EJ, Hynes DM, Ioannou GN, Maciejewski ML, O'Hare AM, Viglianti EM, Berkowitz TS, Pura J, Womer J, Kamphuis LA, Monahan ML, Bowling CB. Self-Reported Everyday Functioning After COVID-19 Infection. JAMA Netw Open 2024; 7:e240869. [PMID: 38427352 PMCID: PMC10907923 DOI: 10.1001/jamanetworkopen.2024.0869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2024] Open
Abstract
Importance Changes in everyday functioning are crucial to assessing the long-term impact of COVID-19 infection. Objective To examine the impact of COVID-19 infection on everyday functioning 18 months after infection among veterans with and without histories of COVID-19 infection. Design, Setting, and Participants This cohort study used data from the US Veterans Affairs (VA) and included 186 veterans who had COVID-19 between October 2020 and April 2021 (ie, COVID-19 cohort) and 186 matched comparators who did not have documented COVID-19 infections (ie, control cohort). This match balanced the risk of COVID-19 based on 39 variables measured in the 24 months before infection or match, using principles of target trial emulation. Data were analyzed from December 2022 to December 2023. Exposure First documented COVID-19. Main Outcome and Measures The differences in self-reported everyday functioning 18 months after COVID-19 infection were estimated and compared with their matched comparators. Within-matched pair logistic and linear regressions assessed differences in outcomes and were weighted to account for sampling and nonresponse. Results Among the 186 matched pairs of participants, their weighted mean age was 60.4 (95% CI, 57.5 to 63.2) years among veterans in the COVID-19 cohort (weighted sample, 91 459 of 101 133 [90.4%] male; 30 611 [30.3%] Black or African American veterans; 65 196 [64.4%] White veterans) and 61.1 (95% CI, 57.8 to 64.4) years among their comparators in the control cohort (91 459 [90.4%] male; 24 576 [24.3%] Black or African American veterans; 70 157 [69.4%] White veterans). A high proportion of veterans in the COVID-19 cohort (weighted percentage, 44.9% [95% CI, 34.2% to 56.2%]) reported that they could do less than what they felt they could do at the beginning of 2020 compared with the control cohort (weighted percentage, 35.3%; [95% CI, 25.6% to 46.4%]; within-matched pair adjusted odds ratio [OR], 1.52 [95% CI, 0.79 to 2.91]). There was no association of documented COVID-19 infection with fatigue, substantial pain, limitations in either activities of daily living and instrumental activities of daily living, severely curtailed life-space mobility, employment, or mean health-related quality of life on a utility scale. Conclusions and Relevance In this cohort study of veterans with and without documented COVID-19, many reported a substantial loss of everyday functioning during the pandemic regardless of whether or not they had a documented infection with COVID-19. Future work with larger samples is needed to validate the estimated associations.
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Affiliation(s)
- Theodore J Iwashyna
- VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Department of Medicine, University of Michigan Medical School, Ann Arbor
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
- School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Valerie A Smith
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
- Department of Population Health Sciences, Duke University, Durham, North Carolina
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
| | - Amy S B Bohnert
- VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Departments of Anesthesiology, Epidemiology, and Psychiatry, University of Michigan Medical School, Ann Arbor
| | - Edward J Boyko
- Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington
- University of Washington, Seattle
| | - Denise M Hynes
- VA Portland Healthcare System, Center to Improve Veteran Involvement in Care, Portland, Oregon
- College of Health, and Center for Quantitative Life Sciences, Oregon State University, Corvallis
- School of Nursing, Oregon Health and Science University, Portland
| | - George N Ioannou
- University of Washington, Seattle
- VA Puget Sound Health Care System Hospital and Specialty Medicine Service and Seattle-Denver Center of Innovation for Veteran Centered and Value Driven Care, Seattle, Washington
| | - Matthew L Maciejewski
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
- School of Nursing, Oregon Health and Science University, Portland
| | - Ann M O'Hare
- University of Washington, Seattle
- VA Puget Sound Health Care System Hospital and Specialty Medicine Service and Seattle-Denver Center of Innovation for Veteran Centered and Value Driven Care, Seattle, Washington
| | - Elizabeth M Viglianti
- VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Department of Medicine, University of Michigan Medical School, Ann Arbor
| | - Theodore S Berkowitz
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
| | - John Pura
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
| | - James Womer
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Lee A Kamphuis
- VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
| | - Max L Monahan
- VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - C Barrett Bowling
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
- Durham Veterans Affairs Geriatric Research Education and Clinical Center, Durham Veterans Affairs Medical Center, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
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Iwashyna TJ, Seelye S, Berkowitz TS, Pura J, Bohnert ASB, Bowling CB, Boyko EJ, Hynes DM, Ioannou GN, Maciejewski ML, O’Hare AM, Viglianti EM, Womer J, Prescott HC, Smith VA. Late Mortality After COVID-19 Infection Among US Veterans vs Risk-Matched Comparators: A 2-Year Cohort Analysis. JAMA Intern Med 2023; 183:1111-1119. [PMID: 37603339 PMCID: PMC10442778 DOI: 10.1001/jamainternmed.2023.3587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 06/09/2023] [Indexed: 08/22/2023]
Abstract
Importance Despite growing evidence of persistent problems after acute COVID-19, how long the excess mortality risk associated with COVID-19 persists is unknown. Objective To measure the time course of differential mortality among Veterans who had a first-documented COVID-19 infection by separately assessing acute mortality from later mortality among matched groups with infected and uninfected individuals who survived and were uncensored at the start of each period. Design, Settings, and Participants This retrospective cohort study used prospectively collected health record data from Veterans Affairs hospitals across the US on Veterans who had COVID-19 between March 2020 and April 2021. Each individual was matched with up to 5 comparators who had not been infected with COVID-19 at the time of matching. This match balanced, on a month-by-month basis, the risk of developing COVID-19 using 37 variables measured in the 24 months before the date of the infection or match. A primary analysis censored comparators when they developed COVID-19 with inverse probability of censoring weighting in Cox regression. A secondary analysis did not censor. Data analyses were performed from April 2021 through June 2023. Exposure First-documented case of COVID-19 (SARS-CoV-2) infection. Main Outcome Measures Hazard ratios for all-cause mortality at clinically meaningful intervals after infection: 0 to 90, 91 to 180, 181 to 365, and 366 to 730 days. Results The study sample comprised 208 061 Veterans with first-documented COVID-19 infection (mean [SD] age, 60.5 (16.2) years; 21 936 (10.5) women; 47 645 [22.9] Black and 139 604 [67.1] White individuals) and 1 037 423 matched uninfected comparators with similar characteristics. Veterans with COVID-19 had an unadjusted mortality rate of 8.7% during the 2-year period after the initial infection compared with 4.1% among uninfected comparators, with censoring if the comparator later developed COVID-19-an adjusted hazard ratio (aHR) of 2.01 (95% CI, 1.98-2.04). The risk of excess death varied, being highest during days 0 to 90 after infection (aHR, 6.36; 95% CI, 6.20-6.51) and still elevated during days 91 to 180 (aHR, 1.18; 95% CI, 1.12-1.23). Those who survived COVID-19 had decreased mortality on days 181 to 365 (aHR, 0.92; 95% CI, 0.89-0.95) and 366 to 730 (aHR, 0.89; 95% CI, 0.85-0.92). These patterns were consistent across sensitivity analyses. Conclusion and Relevance The findings of this retrospective cohort study indicate that although overall 2-year mortality risk was worse among those infected with COVID-19, by day 180 after infection they had no excess mortality during the next 1.5 years.
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Affiliation(s)
- Theodore J. Iwashyna
- Veterans Affairs (VA) Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Department of Medicine, University of Michigan Medical School, Ann Arbor
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
- School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Sarah Seelye
- Veterans Affairs (VA) Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
| | - Theodore S. Berkowitz
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
| | - John Pura
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
| | - Amy S. B. Bohnert
- Veterans Affairs (VA) Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Departments of Anesthesiology and Psychiatry, University of Michigan Medical School, Ann Arbor
| | - C. Barrett Bowling
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
- Durham VA Geriatric Research Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
| | - Edward J. Boyko
- VA Puget Sound Health Care System Hospital and Specialty Medicine Service and Seattle-Denver Center of Innovation for Veteran Centered and Value Driven Care, Seattle, Washington
- Department of Medicine, University of Washington, Seattle
| | - Denise M. Hynes
- VA Center to Improve Veteran Involvement in Care, Portland, Oregon
- College of Public Health and Human Sciences and Center for Quantitative Life Sciences, Oregon State University, Corvallis
- School of Nursing, Oregon Health and Science University, Portland
| | - George N. Ioannou
- VA Puget Sound Health Care System Hospital and Specialty Medicine Service and Seattle-Denver Center of Innovation for Veteran Centered and Value Driven Care, Seattle, Washington
- Department of Medicine, University of Washington, Seattle
| | - Matthew L. Maciejewski
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
- Department of Population Health Sciences, Duke University, Durham, North Carolina
| | - Ann M. O’Hare
- VA Puget Sound Health Care System Hospital and Specialty Medicine Service and Seattle-Denver Center of Innovation for Veteran Centered and Value Driven Care, Seattle, Washington
- Department of Medicine, University of Washington, Seattle
| | - Elizabeth M. Viglianti
- Veterans Affairs (VA) Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Department of Medicine, University of Michigan Medical School, Ann Arbor
| | - James Womer
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Hallie C. Prescott
- Veterans Affairs (VA) Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, Michigan
- Department of Medicine, University of Michigan Medical School, Ann Arbor
| | - Valerie A. Smith
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Duke University, Durham, North Carolina
- Department of Population Health Sciences, Duke University, Durham, North Carolina
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Karlic KJ, Clouse TL, Hogan CK, Garland A, Seelye S, Sussman JB, Prescott HC. Comparison of Administrative versus Electronic Health Record-based Methods for Identifying Sepsis Hospitalizations. Ann Am Thorac Soc 2023; 20:1309-1315. [PMID: 37163757 DOI: 10.1513/annalsats.202302-105oc] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 05/10/2023] [Indexed: 05/12/2023] Open
Abstract
Rationale: Despite the importance of sepsis surveillance, no optimal approach for identifying sepsis hospitalizations exists. The Centers for Disease Control and Prevention Adult Sepsis Event Definition (CDC-ASE) is an electronic medical record-based algorithm that yields more stable estimates over time than diagnostic coding-based approaches but may still result in misclassification. Objectives: We sought to assess three approaches to identifying sepsis hospitalizations, including a modified CDC-ASE. Methods: This cross-sectional study included patients in the Veterans Affairs Ann Arbor Healthcare System admitted via the emergency department (February 2021 to February 2022) with at least one episode of acute organ dysfunction within 48 hours of emergency department presentation. Patients were assessed for community-onset sepsis using three methods: 1) explicit diagnosis codes, 2) the CDC-ASE, and 3) a modified CDC-ASE. The modified CDC-ASE required at least two systemic inflammatory response syndrome criteria instead of blood culture collection and had a more sensitive definition of respiratory dysfunction. Each method was compared with a reference standard of physician adjudication via medical record review. Patients were considered to have sepsis if they had at least one episode of acute organ dysfunction graded as "definitely" or "probably" infection related on physician review. Results: Of 821 eligible hospitalizations, 449 were selected for physician review. Of these, 98 (21.8%) were classified as sepsis by medical record review, 103 (22.9%) by the CDC-ASE, 132 (29.4%) by the modified CDC-ASE, and 37 (8.2%) by diagnostic codes. Accuracy was similar across the three methods of interest (80.6% for the CDC-ASE, 79.6% for the modified CDC-ADE, and 84.2% for diagnostic codes), but sensitivity and specificity varied. The CDC-ASE algorithm had sensitivity of 58.2% (95% confidence interval [CI], 47.2-68.1%) and specificity of 86.9% (95% CI, 82.9-90.2%). The modified CDC-ASE algorithm had greater sensitivity (69.4% [95% CI, 59.3-78.3%]) but lower specificity (81.8% [95% CI, 77.3-85.7%]). Diagnostic codes had lower sensitivity (32.7% [95% CI, 23.5-42.9%]) but greater specificity (98.6% [95% CI, 96.7-99.55%]). Conclusions: There are several approaches to identifying sepsis hospitalizations for surveillance that have acceptable accuracy. These approaches yield varying sensitivity and specificity, so investigators should carefully consider the test characteristics of each method before determining an appropriate method for their intended use.
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Affiliation(s)
- Kevin J Karlic
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Tori L Clouse
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Cainnear K Hogan
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Allan Garland
- Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Sarah Seelye
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Jeremy B Sussman
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Hallie C Prescott
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan; and
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Denstaedt SJ, Cano J, Wang XQ, Donnelly JP, Seelye S, Prescott HC. Blood count derangements after sepsis and association with post-hospital outcomes. Front Immunol 2023; 14:1133351. [PMID: 36936903 PMCID: PMC10018394 DOI: 10.3389/fimmu.2023.1133351] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/03/2023] [Indexed: 03/06/2023] Open
Abstract
Rationale Predicting long-term outcomes in sepsis survivors remains a difficult task. Persistent inflammation post-sepsis is associated with increased risk for rehospitalization and death. As surrogate markers of inflammation, complete blood count parameters measured at hospital discharge may have prognostic value for sepsis survivors. Objective To determine the incremental value of complete blood count parameters over clinical characteristics for predicting 90-day outcomes in sepsis survivors. Methods Electronic health record data was used to identify sepsis hospitalizations at United States Veterans Affairs hospitals with live discharge and relevant laboratory data (2013 to 2018). We measured the association of eight complete blood count parameters with 90-day outcomes (mortality, rehospitalization, cause-specific rehospitalizations) using multivariable logistic regression models. Measurements and main results We identified 155,988 eligible hospitalizations for sepsis. Anemia (93.6%, N=142,162) and lymphopenia (28.1%, N=29,365) were the most common blood count abnormalities at discharge. In multivariable models, all parameters were associated with the primary outcome of 90-day mortality or rehospitalization and improved model discrimination above clinical characteristics alone (likelihood ratio test, p<0.02 for all). A model including all eight parameters significantly improved discrimination (AUROC, 0.6929 v. 0.6756) and reduced calibration error for the primary outcome. Hemoglobin had the greatest prognostic separation with a 1.5 fold increased incidence of the primary outcome in the lowest quintile (7.2-8.9 g/dL) versus highest quintile (12.70-15.80 g/dL). Hemoglobin and neutrophil lymphocyte ratio provided the most added value in predicting the primary outcome and 90-day mortality alone, respectively. Absolute lymphocyte count added little value in predicting 90-day outcomes. Conclusions The incorporation of discharge complete blood count parameters into prognostic scoring systems could improve prediction of 90-day outcomes. Hemoglobin had the greatest prognostic value for the primary composite outcome of 90-day rehospitalization or mortality. Absolute lymphocyte count provided little added value in multivariable model comparisons, including for infection- or sepsis-related rehospitalization.
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Affiliation(s)
- Scott J. Denstaedt
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Jennifer Cano
- VA Center for Clinical Management Research, Ann Arbor, MI, United States
| | - Xiao Qing Wang
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States
| | - John P. Donnelly
- Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, MI, United States
| | - Hallie C. Prescott
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States
- VA Center for Clinical Management Research, Ann Arbor, MI, United States
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Becker NV, Seelye S, Chua KP, Echevarria K, Conti RM, Prescott HC. Dispensing of Ivermectin From Veterans Administration Pharmacies During the COVID-19 Pandemic. JAMA Netw Open 2023; 6:e2254859. [PMID: 36723943 PMCID: PMC9892958 DOI: 10.1001/jamanetworkopen.2022.54859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
This cohort study compares changes in ivermectin dispensing during the COVID-19 pandemic between the Veterans Administration (VA) and retail pharmacy settings and examines the association of the VA national formulary restriction with ivermectin dispensing.
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Affiliation(s)
- Nora V. Becker
- Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Kao-Ping Chua
- Department of Pediatrics, University of Michigan, Ann Arbor
| | - Kelly Echevarria
- Veterans Health Administration Pharmacy Benefits Management, San Antonio, Texas
| | - Rena M. Conti
- Questrom School of Business, Boston University, Boston, Massachusetts
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Prescott HC, Seelye S, Wang XQ, Hogan CK, Smith JT, Kipnis P, Barreda F, Donnelly JP, Pogue JM, Iwashyna TJ, Jones MM, Liu VX. Temporal Trends in Antimicrobial Prescribing During Hospitalization for Potential Infection and Sepsis. JAMA Intern Med 2022; 182:805-813. [PMID: 35759274 PMCID: PMC9237797 DOI: 10.1001/jamainternmed.2022.2291] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/28/2022] [Indexed: 12/19/2022]
Abstract
Importance Some experts have cautioned that national and health system emphasis on rapid administration of antimicrobials for sepsis may increase overall antimicrobial use even among patients without sepsis. Objective To assess whether temporal changes in antimicrobial timing for sepsis are associated with increasing antimicrobial use, days of therapy, or broadness of antimicrobial coverage among all hospitalized patients at risk for sepsis. Design, Setting, and Participants This is an observational cohort study of hospitalized patients at 152 hospitals in 2 health care systems during 2013 to 2018, admitted via the emergency department with 2 or more systemic inflammatory response syndrome (SIRS) criteria. Data analysis was performed from June 10, 2021, to March 22, 2022. Exposures Hospital-level temporal trends in time to first antimicrobial administration. Outcomes Antimicrobial outcomes included antimicrobial use, days of therapy, and broadness of antibacterial coverage. Clinical outcomes included in-hospital mortality, 30-day mortality, length of hospitalization, and new multidrug-resistant (MDR) organism culture positivity. Results Among 1 559 523 patients admitted to the hospital via the emergency department with 2 or more SIRS criteria (1 269 998 male patients [81.4%]; median [IQR] age, 67 [59-77] years), 273 255 (17.5%) met objective criteria for sepsis. In multivariable models adjusted for patient characteristics, the adjusted median (IQR) time to first antimicrobial administration to patients with sepsis decreased by 37 minutes, from 4.7 (4.1-5.3) hours in 2013 to 3.9 (3.6-4.4) hours in 2018, although the slope of decrease varied across hospitals. During the same period, antimicrobial use within 48 hours, days of antimicrobial therapy, and receipt of broad-spectrum coverage decreased among the broader cohort of patients with SIRS. In-hospital mortality, 30-day mortality, length of hospitalization, new MDR culture positivity, and new MDR blood culture positivity decreased over the study period among both patients with sepsis and those with SIRS. When examining hospital-specific trends, decreases in antimicrobial use, days of therapy, and broadness of antibacterial coverage for patients with SIRS did not differ by hospital antimicrobial timing trend for sepsis. Overall, there was no evidence that accelerating antimicrobial timing for sepsis was associated with increasing antimicrobial use or impaired antimicrobial stewardship. Conclusions and Relevance In this multihospital cohort study, the time to first antimicrobial for sepsis decreased over time, but this trend was not associated with increasing antimicrobial use, days of therapy, or broadness of antimicrobial coverage among the broader population at-risk for sepsis, which suggests that shortening the time to antibiotics for sepsis is feasible without leading to indiscriminate antimicrobial use.
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Affiliation(s)
- Hallie C. Prescott
- Department of Internal Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Xiao Qing Wang
- Department of Internal Medicine, University of Michigan, Ann Arbor
| | | | - Joshua T. Smith
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Patricia Kipnis
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Fernando Barreda
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - John P. Donnelly
- Department of Learning Health Sciences, University of Michigan, Ann Arbor
| | - Jason M. Pogue
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor
| | - Theodore J. Iwashyna
- Department of Internal Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Makoto M. Jones
- Salt Lake City VA Healthcare System, Salt Lake City, Utah
- Department of Medicine, University of Utah, Salt Lake City
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente Northern California, Oakland
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9
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Viglianti EM, Carlton EF, McPeake J, Wang XQ, Seelye S, Iwashyna TJ. Acquisition of new medical devices among the persistently critically ill: A retrospective cohort study in the Veterans Affairs. Medicine (Baltimore) 2022; 101:e29821. [PMID: 35801748 PMCID: PMC9259166 DOI: 10.1097/md.0000000000029821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/20/2022] [Accepted: 05/31/2022] [Indexed: 01/04/2023] Open
Abstract
Patients who develop persistent critical illness remain in the ICU predominately because they develop new late-onset organ failure(s), which may render them at risk of acquiring a new medical device. The epidemiology and short-term outcomes of patients with persistent critical illness who acquire a new medical device are unknown. We retrospectively studied a cohort admitted to the Veterans Affairs (VA) ICUs from 2014 to 2019. Persistent critical illness was defined as an ICU length of stay of at least 14 days. Receipt of new devices was defined as acquisition of a new tracheostomy, feeding tube (including gastrostomy and jejunostomy tubes), implantable cardiac device, or ostomy. Logistic regression models were fit to identify patient factors associated with the acquisition of each new medical device. Among hospitalized survivors, 90-day posthospitalization discharge location and mortality were identified. From 2014 to 2019, there were 13,184 ICU hospitalizations in the VA which developed persistent critical illness. In total, 30.4% of patients (N = 3998/13,184) acquired at least 1 medical device during their persistent critical illness period. Patients with an initial higher severity of illness and prolonged hospital stay preICU admission had higher odds of acquiring each medical device. Among patients who survived their hospitalization, discharge location and mortality did not significantly differ among those who acquired a new medical device as compared to those who did not. Less than one-third of patients with persistent critical illness acquire a new medical device and no significant difference in short-term outcomes was identified. Future work is needed to understand if the acquisition of new medical devices is contributing to the development of persistent critical illness.
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Affiliation(s)
- Elizabeth M. Viglianti
- Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA
- Veterans Affairs Center for Clinical Management Research, HSR&D Center for Innovation, Ann Arbor, MI, USA
| | - Erin F. Carlton
- Department of Pediatrics Division of Pediatric Critical Care, University of Michigan, Ann Arbor, MI, USA
- Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan, Ann Arbor, MI, USA
| | - Joanne McPeake
- University of Glasgow, School of Medicine, Dentistry and Nursing, Scotland, UK
- NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, Intensive Care Unit, Scotland, UK
| | - Xiao Qing Wang
- Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA
| | - Sarah Seelye
- Veterans Affairs Center for Clinical Management Research, HSR&D Center for Innovation, Ann Arbor, MI, USA
| | - Theodore J. Iwashyna
- Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA
- Veterans Affairs Center for Clinical Management Research, HSR&D Center for Innovation, Ann Arbor, MI, USA
- Institute for Social Research, Ann Arbor, MI, USA
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10
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Valbuena VSM, Seelye S, Sjoding MW, Valley TS, Dickson RP, Gay SE, Claar D, Prescott HC, Iwashyna TJ. Racial bias and reproducibility in pulse oximetry among medical and surgical inpatients in general care in the Veterans Health Administration 2013-19: multicenter, retrospective cohort study. BMJ 2022; 378:e069775. [PMID: 35793817 PMCID: PMC9254870 DOI: 10.1136/bmj-2021-069775] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/23/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVES To evaluate measurement discrepancies by race between pulse oximetry and arterial oxygen saturation (as measured in arterial blood gas) among inpatients not in intensive care. DESIGN Multicenter, retrospective cohort study using electronic medical records from general care medical and surgical inpatients. SETTING Veteran Health Administration, a national and racially diverse integrated health system in the United States, from 2013 to 2019. PARTICIPANTS Adult inpatients in general care (medical and surgical), in Veteran Health Administration medical centers. MAIN OUTCOMES MEASURES Occult hypoxemia (defined as arterial blood oxygen saturation (SaO2) of <88% despite a pulse oximetry (SpO2) reading of ≥92%), and whether rates of occult hypoxemia varied by race and ethnic origin. RESULTS A total of 30 039 pairs of SpO2-SaO2 readings made within 10 minutes of each other were identified during the study. These pairs were predominantly among non-Hispanic white (21 918 (73.0%)) patients; non-Hispanic black patients and Hispanic or Latino patients accounted for 6498 (21.6%) and 1623 (5.4%) pairs in the sample, respectively. Among SpO2 values greater or equal to 92%, unadjusted probabilities of occult hypoxemia were 15.6% (95% confidence interval 15.0% to 16.1%) in white patients, 19.6% (18.6% to 20.6%) in black patients (P<0.001 v white patients, with similar P values in adjusted models), and 16.2% (14.4% to 18.1%) in Hispanic or Latino patients (P=0.53 v white patients, P<0.05 in adjusted models). This result was consistent in SpO2-SaO2 pairs restricted to occur within 5 minutes and 2 minutes. In white patients, an initial SpO2-SaO2 pair with little difference in saturation was associated with a 2.7% (95% confidence interval -0.1% to 5.5%) probability of SaO2 <88% on a later paired SpO2-SaO2 reading showing an SpO2 of 92%, but black patients had a higher probability (12.9% (-3.3% to 29.0%)). CONCLUSIONS In general care inpatient settings across the Veterans Health Administration where paired readings of arterial blood gas (SaO2) and pulse oximetry (SpO2) were obtained, black patients had higher odds than white patients of having occult hypoxemia noted on arterial blood gas but not detected by pulse oximetry. This difference could limit access to supplemental oxygen and other more intensive support and treatments for black patients.
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Affiliation(s)
- Valeria S M Valbuena
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA
- National Clinician Scholars Program, University of Michigan, Ann Arbor, MI, USA
| | - Sarah Seelye
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA
| | - Michael W Sjoding
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Thomas S Valley
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Robert P Dickson
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Steven E Gay
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Dru Claar
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Hallie C Prescott
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Theodore J Iwashyna
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA
- National Clinician Scholars Program, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
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11
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Vincent BM, Molling D, Escobar GJ, Hofer TP, Iwashyna TJ, Liu VX, Rosen AK, Ryan AM, Seelye S, Wiitala WL, Prescott HC. Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System. Med Care 2021; 59:1090-1098. [PMID: 34629424 PMCID: PMC8802232 DOI: 10.1097/mlr.0000000000001645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings. OBJECTIVE The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality. RESEARCH DESIGN Observational cohort study with hospital-specific template matching assessment. For each VA hospital, the 30-day mortality of a representative subset of hospitalizations was compared with the pooled mortality from matched hospitalizations at a set of comparison VA hospitals treating sufficiently similar patients. The simulation was used to determine power to detect greater-than-expected mortality. SUBJECTS A total of 556,266 hospitalizations at 122 VA hospitals in 2017. MEASURES A number of comparison hospitals identified per hospital; 30-day mortality. RESULTS Each hospital had a median of 38 comparison hospitals (interquartile range: 33, 44) identified, and 116 (95.1%) had at least 20 comparison hospitals. In total, 8 hospitals (6.6%) had a significantly lower 30-day mortality than their benchmark, 5 hospitals (4.1%) had a significantly higher 30-day mortality, and the remaining 109 hospitals (89.3%) were similar to their benchmark. Power to detect a standardized mortality ratio of 2.0 ranged from 72.5% to 79.4% for a hospital with the fewest (6) versus most (64) comparison hospitals. CONCLUSIONS Hospital-specific template matching may be feasible for assessing hospital performance in the diverse VA health care system, but further refinements are needed to optimize the approach before operational use. Our findings are likely applicable to other large and diverse multihospital systems.
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Affiliation(s)
| | - Daniel Molling
- VA Center for Clinical Management Research, Ann Arbor, MI
| | - Gabriel J. Escobar
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Timothy P. Hofer
- VA Center for Clinical Management Research, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI
| | - Theodore J. Iwashyna
- VA Center for Clinical Management Research, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI
- Survey Research Center, Institute for Social Research, Ann Arbor, MI
| | - Vincent X Liu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Amy K. Rosen
- VA Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA
| | - Andrew M. Ryan
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, MI
| | | | - Hallie C. Prescott
- VA Center for Clinical Management Research, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI
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12
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Wang XQ, Iwashyna T, Prescott H, Valbuena V, Seelye S. Pulse oximetry and supplemental oxygen use in nationwide Veterans Health Administration hospitals, 2013-2017: a Veterans Affairs Patient Database validation study. BMJ Open 2021; 11:e051978. [PMID: 34625416 PMCID: PMC8504347 DOI: 10.1136/bmjopen-2021-051978] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVE Extraction and standardisation of pulse oximetry and supplemental oxygen data from electronic health records has the potential to improve risk-adjustment, quality assessment and prognostication. We develop an approach to standardisation and report on its use for benchmarking purposes. MATERIALS AND METHODS Using electronic health record data from the nationwide Veteran's Affairs healthcare system (2013-2017), we extracted, standardised and validated pulse oximetry and supplemental oxygen data for 2 765 446 hospitalisations in the Veteran's Affairs Patient Database (VAPD) cohort study. We assessed face, concurrent and predictive validities using the following approaches, respectively: (1) evaluating the stability of patients' pulse oximetry values during a 24-hour period, (2) testing for greater amounts of supplemental oxygen use in patients likely to need oxygen therapy and (3) examining the association between supplemental oxygen and subsequent mortality. RESULTS We found that 2 700 922 (98%) hospitalisations had at least one pulse oximetry reading, and 864 605 (31%) hospitalisations received oxygen therapy. Patients monitored by pulse oximetry had a reading on average every 6 hours (median 4; IQR 3-7). Patients on supplemental oxygen were older, white and male compared with patients not receiving oxygen therapy (p<0.001) and were more likely to have diagnoses of heart failure and chronic pulmonary diseases (p<0.001). The amount of supplemental oxygen for patients with at least three consecutive values recorded during a 24-hour period fluctuated by median 2 L/min (IQR: 2-3), and 81% of such triplets showed the same level of oxygen receipt. CONCLUSION Our approach to standardising pulse oximetry and supplemental oxygen data shows face, concurrent and predictive validities as the following: supplemental oxygen clusters in the range consistent with hospital wall-dispensed oxygen supplies (face validity); there are greater amounts of supplemental oxygen for certain clinical conditions (concurrent validity) and there is an association of supplemental oxygen with in-hospital and postdischarge mortality (predictive validity).
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Affiliation(s)
- Xiao Qing Wang
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Theodore Iwashyna
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
- Ann Arbor VA Medical Center, Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan, USA
| | - Hallie Prescott
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
- Ann Arbor VA Medical Center, Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan, USA
| | - Valeria Valbuena
- Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA
| | - Sarah Seelye
- Ann Arbor VA Medical Center, Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan, USA
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13
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Wayne MT, Seelye S, Molling D, Wang XQ, Donnelly JP, Hogan CK, Jones MM, Iwashyna TJ, Liu VX, Prescott HC. Temporal Trends and Hospital Variation in Time-to-Antibiotics Among Veterans Hospitalized With Sepsis. JAMA Netw Open 2021; 4:e2123950. [PMID: 34491351 PMCID: PMC8424480 DOI: 10.1001/jamanetworkopen.2021.23950] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/01/2021] [Indexed: 12/19/2022] Open
Abstract
Importance It is unclear whether antimicrobial timing for sepsis has changed outside of performance incentive initiatives. Objective To examine temporal trends and variation in time-to-antibiotics for sepsis in the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants This observational cohort study included 130 VA hospitals from 2013 to 2018. Participants included all patients admitted to the hospital via the emergency department with sepsis from 2013 to 2018, using a definition adapted from the Centers for Disease Control and Prevention Adult Sepsis Event definition, which requires evidence of suspected infection, acute organ dysfunction, and systemic antimicrobial therapy within 12 hours of presentation. Data were analyzed from October 6, 2020, to July 1, 2021. Exposures Time from presentation to antibiotic administration. Main Outcomes and Measures The main outcome was differences in time-to-antibiotics across study periods, hospitals, and patient subgroups defined by presenting temperature and blood pressure. Temporal trends in time-to-antibiotics were measured overall and by subgroups. Hospital-level variation in time-to-antibiotics was quantified after adjusting for differences in patient characteristics using multilevel linear regression models. Results A total of 111 385 hospitalizations for sepsis were identified, including 107 547 men (96.6%) men and 3838 women (3.4%) with a median (interquartile range [IQR]) age of 68 (62-77) years. A total of 7574 patients (6.8%) died in the hospital, and 13 855 patients (12.4%) died within 30 days. Median (IQR) time-to-antibiotics was 3.9 (2.4-6.5) hours but differed by presenting characteristics. Unadjusted median (IQR) time-to-antibiotics decreased over time, from 4.5 (2.7-7.1) hours during 2013 to 2014 to 3.5 (2.2-5.9) hours during 2017 to 2018 (P < .001). In multilevel models adjusted for patient characteristics, median time-to-antibiotics declined by 9.0 (95% CI, 8.8-9.2) minutes per calendar year. Temporal trends in time-to-antibiotics were similar across patient subgroups, but hospitals with faster baseline time-to-antibiotics had less change over time, with hospitals in the slowest tertile decreasing time-to-antibiotics by 16.6 minutes (23.1%) per year, while hospitals in the fastest tertile decreased time-to-antibiotics by 7.2 minutes (13.1%) per year. In the most recent years (2017-2018), median time-to-antibiotics ranged from 3.1 to 6.7 hours across hospitals (after adjustment for patient characteristics), 6.8% of variation in time-to-antibiotics was explained at the hospital level, and odds of receiving antibiotics within 3 hours increased by 65% (95% CI, 56%-77%) for the median patient if moving to a hospital with faster time-to-antibiotics. Conclusions and Relevance This cohort study across nationwide VA hospitals found that time-to-antibiotics for sepsis has declined over time. However, there remains significant variability in time-to-antibiotics not explained by patient characteristics, suggesting potential unwarranted practice variation in sepsis treatment. Efforts to further accelerate time-to-antibiotics must be weighed against risks of overtreatment.
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Affiliation(s)
- Max T. Wayne
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Daniel Molling
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Xiao Qing Wang
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - John P. Donnelly
- Institute for Healthcare Policy & Innovation, University of Michigan, Ann Arbor
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
| | | | - Makoto M. Jones
- Salt Lake City VA Healthcare System, Salt Lake City, Utah
- Department of Medicine, University of Utah, Salt Lake City
| | - Theodore J. Iwashyna
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Hallie C. Prescott
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
- VA Center for Clinical Management Research, Ann Arbor, Michigan
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14
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Wayne MT, Molling D, Wang XQ, Hogan CK, Seelye S, Liu VX, Prescott HC. Measurement of Sepsis in a National Cohort Using Three Different Methods to Define Baseline Organ Function. Ann Am Thorac Soc 2021; 18:648-655. [PMID: 33476245 PMCID: PMC8008999 DOI: 10.1513/annalsats.202009-1130oc] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 01/20/2021] [Indexed: 12/21/2022] Open
Abstract
Rationale: In 2017, the U.S. Centers for Disease Control and Prevention (CDC) developed a new surveillance definition of sepsis, the adult sepsis event (ASE), to better track sepsis epidemiology. The ASE requires evidence of acute organ dysfunction and defines baseline organ function pragmatically as the best in-hospital value. This approach may undercount sepsis if new organ dysfunction does not resolve by discharge.Objectives: To understand how sepsis identification and outcomes differ when using the best laboratory values during hospitalization versus methods that use historical lookbacks to define baseline organ function.Methods: We identified all patients hospitalized at 138 Veterans Affairs hospitals (2013-2018) admitted via the emergency department with two or more systemic inflammatory response criteria, were treated with antibiotics within 48 hours (i.e., had potential infection), and completed 4+ days of antibiotics (i.e., had suspected infection). We considered the following three approaches to defining baseline renal, hematologic, and liver function: the best values during hospitalization (as in the Centers for Disease Control and Prevention's ASE), the best values during hospitalization plus the prior 90 days (3-mo baseline), and the best values during hospitalization plus the prior 180 days (6-mo baseline). We determined how many patients met the criteria for sepsis by each approach, and then compared characteristics and outcomes of sepsis hospitalizations between the three approaches.Results: Among 608,128 hospitalizations with potential infection, 72.1%, 68.5%, and 58.4% had creatinine, platelet, and total bilirubin measured, respectively, in the prior 3 months. A total of 86.0%, 82.6%, and 74.8%, respectively, had these labs in the prior 6 months. Using the hospital baseline, 100,568 hospitalizations met criteria for community-acquired sepsis. By contrast, 111,983 and 117,435 met criteria for sepsis using the 3- and 6-month baselines, for a relative increase of 11% and 17%, respectively. Patient characteristics were similar across the three approaches. In-hospital mortality was 7.2%, 7.0%, and 6.8% for sepsis hospitalizations identified using the hospital, 3-month baseline, and 6-month baseline. The 30-day mortality was 12.5%, 12.7%, and 12.5%, respectively.Conclusions: Among veterans hospitalized with potential infection, the majority had laboratory values in the prior 6 months. Using 3- and 6-month lookbacks to define baseline organ function resulted in an 11% and 17% relative increase, respectively, in the number of sepsis hospitalizations identified.
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Affiliation(s)
- Max T. Wayne
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Daniel Molling
- VA Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Xiao Qing Wang
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- VA Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Cainnear K. Hogan
- VA Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, Michigan; and
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Hallie C. Prescott
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- VA Center for Clinical Management Research, Ann Arbor, Michigan; and
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15
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Iwashyna TJ, Ma C, Wang XQ, Seelye S, Zhu J, Waljee AK. Variation in model performance by data cleanliness and classification methods in the prediction of 30-day ICU mortality, a US nationwide retrospective cohort and simulation study. BMJ Open 2020; 10:e041421. [PMID: 33268427 PMCID: PMC7713192 DOI: 10.1136/bmjopen-2020-041421] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE There has been a proliferation of approaches to statistical methods and missing data imputation as electronic health records become more plentiful; however, the relative performance on real-world problems is unclear. MATERIALS AND METHODS Using 355 823 intensive care unit (ICU) hospitalisations at over 100 hospitals in the nationwide Veterans Health Administration system (2014-2017), we systematically varied three approaches: how we extracted and cleaned physiologic variables; how we handled missing data (using mean value imputation, random forest, extremely randomised trees (extra-trees regression), ridge regression, normal value imputation and case-wise deletion) and how we computed risk (using logistic regression, random forest and neural networks). We applied these approaches in a 70% development sample and tested the results in an independent 30% testing sample. Area under the receiver operating characteristic curve (AUROC) was used to quantify model discrimination. RESULTS In 355 823 ICU stays, there were 34 867 deaths (9.8%) within 30 days of admission. The highest AUROCs obtained for each primary classification method were very similar: 0.83 (95% CI 0.83 to 0.83) to 0.85 (95% CI 0.84 to 0.85). Likewise, there was relatively little variation within classification method by the missing value imputation method used-except when casewise deletion was applied for missing data. CONCLUSION Variation in discrimination was seen as a function of data cleanliness, with logistic regression suffering the most loss of discrimination in the least clean data. Losses in discrimination were not present in random forest and neural networks even in naively extracted data. Data from a large nationwide health system revealed interactions between missing data imputation techniques, data cleanliness and classification methods for predicting 30-day mortality.
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Affiliation(s)
- Theodore J Iwashyna
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA
- Institute for Healthcare Policy and Innovation, University ofMichigan, Ann Arbor, Michigan, USA
- Michigan Integrated Center for Health Analytics and MedicalPrediction (MiCHAMP), Ann Arbor, Michigan, USA
| | - Cheng Ma
- Department of Statistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Xiao Qing Wang
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Sarah Seelye
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA
| | - Ji Zhu
- Department of Statistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Akbar K Waljee
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA
- Institute for Healthcare Policy and Innovation, University ofMichigan, Ann Arbor, Michigan, USA
- Michigan Integrated Center for Health Analytics and MedicalPrediction (MiCHAMP), Ann Arbor, Michigan, USA
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Viglianti EM, Bagshaw SM, Bellomo R, McPeake J, Molling DJ, Wang XQ, Seelye S, Iwashyna TJ. Late Vasopressor Administration in Patients in the ICU: A Retrospective Cohort Study. Chest 2020; 158:571-578. [PMID: 32278780 PMCID: PMC7417379 DOI: 10.1016/j.chest.2020.02.071] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 01/31/2020] [Accepted: 02/16/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Little is known about the prevalence, predictors, and outcomes of late vasopressor administration which evolves after admission to the ICU. RESEARCH QUESTION What is the epidemiology of late vasopressor administration in the ICU? STUDY DESIGN AND METHODS We retrospectively studied a cohort of veterans admitted to the Veterans Administration ICUs for ≥ 4 days from 2014 to 2017. The timing of vasopressor administration was categorized as early (only within the initial 3 days), late (on day 4 or later and none on day 3), and continuous (within the initial 2 days through at least day 4). Regressions were performed to identify patient factors associated with late vasopressor administration and the timing of vasopressor administration with posthospitalization discharge mortality. RESULTS Among the 62,206 hospitalizations with at least 4 ICU days, late vasopressor administration occurred in 5.5% (3,429 of 62,206). Patients with more comorbidities (adjusted OR [aOR], 1.02 per van Walraven point; 95% CI, 1.02-1.03) and worse severity of illness on admission (aOR, 1.01 per percentage point risk of death; 95% CI, 1.01-1.02) were more likely to receive late vasopressor therapy. Nearly 50% of patients started a new antibiotic within 24 h of receiving late vasopressor therapy. One-year mortality after survival to discharge was higher for patients with continuous (adjusted hazard ratio [aHR], 1.48; 95% CI, 1.33-1.65) and late vasopressor administration (aHR, 1.26; 95% CI, 1.15-1.38) compared with only early vasopressor administration. INTERPRETATION Late vasopressor administration was modestly associated with comorbidities and admission illness severity. One-year mortality was higher among those who received late vasopressor administration compared with only early vasopressor administration. Research to understand optimization of late vasopressor therapy administration may improve long-term mortality.
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Affiliation(s)
- Elizabeth M Viglianti
- Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI.
| | - Sean M Bagshaw
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
| | - Rinaldo Bellomo
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Department of Intensive Care, Alfred Hospital, Melbourne, VIC, Australia
| | - Joanne McPeake
- School of Medicine, Dentistry and Nursing, University of Glasgow, Glasgow, Scotland; Intensive Care Unit, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, Glasgow, Scotland
| | - Daniel J Molling
- HSR&D Center for Innovation, Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI
| | - Xiao Qing Wang
- Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI
| | - Sarah Seelye
- HSR&D Center for Innovation, Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI
| | - Theodore J Iwashyna
- Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI; HSR&D Center for Innovation, Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI; Institute for Social Research, Ann Arbor, MI
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Molling D, Vincent BM, Wiitala WL, Escobar GJ, Hofer TP, Liu VX, Rosen AK, Ryan AM, Seelye S, Prescott HC. Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system. Medicine (Baltimore) 2020; 99:e20385. [PMID: 32541458 PMCID: PMC7302661 DOI: 10.1097/md.0000000000020385] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Template matching is a proposed approach for hospital benchmarking, which measures performance based on matching a subset of comparable patient hospitalizations from each hospital. We assessed the ability to create the required matched samples and thus the feasibility of template matching to benchmark hospital performance in a diverse healthcare system.Nationwide Veterans Affairs (VA) hospitals, 2017.Observational cohort study.We used administrative and clinical data from 668,592 hospitalizations at 134 VA hospitals in 2017. A standardized template of 300 hospitalizations was selected, and then 300 hospitalizations were matched to the template from each hospital.There was substantial case-mix variation across VA hospitals, which persisted after excluding small hospitals, hospitals with primarily psychiatric admissions, and hospitalizations for rare diagnoses. Median age ranged from 57 to 75 years across hospitals; percent surgical admissions ranged from 0.0% to 21.0%; percent of admissions through the emergency department, 0.1% to 98.7%; and percent Hispanic patients, 0.2% to 93.3%. Characteristics for which there was substantial variation across hospitals could not be balanced with any matching algorithm tested. Although most other variables could be balanced, we were unable to identify a matching algorithm that balanced more than ∼20 variables simultaneously.We were unable to identify a template matching approach that could balance hospitals on all measured characteristics potentially important to benchmarking. Given the magnitude of case-mix variation across VA hospitals, a single template is likely not feasible for general hospital benchmarking.
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Affiliation(s)
- Daniel Molling
- VA Center for Clinical Management Research, Ann Arbor, MI
| | | | | | - Gabriel J. Escobar
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Timothy P. Hofer
- VA Center for Clinical Management Research, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Amy K. Rosen
- VA Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA
| | - Andrew M. Ryan
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Sarah Seelye
- VA Center for Clinical Management Research, Ann Arbor, MI
| | - Hallie C. Prescott
- VA Center for Clinical Management Research, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan
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Burgard SA, Lin KYP, Segal BD, Elliott MR, Seelye S. Stability and Change in Health Behavior Profiles of U.S. Adults. J Gerontol B Psychol Sci Soc Sci 2020; 75:674-683. [PMID: 32059056 DOI: 10.1093/geronb/gby088] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVES While understanding of complex within-person clustering of health behaviors into meaningful profiles of risk is growing, we still know little about whether and how U.S. adults transition from one profile to another as they age. This study assesses patterns of stability and change in profiles of tobacco and alcohol use and body mass index (BMI). METHOD A nationally representative cohort of U.S. adults 25 years and older was interviewed up to 5 times between 1986 and 2011. Latent transition analysis (LTA) models characterized the most common profiles, patterning of transitions across profiles over follow-up, and assessed whether some were associated with higher mortality risk. RESULTS We identified 5 profiles: "health promoting" with normal BMI and moderate alcohol consumption; "overweight"; "current smokers"; "obese"; and "nondrinkers". Profile membership was largely stable, with the most common transitions to death or weight gain. "Obese" was the most stable profile, while "smokers" were most likely to transition to another profile. Mortality was most frequent in the "obese" and "nondrinker" profiles. DISCUSSION Stability was more common than transition, suggesting that adults sort into health behavior profiles relatively early. Women and men were differently distributed across profiles at baseline, but showed broad similarity in transitions.
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Affiliation(s)
| | | | - Brian D Segal
- Department of Biostatistics, University of Michigan, Ann Arbor
| | | | - Sarah Seelye
- Population Studies Center, University of Michigan, Ann Arbor
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Abstract
Changes in the labor market and employment contracts over the past several decades and a recent global recession have increased the salience of perceived job insecurity as a risk factor for poor mental health. We use 25 years of prospective data from the Americans' Changing Lives study to examine long-term histories of perceived job insecurity and their link to psychological distress. We build on the prior literature by using a much longer window of exposure and accounting for involuntary job losses over the lengthy observation period. We find that persistent perceived job insecurity is strongly and significantly associated with greater psychological distress among U.S. workers in the latter part of their careers. Moreover, considering histories of exposure reveals more nuance in the sociodemographic characteristics and employment interruptions that predict persistent or intermittent insecurity and that identify contemporary older workers at particular risk.
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