Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester.
JAMA Netw Open. 2023 Sep 5;6(9):e2332173. doi: 10.1001/jamanetworkopen.2023.32173.
The first MassHealth Social Determinants of Health payment model boosted payments for groups with unstable housing and those living in socioeconomically stressed neighborhoods. Improvements were designed to address previously mispriced subgroups and promote equitable payments to MassHealth accountable care organizations (ACOs).
To develop a model that ensures payments largely follow observed costs for members with complex health and/or social risks.
DESIGN, SETTING, AND PARTICIPANTS: This cross sectional study used administrative data for members of the Massachusetts Medicaid program MassHealth in 2016 or 2017. Participants included members who were eligible for MassHealth's managed care, aged 0 to 64 years, and enrolled for at least 183 days in 2017. A new total cost of care model was developed and its performance compared with 2 earlier models. All models were fit to 2017 data (most recent available) and validated on 2016 data. Analyses were begun in February 2019 and completed in January 2023.
Model 1 used age-sex categories, a diagnosis-based morbidity relative risk score (RRS), disability, serious mental illness, substance use disorder, housing problems, and neighborhood stress. Model 2 added an interaction for unstable housing with RRS. Model 3 added rurality and updated diagnosis-based RRS, medication-based RRS, and interactions between sociodemographic characteristics and morbidity.
Total 2017 annual cost was modeled and overall model performance (R2) and fair pricing of subgroups evaluated using observed-to-expected (O:E) ratios.
Among 1 323 424 members, mean (SD) age was 26.4 (17.9) years, 53.4% were female (46.6% male), and mean (SD) 2017 cost was $5862 ($15 417). The R2 for models 1, 2, and 3 was 52.1%, 51.5%, and 60.3%, respectively. Earlier models overestimated costs for members without behavioral health conditions (O:E ratios 0.94 and 0.93 for models 1 and 2, respectively) and underestimated costs for those with behavioral health conditions (O:E ratio >1.10); model 3 O:E ratios were near 1.00. Model 3 was better calibrated for members with housing problems, those with children, and those with high morbidity scores. It reduced underpayments to ACOs whose members had high medical and social complexity. Absolute and relative model performance were similar in 2016 data.
In this cross-sectional study of data from Massachusetts Medicaid, careful modeling of social and medical risk improved model performance and mitigated underpayments to safety-net systems.
第一个 MassHealth 社会决定因素健康支付模型增加了对住房不稳定和居住在社会经济压力大的社区的群体的支付。改进旨在解决以前定价错误的亚组问题，并促进向 MassHealth 负责医疗保健组织 (ACO) 进行公平支付。
开发一种模型，确保支付主要根据具有复杂健康和/或社会风险的成员的实际成本。
设计、设置和参与者：这项横断面研究使用了 2016 或 2017 年马萨诸塞州医疗补助计划 MassHealth 的成员的管理数据。参与者包括有资格参加 MassHealth 管理式医疗的成员，年龄在 0 至 64 岁之间，并且在 2017 年至少注册了 183 天。开发了一种新的总医疗成本模型，并将其性能与之前的 2 种模型进行了比较。所有模型都适用于 2017 年的数据（可获得的最新数据），并在 2016 年的数据上进行了验证。分析于 2019 年 2 月开始，2023 年 1 月完成。
模型 1 使用年龄-性别类别、基于诊断的发病率相对风险评分 (RRS)、残疾、严重精神疾病、物质使用障碍、住房问题和社区压力。模型 2 增加了与 RRS 不稳定住房的相互作用。模型 3 增加了农村地区，并更新了基于诊断的 RRS、基于药物的 RRS 以及社会人口特征和发病率之间的相互作用。
对 2017 年的年度总成本进行建模，并使用观察到的预期 (O:E) 比率评估总体模型性能 (R2) 和亚组的公平定价。
在 1323424 名成员中，平均（标准差）年龄为 26.4（17.9）岁，53.4%为女性（46.6%为男性），平均（标准差）2017 年费用为 5862 美元（15417 美元）。模型 1、2 和 3 的 R2 分别为 52.1%、51.5%和 60.3%。早期模型高估了没有行为健康状况的成员的成本（模型 1 和 2 的 O:E 比率分别为 0.94 和 0.93），低估了有行为健康状况的成员的成本（O:E 比率>1.10）；模型 3 的 O:E 比率接近 1.00。模型 3 更好地校准了有住房问题、有子女和发病率高的成员。它减少了向医疗保健成员具有高医疗和社会复杂性的 ACO 的预付款。2016 年数据的绝对和相对模型性能相似。
在这项对马萨诸塞州医疗补助计划数据的横断面研究中，对社会和医疗风险的仔细建模提高了模型性能，并减轻了对安全网系统的预付款不足。
