Khezri Ali, Mahboub-Ahari Alireza, Tabrizi Jafar Sadegh, Nosratnejad Shirin
Tabriz Health Services Management Research Center, Health Management and Safety Promotion Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran.
Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Scineces, Tabriz, Iran.
Med J Islam Repub Iran. 2022 Feb 2;36:2. doi: 10.47176/mjiri.36.2. eCollection 2022.
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. 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. 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. 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.
按人头付费是初级卫生保健中支付医疗服务提供者费用最广为人知的策略。由于医疗保健需求和个人特征在医疗保健利用和资源支出中起着至关重要的作用,健康研究人员对风险调整模型的使用呈增长趋势。本系统评价的目的是研究初级卫生保健按人头付费中用于风险调整的权重。2018年3月,我们系统检索了Scopus、ProQuest、Web of Science和PubMed。两位作者独立评估纳入的文章,并对纳入研究中提到的按人头付费的不同因素进行评估、识别和分类。共识别出742项研究,筛选后有12项纳入系统评价。按人头调整的风险因素包括年龄、性别和收入,加权平均值分别为1.76和1.03。此外,加权平均疾病发病率调整临床组(ACG)、诊断成本组(DCG)、住院患者主要诊断成本组(PIP-DCG)和分层共存疾病(HCC)分别报告为1.31、24.7-.99、10.4-.65和11.7-1.01。在低收入国家,按人头调整中最有效的因素是年龄和性别。此外,高收入国家最常用的因素是调整临床组,收入因素对低收入国家降低成本有更好的影响。每个国家可以根据因素权重、收入水平和地理条件选择最有效的因素。