Volume 36, Issue 1 (1-2022)                   Med J Islam Repub Iran 2022 | Back to browse issues page


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Khezri A, Mahboub-ahari A, Sadegh Tabrizi J, Nosratnejad S. Weight of Risk Factors for Adjusting Capitation in Primary Health Care: A Systematic Review. Med J Islam Repub Iran. 2022; 36 (1) :7-21
URL: http://mjiri.iums.ac.ir/article-1-5909-en.html
Tabriz Health Services Management Research Center, Health Management and Safety Promotion Research Institute, & Department of Health Economics, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran , nosratnejadsh@tbzmed.ac.ir
Abstract:   (67 Views)
Background: Capitation payment is the best-known strategy for paying providers in primary health care. Since health care needs and personal characteristics play an essential role in health care utilization and resource spending, there is a growing tendency on risk adjustment models among health researchers.  The objective of this systematic review was to examine the weights used for risk adjustment in primary health care capitation payment.
   Methods: We systematically searched Scopus, ProQuest, Web of Science, and PubMed in March 2018. Two authors independently apprised the included articles and they also evaluated, identified, and categorized different factors on capitation payments mentioned in the included studies.
   Results: A total of 742 studies were identified and 12 were included in the systematic review after the screening process. Risk factors for capitation adjustment included age, gender, and income with the weighted average being 1.76 and 1.03, respectively. Moreover, the weighted average disease incidence adjusted clinical groups (ACGs), diagnostic cost groups (DCGs), principal in patient diagnostic cost groups (PIP-DCGs), and hierarchical coexisting conditions (HCCs) were reported as 1.31, 24.7-.99, 10.4-.65, and 11.7-1.01, respectively.
   Conclusion: In low-income countries, the most effective factors used in capitation adjustment are age and sex. Moreover, the most applied factor in high-income countries is adjusted clinical groups, and income factors can have a better impact on the reduction of costs in low-income countries. Each country can select its most efficient factors based on the weight of the factor, income level, and geographical condition.
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