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Nair D, Schildcrout JS, Shi Y, Trochez R, Nwosu S, Bell SP, Mixon AS, Welch SA, Goggins K, Bachmann JM, Vasilevskis EE, Cavanaugh KL, Rothman RL, Kripalani SB. Patient-reported predictors of postdischarge mortality after cardiac hospitalization. J Hosp Med 2024. [PMID: 38560772 DOI: 10.1002/jhm.13336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 03/07/2024] [Accepted: 03/09/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Adults hospitalized for cardiovascular events are at high risk for postdischarge mortality. Screening of psychosocial risk is prioritized by the Joint Commission. We tested whether key patient-reported psychosocial and behavioral measures could predict posthospitalization mortality in a cohort of adults hospitalized for a cardiovascular event. METHODS We conducted a prospective cohort study to test the prognostic utility of validated patient-reported measures, including health literacy, social support, health behaviors and disease management, and socioeconomic status. Cox survival analyses of mortality were conducted over a median of 3.5 years. RESULTS Among 2977 adults hospitalized for either acute coronary syndrome or acute decompensated heart failure, the mean age was 53 years, and 60% were male. After adjusting for demographic, clinical, and other psychosocial factors, mortality risk was greatest among patients who reported being unemployed (hazard ratio [HR]: 1.99, 95% confidence interval [CI]): 1.30-3.06), retired (HR: 2.14, 95% CI: 1.60-2.87), or unable to work due to disability (HR: 2.36, 95% CI: 1.73-3.21), as compared to those who were employed. Patient-reported perceived health competence (PHCS-2) and exercise frequency were also associated with mortality risk after adjusting for all other variables (HR: 0.86, 95% CI: 0.73-1.00 per four-point increase in PHCS-2; HR: 0.86, 95% CI: 0.77-0.96 per 3-day increase in exercise frequency, respectively). CONCLUSIONS Patient-reported measures of employment status, perceived health competence, and exercise frequency independently predict mortality after a cardiac hospitalization. Incorporating these brief, valid measures into hospital-based screening may help with prognostication and targeting patients for resources during post-discharge transitions of care.
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Affiliation(s)
- Devika Nair
- Department of Medicine, Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Health Services Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jonathan S Schildcrout
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ricardo Trochez
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sam Nwosu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Susan P Bell
- Department of Medicine, Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Amanda S Mixon
- Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Veterans Affairs, Geriatric Research Education and Clinical Center (GRECC), Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - Sarah A Welch
- Department of Veterans Affairs, Geriatric Research Education and Clinical Center (GRECC), Tennessee Valley Healthcare System, Nashville, Tennessee, USA
- Department of Physical Medicine and Rehabilitation, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kathryn Goggins
- Vanderbilt Center for Health Services Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Justin M Bachmann
- Department of Medicine, Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | | | - Kerri L Cavanaugh
- Department of Medicine, Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Health Services Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Russell L Rothman
- Institute of Medicine and Public Health, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sunil B Kripalani
- Vanderbilt Center for Health Services Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Center for Clinical Quality and Implementation Research, VUMC, Nashville, Tennessee, USA
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Schario ME, Pronovost PJ, Runnels P, Corder-Palko T, Carson B, Szubski M. A Path to Risk: Critical Elements of a Structured Approach. Popul Health Manag 2024; 27:49-54. [PMID: 38324750 DOI: 10.1089/pop.2023.0197] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
Value-based care arrangements have been the cornerstone of accountable care for decades. Risk arrangements with government and commercial insurance plans are ubiquitous, with most contracts focusing on upside risk only, meaning payers reward providers for good performance without punishing them for poor performance on quality and cost. However, payers are increasingly moving into downside risk arrangements, bringing to mind global capitation in the 1990s wherein several health systems failed. In this article, the authors focus on their framework for succeeding in value-based arrangements at University Hospitals Accountable Care Organization, including essential structural elements that provider organizations need to successfully assume downside risk in value-based arrangements. These elements include quality performance and reporting, risk adjustment, utilization management, care management and clinical services, network integrity, technology, and contracting and financial reconciliation. Each of these elements has an important place in the strategic roadmap to value, even if downside risk is not taken. This roadmap was developed through an applied approach and intends to fill the gap in published practical models of how provider organizations can maneuver value-based arrangements.
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Affiliation(s)
- Mark E Schario
- UH Quality Care Network & UH Accountable Care Organization, University Hospitals Health System, Cleveland, Ohio, USA
- Ursuline College, Breen School of Nursing and Health Professions, Pepper Pike, Ohio, USA
| | - Peter J Pronovost
- University Hospitals Health System, Cleveland, Ohio, USA
- Francis Payne Bolton School of Nursing, and Weatherhead School of Management, Case Western University, School of Medicine, Cleveland, Ohio, USA
| | - Patrick Runnels
- Population Health, University Hospitals, Cleveland, Ohio, USA
- Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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Nair D, Schildcrout JS, Shi Y, Trochez R, Nwosu S, Bell SP, Mixon AS, Welch SA, Goggins K, Bachmann JM, Vasilevskis EE, Cavanaugh KL, Rothman RL, Kripalani SB. Patient-reported predictors of post-discharge mortality after cardiac hospitalization. medRxiv 2023:2023.10.02.23296460. [PMID: 37873096 PMCID: PMC10593012 DOI: 10.1101/2023.10.02.23296460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Background Adults hospitalized for cardiovascular events are at high risk for post-discharge mortality. Hospital-based screening of health-related psychosocial risk factors is now prioritized by the Joint Commission and the National Quality Forum to achieve equitable, high-quality care. We tested our hypothesis that key patient-reported psychosocial and behavioral measures could predict post-hospitalization mortality in a cohort of adults hospitalized for a cardiovascular event. Methods This was a prospective cohort of adults hospitalized at Vanderbilt University Medical Center. Validated patient-reported measures of health literacy, social support, disease self-management, and socioeconomic status were used as predictors of interest. Cox survival analyses of mortality were conducted over a median 3.5-year follow-up (range: 1.25 - 5.5 years). Results Among 2,977 adults, 1,874 (63%) were hospitalized for acute coronary syndrome and 1,103 (37%) were hospitalized for acute decompensated heart failure; 60% were male; and the mean age was 53 years. After adjusting for demographic, clinical, and other psychosocial factors, mortality risk was greatest among patients who reported being unable to work due to disability (Hazard Ratio (HR) 2.36, 95% Confidence Interval (CI): 1.73-3.21), who were retired (HR 2.14, 95% CI 1.60-2.87), and who reported unemployment (HR 1.99, 95% CI 1.30-3.06) as compared to those who were employed. Patient-reported measures of disease self-management, perceived health competence and exercise frequency, were also associated with mortality risk after full covariate adjustment (HR 0.86, 95% CI 0.73-1.00 per four-point increase), (HR 0.86, 95% CI 0.77-0.96 per three-day change), respectively. Conclusions Patient-reported measures of employment status independently predict post-discharge mortality after a cardiac hospitalization. Measure of disease self-management also have prognostic modest utility. Hospital-based screening of psychosocial risk is increasingly prioritized in legislative policy. Incorporating brief, valid measures of employment status and disease self-management factors may help target patients for psychosocial, financial, and rehabilitative resources during post-discharge transitions of care.
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Kostelanetz S, Di Gravio C, Schildcrout JS, Roumie CL, Conway D, Kripalani S. Should We Implement Geographic or Patient-Reported Social Determinants of Health Measures In Cardiovascular Patients. Ethn Dis 2021; 31:9-22. [PMID: 33519151 DOI: 10.18865/ed.31.1.9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Objectives To compare patient-reported social determinants of health (SDOH) to the Brokamp Area Deprivation Index (ADI), and evaluate the association of patient-reported SDOH and ADI with mortality in patients with cardiovascular disease (CVD). Design Prospective cohort. Setting Academic medical center. Participants Adults with acute coronary syndrome (ACS) and/or acute exacerbation of heart failure (HF) hospitalized between 2011 and 2015. Methods Patient-reported SDOH included: income range, education, health insurance, and household size. ADI was calculated using census tract level variables of poverty, median income, high school completion, lack of health insurance, assisted income, and vacant housing. Primary Outcome All-cause mortality, up to 5 years follow-up. Results The sample was 60% male, 84% White, and 93% insured; mean patient-reported household income was $48,000 (SD $34,000). ADI components were significantly associated with corresponding patient-reported variables. In age, sex, and race adjusted Cox regression models, ADI was associated with mortality for ACS (HR 1.23, 95% CI 1.06, 1.42), but not HF (HR 1.09, 95% CI .99, 1.21). Mortality models for ACS improved with consideration of social determinants data (C-statistics: base demographic model=.612; ADI added=.644; patient-reported SDOH added=.675; both ADI and patient-reported SDOH added=.689). HF mortality models improved only slightly (C-statistics: .600, .602, .617, .620, respectively). Conclusions The Brokamp ADI is associated with mortality in hospitalized patients with CVD. In the absence of available patient-reported data, hospitals could implement the Brokamp ADI as an approximation for patient-reported data to enhance risk stratification of patients with CVD.
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Affiliation(s)
- Sophia Kostelanetz
- Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Chiara Di Gravio
- Department of Biostatistics, Vanderbilt University, Nashville, TN
| | | | - Christianne L Roumie
- Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Douglas Conway
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | - Sunil Kripalani
- Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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Predmore Z, Hatef E, Weiner JP. Integrating Social and Behavioral Determinants of Health into Population Health Analytics: A Conceptual Framework and Suggested Road Map. Popul Health Manag 2019; 22:488-494. [PMID: 30864884 DOI: 10.1089/pop.2018.0151] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
There is growing recognition that social and behavioral risk factors impact population health outcomes. Interventions that target these risk factors can improve health outcomes. This study presents a review of existing literature and proposes a conceptual framework for the integration of social and behavioral data into population health analytics platforms. The authors describe several use cases for these platforms at the patient, health system, and community levels, and align these use cases with the different types of prevention identified by the Centers for Disease Control and Prevention. They then detail the potential benefits of these use cases for different health system stakeholders and explore currently available and potential future sources of social and behavioral domains data. Also noted are several potential roadblocks for these analytic platforms, including limited data interoperability, expense of data acquisition, and a lack of standardized technical terminology for socio-behavioral factors.
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Affiliation(s)
- Zachary Predmore
- Department of Health Policy and Management, Center for Population Health Information Technology (CPHIT), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Elham Hatef
- Department of Health Policy and Management, Center for Population Health Information Technology (CPHIT), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.,Department of Health Policy and Management, Johns Hopkins Center for Health Disparities Solutions, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Jonathan P Weiner
- Department of Health Policy and Management, Center for Population Health Information Technology (CPHIT), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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