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Approaches to capitation and risk adjustment in health care: an international survey

Author

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  • Nigel Rice

    (Centre for Health Economics, The University of York)

  • Peter Smith

    (Centre for Health Economics, The University of York)

Abstract

This report is a survey of current capitation methods in health care finance in developed countries. It was commissioned as part of the fundamental review by UK Ministers of the formula used to allocate health care finance to local areas in England, being carried out under the auspices of the Advisory Committee on Resource Allocation (ACRA). The study was commissioned in February 1999 and completed in May 1999. It was informed by a review of published literature and an extensive network of contacts in government departments and academic institutions. A capitation can be defined as the amount of health service funds to be assigned to a person for the service in question, for the time period in question, subject to any national budget constraints. In effect, a capitation system puts a “price” on the head of every citizen. Capitations are usually varied according to an individual’s personal and social characteristics, using a process known as risk adjustment. In most nations, the intention is that the risk-adjusted capitation should represent an unbiased estimate of the expected costs of the citizen to the health care plan over the chosen time period (typically one year). There is an element of capitation funding in the health care systems of almost all developed countries. Capitation is seen as an important mechanism for securing both equity and efficiency objectives. The review examined capitation schemes in 19 countries and concentrated on major strategic risk adjustment schemes implemented at the national or regional level. It identified two broad approaches to setting capitations, which we term matrix methods and index methods. The fundamental difficulties affecting both approaches are a lack of suitable data and the problem of disentangling needs effects from supply effects on health care utilization. Almost all schemes rely on analysis of empirical data, and various analytic methods have been used for setting capitations. Numerous need and cost factors have been used in setting capitations. However, the choice has usually been determined more by data availability than a compelling link to health care expenditure needs. The review concluded that there were elements of many schemes that may be of relevance to the review of methods currently used in England, and which deserve further investigation. However, until improvements in data availability are in place, it is difficult to envisage major enhancements to methods currently in use.

Suggested Citation

  • Nigel Rice & Peter Smith, 1999. "Approaches to capitation and risk adjustment in health care: an international survey," Working Papers 038cheop, Centre for Health Economics, University of York.
  • Handle: RePEc:chy:respap:38cheop
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    Cited by:

    1. Oliveira, Monica Duarte & Bevan, Gwyn, 2003. "Measuring geographic inequities in the Portuguese health care system: an estimation of hospital care needs," Health Policy, Elsevier, vol. 66(3), pages 277-293, December.
    2. Schokkaert, Erik & Van de Voorde, Carine, 2004. "Risk selection and the specification of the conventional risk adjustment formula," Journal of Health Economics, Elsevier, vol. 23(6), pages 1237-1259, November.
    3. Oliveira, Monica D. & Bevan, Gwyn, 2008. "Modelling hospital costs to produce evidence for policies that promote equity and efficiency," European Journal of Operational Research, Elsevier, vol. 185(3), pages 933-947, March.
    4. O'Loughlin, Rosalyn & Kelly, Alan, 2004. "Equity in resource allocation in the Irish health service: A policy Delphi study," Health Policy, Elsevier, vol. 67(3), pages 271-280, March.
    5. Monica Oliveira, 2004. "Modelling demand and supply influences on utilization: A flow demand model to predict hospital utilization at the small area level," Applied Economics, Taylor & Francis Journals, vol. 36(20), pages 2237-2251.
    6. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Monica Auteri & Guido Borà, 2017. "La spesa sanitaria delle Regioni in Italia - Saniregio2017," Working Papers CERM 01-2017, Competitività, Regole, Mercati (CERM).
    7. Somi Shin, 2021. "Healthcare provider response to payment system reform: evidence from New Zealand," SN Business & Economics, Springer, vol. 1(11), pages 1-29, November.
    8. Trevor A. Sheldon & Peter C. Smith, 2000. "Equity in the allocation of health care resources," Health Economics, John Wiley & Sons, Ltd., vol. 9(7), pages 571-574, October.
    9. Peter McHenry & Jennifer Mellor, 2018. "Medicare hospital payment adjustments and nursing wages," International Journal of Health Economics and Management, Springer, vol. 18(2), pages 169-196, June.
    10. Amir Shmueli, 2015. "On the calculation of the Israeli risk adjustment rates," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(3), pages 271-277, April.
    11. Friedrich Breyer & Mathias Kifmann, 2001. "Optionen der Weiterentwicklung des Risikostrukturausgleichs in der GKV," Discussion Papers of DIW Berlin 236, DIW Berlin, German Institute for Economic Research.
    12. Kathryn Antioch & Michael Walsh, 2004. "The risk-adjusted vision beyond casemix (DRG) funding in Australia," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 5(2), pages 95-109, May.
    13. Constantinou, Panayotis & Tuppin, Philippe & Gastaldi-Ménager, Christelle & Pelletier-Fleury, Nathalie, 2022. "Defining a risk-adjustment formula for the introduction of population-based payments for primary care in France," Health Policy, Elsevier, vol. 126(9), pages 915-924.
    14. Robert Elliott & Ada Ma & Matt Sutton & Diane Skatun & Nigel Rice & Stephen Morris & Alex McConnachie, 2010. "The role of the staff MFF in distributing NHS funding: taking account of differences in local labour market conditions," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 532-548, May.
    15. Barbara Wieckowska, 2013. "Systemy wyrownywania szkodowosci funkcjonujace w bazowych systemach zabezpieczenia zdrowotnego z konkurencja pomiedzy platnikami trzeciej strony. (Claims equalization systems, operating in the health ," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 11(41), pages 193-203.
    16. Enza Caruso & Nerina Dirindin, 2012. "Health care and fiscal federalism: Paradoxes of recent reform in Italy," Politica economica, Società editrice il Mulino, issue 2, pages 169-196.
    17. repec:sgm:pzwzuw:v:1:i:2:y:2013:p:193-203 is not listed on IDEAS
    18. Vallejo-Torres, Laura & Morris, Stephen & Carr-Hill, Roy & Dixon, Paul & Law, Malcom & Rice, Nigel & Sutton, Matthew, 2009. "Can regional resource shares be based only on prevalence data? An empirical investigation of the proportionality assumption," Social Science & Medicine, Elsevier, vol. 69(11), pages 1634-1642, December.
    19. Matranga, Domenica & Sapienza, Francesca, 2015. "Congestion analysis to evaluate the efficiency and appropriateness of hospitals in Sicily," Health Policy, Elsevier, vol. 119(3), pages 324-332.
    20. Matthew Sutton & Peter Lock, 2000. "Regional differences in health care delivery: implications for a national resource allocation formula," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 547-559, September.
    21. Montero Granados, Roberto & Jimenez Aguilera, Juan de Dios & Martin Martin, Jose Jesus, 2007. "Estimation of an index of regional health needs in Spain using count regression models with filter," Health Policy, Elsevier, vol. 81(1), pages 4-16, April.
    22. Almeida, Anabela, 2007. "Práticas de Aprovisionamento nos Hospitais Públicos Portugueses: Estudo das Diferenças Regionais [Procurement Practices In The Public Hospitals In Portugal: A Study Of Regional Differences]," MPRA Paper 6241, University Library of Munich, Germany.

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    Keywords

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