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Predicting diagnostic coding in hospitals: individual level effects of price incentives

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  • Kjartan Sarheim Anthun

    (SINTEF Digital
    Norwegian University of Science and Technology)

Abstract

The purpose of this paper is to test if implicit price incentives influence the diagnostic coding of hospital discharges. We estimate if the probability of being coded as a complicated patient was related to a specific price incentive. This paper tests empirically if upcoding can be linked to shifts in patient composition through proxy measures such as age composition, length of stay, readmission rates, mortality- and morbidity of patients. Data about inpatient episodes in Norway in all specialized hospitals in the years 1999–2012 were collected, N = 11 065 330. We examined incentives present in part of the hospital funding system. First, we analyse trends in the proxy measures of diagnostic upcoding: can hospital behavioural changes be seen over time with regards to age composition, readmission rates, length of stay, comorbidity and mortality? Secondly, we examine specific patient groups to see if variations in the price incentive are related to probability of being coded as complicated. In the first years (1999–2003) there was an observed increase in the share of episodes coded as complicated, while the level has become more stable in the years 2004–2012. The analysis showed some indications of upcoding. However, we found no evidence of widespread upcoding fuelled by implicit price incentive, as other issues such as patient characteristics seem to be more important than the price differences. This study adds to previous research by testing individual level predictions. The added value of such analysis is to have better case mix control. We observe the presence of price effects even at individual level.

Suggested Citation

  • Kjartan Sarheim Anthun, 2022. "Predicting diagnostic coding in hospitals: individual level effects of price incentives," International Journal of Health Economics and Management, Springer, vol. 22(2), pages 129-146, June.
    • Handle: RePEc:kap:ijhcfe:v:22:y:2022:i:2:d:10.1007_s10754-021-09314-5
    DOI: 10.1007/s10754-021-09314-5
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    References listed on IDEAS

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    1. 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.
    2. Melberg, Hans Olav & Beck Olsen, Camilla & Pedersen, Kine, 2016. "Did hospitals respond to changes in weights of Diagnosis Related Groups in Norway between 2006 and 2013?," Health Policy, Elsevier, vol. 120(9), pages 992-1000.
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    4. Carine Milcent, 2021. "From downcoding to upcoding: DRG based payment in hospitals," International Journal of Health Economics and Management, Springer, vol. 21(1), pages 1-26, March.
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    6. Sacarny, Adam, 2018. "Adoption and learning across hospitals: The case of a revenue-generating practice," Journal of Health Economics, Elsevier, vol. 60(C), pages 142-164.
    7. Carine Milcent, 2021. "From downcoding to upcoding: DRG based payment in hospitals," Post-Print halshs-03094679, HAL.
    8. Fisher, E.S. & Whaley, F.S. & Krushat, W.M. & Malenka, D.J. & Fleming, C. & Baron, J.A. & Hsia, D.C., 1992. "The accuracy of Medicare's hospital claims data: Progress has been made, but problems remain," American Journal of Public Health, American Public Health Association, vol. 82(2), pages 243-248.
    9. Carine Milcent, 2021. "From downcoding to upcoding: DRG based payment in hospitals," PSE-Ecole d'économie de Paris (Postprint) halshs-03094679, HAL.
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