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Continuity of Care and Risk of Readmission: An Investigation into the Healthcare Journey of Heart Failure Patients

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  • Claire Senot

Abstract

We investigate the association between continuity of care mechanisms and a patient's risk of readmission in the context of one chronic condition, heart failure. We define continuity of care as the level of consistency across patient care episodes. We dynamically measure continuity of individual referring provider; continuity of physical location, which links multiple individual providers; and continuity of Accountable Care Organization, which spans a variety of individual and institutional providers. We compile a unique large‐scale dataset that includes patient‐level claims, to follow heart failure patients throughout inpatient and outpatient settings in 2014. Our final sample covers 44,129 episodes of care for 3263 patients. Using a competitive‐risks survival model, we find that all three continuity mechanisms are associated with a patient's lower risk of readmission. This exploratory study contributes to operations management literature by identifying effective integration mechanisms in the setting of healthcare delivery. In addition, by providing the first quantitative evidence for the critical role of multiple simultaneous mechanisms in ensuring continuity of care, this study offers important preliminary insights for public policy efforts.

Suggested Citation

  • Claire Senot, 2019. "Continuity of Care and Risk of Readmission: An Investigation into the Healthcare Journey of Heart Failure Patients," Production and Operations Management, Production and Operations Management Society, vol. 28(8), pages 2008-2030, August.
  • Handle: RePEc:bla:popmgt:v:28:y:2019:i:8:p:2008-2030
    DOI: 10.1111/poms.13027
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    Cited by:

    1. Topuz, Kazim & Urban, Timothy L. & Yildirim, Mehmet B., 2024. "A Markovian score model for evaluating provider performance for continuity of care—An explainable analytics approach," European Journal of Operational Research, Elsevier, vol. 317(2), pages 341-351.
    2. Ghazalbash, Somayeh & Zargoush, Manaf & Mowbray, Fabrice & Costa, Andrew, 2022. "Impact of multimorbidity and frailty on adverse outcomes among older delayed discharge patients: Implications for healthcare policy," Health Policy, Elsevier, vol. 126(3), pages 197-206.
    3. Vishal Ahuja & Carlos A. Alvarez & Bradley R. Staats, 2020. "Maintaining Continuity in Service: An Empirical Examination of Primary Care Physicians," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 1088-1106, September.
    4. Chih-Chou Chiu & Chung-Min Wu & Te-Nien Chien & Ling-Jing Kao & Chengcheng Li & Chuan-Mei Chu, 2023. "Integrating Structured and Unstructured EHR Data for Predicting Mortality by Machine Learning and Latent Dirichlet Allocation Method," IJERPH, MDPI, vol. 20(5), pages 1-22, February.
    5. Liangfei Qiu & Subodha Kumar & Arun Sen & Atish P. Sinha, 2022. "Impact of the Hospital Readmission Reduction Program on hospital readmission and mortality: An economic analysis," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2341-2360, May.
    6. Katherine Bobroske & Michael Freeman & Lawrence Huan & Anita Cattrell & Stefan Scholtes, 2022. "Curbing the Opioid Epidemic at Its Root: The Effect of Provider Discordance After Opioid Initiation," Management Science, INFORMS, vol. 68(3), pages 2003-2015, March.

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