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Higher Quality and Lower Cost from Improving Hospital Discharge Decision Making

Author

Listed:
  • James C. Cox
  • Vjollca Sadiraj
  • Kurt E. Schnier
  • John F. Sweeney

Abstract

The added costs from excess, wasted resources in healthcare are estimated to exceed the size of the entire defense budget. Effectively addressing this problem requires decreasing the cost of healthcare while increasing its quality by improving healthcare decision making. This paper reports research on improving decisions about hospital discharges -- decisions that are now made by physicians based on mainly subjective evaluations of patients' discharge status. The research has three components: (a) econometric identification of patient medical status and demographic characteristics that discriminate between the likelihood of successful discharge and unsuccessful discharge (resulting in unplanned readmission within 30 days); (b) development of decision support software that incorporates evidence-based discharge criteria; and (c) empirical evaluation of efficacy of the decision support software. Experimental data reported herein indicate that utilization of the decision support software with evidence-based selection of the default option reduces both patients' average length of stay in the hospital and the likelihood of higher risk patients being readmitted.

Suggested Citation

  • James C. Cox & Vjollca Sadiraj & Kurt E. Schnier & John F. Sweeney, 2013. "Higher Quality and Lower Cost from Improving Hospital Discharge Decision Making," Experimental Economics Center Working Paper Series 2013-09, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Mar 2015.
    • Handle: RePEc:exc:wpaper:2013-09
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    Cited by:

    1. Cox, James C. & Sadiraj, Vjollca & Schnier, Kurt E. & Sweeney, John F., 2016. "Incentivizing cost-effective reductions in hospital readmission rates," Journal of Economic Behavior & Organization, Elsevier, vol. 131(PB), pages 24-35.
    2. Duncan James & Daniel Friedman & Christina Louie & Taylor O'Meara, 2018. "Dissecting The Monty Hall Anomaly," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1817-1826, July.
    3. Finocchiaro Castro, Massimo & Guccio, Calogero & Romeo, Domenica, 2022. "A systematic literature review of 10 years of behavioral research on health services," EconStor Preprints 266248, ZBW - Leibniz Information Centre for Economics.
    4. Brosig-Koch, Jeannette & Groß, Mona & Hennig-Schmidt, Heike & Kairies-Schwarz, Nadja & Wiesen, Daniel, 2021. "Physicians' incentives, patients' characteristics, and quality of care: A systematic experimental comparison of fee-for-service, capitation, and pay for performance," Ruhr Economic Papers 923, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. James C. Cox & Vjollca Sadiraj & Kurt E. Schnier & John F. Sweeney, 2017. "Fit as a Fiddle or Sick as a Dog: Effects of Subjective Patient Reports on Uptake of Clinical Decision Support," Experimental Economics Center Working Paper Series 2017-03, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Aug 2020.

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    More about this item

    Keywords

    Healthcare; Experiment; Clinical Decision Support System; Risk; Default Option;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I10 - Health, Education, and Welfare - - Health - - - General

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