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The Impact of the Inpatient Prospective Payment System and Diagnosis-Related Groups

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  • Marjorie Rosenberg
  • Mark Browne

Abstract

The outpatient prospective payment system for the Medicare program became effective Aug. 1, 2000, as mandated by the Balanced Budget Act of 1997. This outpatient program complements Medicare’s inpatient prospective payment system, which was introduced in 1983. A survey of the literature over the past 20 years is undertaken to review the effects of the inpatient prospective payment system and diagnosis-related groups (DRGs) on inpatient hospital utilization, expenditures, and outcomes. The level of the DRG payment has been questioned, as well as the process of adjusting the payment levels from one year to the next. In addition, past research has speculated that the DRG classification may not be sensitive to severity and is subject to coding ambiguities. These conclusions can be used as input to future research on the new outpatient program, as well as updating research on the inpatient program.

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  • Marjorie Rosenberg & Mark Browne, 2001. "The Impact of the Inpatient Prospective Payment System and Diagnosis-Related Groups," North American Actuarial Journal, Taylor & Francis Journals, vol. 5(4), pages 84-94.
    • Handle: RePEc:taf:uaajxx:v:5:y:2001:i:4:p:84-94
    DOI: 10.1080/10920277.2001.10596020
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    Cited by:

    1. Powell, Philip T. & Laufer, Ron, 2010. "The promises and constraints of consumer-directed healthcare," Business Horizons, Elsevier, vol. 53(2), pages 171-182, March.
    2. Kjartan Sarheim Anthun & Johan Håkon Bjørngaard & Jon Magnussen, 2017. "Economic incentives and diagnostic coding in a public health care system," International Journal of Health Economics and Management, Springer, vol. 17(1), pages 83-101, March.
    3. Cheng, Shou-Hsia & Chen, Chi-Chen & Tsai, Shu-Ling, 2012. "The impacts of DRG-based payments on health care provider behaviors under a universal coverage system: A population-based study," Health Policy, Elsevier, vol. 107(2), pages 202-208.
    4. Kanix Wang & Walid Hussain & John R. Birge & Michael D. Schreiber & Daniel Adelman, 2022. "A High-Fidelity Model to Predict Length of Stay in the Neonatal Intensive Care Unit," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 183-195, January.
    5. Paolo Berta & Chiara Seghieri & Giorgio Vittadini, 2013. "Comparing health outcomes among hospitals: the experience of the Lombardy Region," Health Care Management Science, Springer, vol. 16(3), pages 245-257, September.
    6. Laurence C. Baker & Karine Lamiraud, 2022. "Adoption of hospital diagnosis‐related group financing in Switzerland and the availability of computed tomography scanners," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2537-2557, December.

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