Predicting healthcare expenditure based on Adjusted Morbidity Groups to implement a needs-based capitation financing system.

IF 2.7 3区 经济学 Q1 ECONOMICS
Jorge-Eduardo Martínez-Pérez, Juan-Antonio Quesada-Torres, Eduardo Martínez-Gabaldón
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引用次数: 0

Abstract

Background: Due to population aging, healthcare expenditure is projected to increase substantially in developed countries like Spain. However, prior research indicates that health status, not merely age, is a key driver of healthcare costs. This study analyzed data from over 1.25 million residents of Spain's Murcia region to develop a capitation-based healthcare financing model incorporating health status via Adjusted Morbidity Groups (AMGs). The goal was to simulate an equitable area-based healthcare budget allocation reflecting population needs.

Methods: Using 2017 data on residents' age, sex, AMG designation, and individual healthcare costs, generalized linear models were built to predict healthcare expenditure based on health status indicators. Multiple link functions and distribution families were tested, with model selection guided by information criteria, residual analysis, and goodness-of-fit statistics. The selected model was used to estimate adjusted populations and simulate capitated budgets for the 9 healthcare districts in Murcia.

Results: The gamma distribution with logarithmic link function provided the best model fit. Comparisons of predicted and actual average costs revealed underfunded and overfunded areas within Murcia. If implemented, the capitation model would decrease funding for most districts (up to 15.5%) while increasing it for two high-need areas, emphasizing allocation based on health status and standardized utilization rather than historical spending alone.

Conclusions: AMG-based capitated budgeting could improve equity in healthcare financing across regions in Spain. By explicitly incorporating multimorbidity burden into allocation formulas, resources can be reallocated towards areas with poorer overall population health. Further policy analysis and adjustment is needed before full-scale implementation of such need-based global budgets.

根据调整后发病率组别预测医疗支出,以实施基于需求的按人头付费融资系统。
背景:由于人口老龄化,预计西班牙等发达国家的医疗保健支出将大幅增加。然而,先前的研究表明,健康状况,而不仅仅是年龄,是医疗费用的主要驱动因素。本研究分析了西班牙穆尔西亚地区 125 多万居民的数据,通过调整发病率组(AMGs)建立了一个基于按人头付费的医疗融资模型,将健康状况纳入其中。目标是模拟反映人口需求的基于地区的公平医疗预算分配:利用 2017 年居民的年龄、性别、AMG 名称和个人医疗费用数据,建立广义线性模型,根据健康状况指标预测医疗支出。测试了多个链接函数和分布族,并根据信息标准、残差分析和拟合优度统计来选择模型。所选模型用于估算调整后的人口数量,并模拟穆尔西亚 9 个医疗保健区的按人头计算的预算:带有对数链接函数的伽马分布提供了最佳模型拟合。对预测平均成本和实际平均成本进行比较后发现,穆尔西亚有资金不足和资金过剩的地区。如果实施按人头分配模式,大多数地区的资金将减少(最多 15.5%),而两个高需求地区的资金将增加,强调根据健康状况和标准化使用情况分配资金,而不是仅根据历史支出分配资金:基于 AMG 的按人头编制预算可提高西班牙各地区医疗融资的公平性。通过将多病症负担明确纳入分配公式,可将资源重新分配到总体人口健康状况较差的地区。在全面实施这种基于需求的全球预算之前,还需要进一步的政策分析和调整。
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来源期刊
CiteScore
3.90
自引率
4.20%
发文量
59
审稿时长
13 weeks
期刊介绍: Health Economics Review is an international high-quality journal covering all fields of Health Economics. A broad range of theoretical contributions, empirical studies and analyses of health policy with a health economic focus will be considered for publication. Its scope includes macro- and microeconomics of health care financing, health insurance and reimbursement as well as health economic evaluation, health services research and health policy analysis. Further research topics are the individual and institutional aspects of health care management and the growing importance of health care in developing countries.
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