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Measuring the relationship between costs and outcomes: The example of Acute Myocardial Infarction in German hospitals

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  • Stargardt, Tom
  • Schreyögg, Jonas
  • Kondofersky, Ivan

Abstract

In this paper, we propose a methodological approach to measure the relationship between hospital costs and health outcomes. We propose to investigate the relationship for each condition or disease area using patient-level data. We suggest to examine health outcomes as a function of costs and other patientlevel variables: (1) using two-stage residual inclusion with Murphy-Topel adjustment to address costs being endogenous to health outcomes, (2) using random-effects models in both stages to correct for correlation between observation, and (3) using Cox proportional hazard models in the second stage to ensure the available information is exploited. To demonstrate its application, data on mortality following hospital treatment for acute myocardial infarction (AMI) from a large German sickness was used. Provider reimbursement was used as a proxy for treatment costs. We relied on the Ontario Acute Myocardial Infarction Mortality Prediction Rules as a disease-specific risk-adjustment instrument. 12,284 patients with a treatment for AMI in 2004-2006 were included. Results showed a reduction in hospital costs by 100 to increase the hazard of dying, i.e. mortality, by 0.43%. The negative association between costs and mortality confirms that increased resource input leads to better outcomes for treatment after AMI.

Suggested Citation

  • Stargardt, Tom & Schreyögg, Jonas & Kondofersky, Ivan, 2012. "Measuring the relationship between costs and outcomes: The example of Acute Myocardial Infarction in German hospitals," hche Research Papers 2012/04, University of Hamburg, Hamburg Center for Health Economics (hche).
  • Handle: RePEc:zbw:hcherp:201204
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    References listed on IDEAS

    as
    1. Shen, Yu-Chu, 2002. "The effect of hospital ownership choice on patient outcomes after treatment for acute myocardial infarction," Journal of Health Economics, Elsevier, vol. 21(5), pages 901-922, September.
    2. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, vol. 27(3), pages 531-543, May.
    3. Murphy, Kevin M & Topel, Robert H, 2002. "Estimation and Inference in Two-Step Econometric Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 88-97, January.
    4. Jonas Schreyögg & Tom Stargardt & Oliver Tiemann, 2011. "Costs and quality of hospitals in different health care systems: a multi‐level approach with propensity score matching," Health Economics, John Wiley & Sons, Ltd., vol. 20(1), pages 85-100, January.
    5. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
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    Cited by:

    1. Laura Haas & Tom Stargardt & Jonas Schreyoegg & Rico Schlösser & Burghard Klapp & Gerhard Danzer, 2013. "The Trade-off Between Costs and Quality of Care in the Treatment of Psychosomatic Patients with Somatoform Pain Disorder," Applied Health Economics and Health Policy, Springer, vol. 11(4), pages 359-368, August.
    2. Mareike Heimeshoff & Jonas Schreyögg & Lukas Kwietniewski, 2014. "Cost and technical efficiency of physician practices: a stochastic frontier approach using panel data," Health Care Management Science, Springer, vol. 17(2), pages 150-161, June.
    3. Milstein, Ricarda & Schreyoegg, Jonas, 2016. "Pay for performance in the inpatient sector: A review of 34 P4P programs in 14 OECD countries," Health Policy, Elsevier, vol. 120(10), pages 1125-1140.
    4. Lindlbauer, Ivonne & Schreyögg, Jonas & Winter, Vera, 2016. "Changes in technical efficiency after quality management certification: A DEA approach using difference-in-difference estimation with genetic matching in the hospital industry," European Journal of Operational Research, Elsevier, vol. 250(3), pages 1026-1036.

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    Keywords

    hospital costs; acute myocardial infarction; trade-off; readmission; mortality;

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