Latent Class Analysis to Represent Social Determinant of Health Risk Groups in the Medicaid Cohort of the District of Columbia.
Latent Class Analysis to Represent Social Determinant of Health Risk Groups in the Medicaid Cohort of the District of Columbia.
复制标题
代表哥伦比亚特区医疗补助队列中健康风险群体社会决定因素的潜在类别分析。
DOI：
10.1097/mlr.0000000000001468
复制
发表时间：
2021-03-01
期刊：
影响因子：
3
通讯作者：
Zeger SL
中科院分区：
文献类型：
--
作者：
McCarthy ML;Zheng Z;Wilder ME;Elmi A;Kulie P;Johnson S;Zeger SL
根据健康的社会决定因素（SDH）信息制定不同的社会风险概况，并确定这些社会风险群体在健康、医疗保健利用和成本方面是否存在差异。我们前瞻性地招募了2017年9月至2018年12月期间由哥伦比亚特区医疗补助计划承保的8，943名受益人。参与者完成了SDH调查，我们在研究入组前2年内获得了他们的医疗补助索赔数据。我们使用潜在类别分析（LCA），以确定不同的社会风险概况的基础上，他们的SDH的反应。我们评估了不同SDH之间的关系以及社会风险等级与健康、医疗保健使用和成本之间的关系。大多数SDH之间存在中度至强烈的相关性。LCA产生了四个不同的社会风险群体。第1组报告的社会风险最小，就业人数最多。第二组的特点是财政紧张和住房不稳定，就业人数较少。第三组大多是失业者，汽车和互联网接入有限。第4组的社会风险最大，失业人数最多。社会风险组在健康、急性护理利用和医疗保健费用方面表现出有意义的差异，第1组的健康结果最好，第4组最差（p <0.05）。LCA是一种将相关的SDH数据聚合成有限数量的不同社会风险群体的实用方法。了解患者面临的社会挑战的星座是至关重要的，当试图解决他们的社会需求和改善健康结果。
To develop distinct social risk profiles based on social determinants of health (SDH) information and to determine whether these social risk groups varied in terms of health, healthcare utilization and costs. We prospectively enrolled 8,943 beneficiaries insured by the District of Columbia Medicaid program between September 2017 and December 2018. Participants completed a SDH survey and we obtained their Medicaid claims data for a 2-year period prior to study enrollment. We used latent class analysis (LCA) to identify distinct social risk profiles based on their SDH responses. We assessed the relationship among different SDH as well as the relationship among the social risk classes and health, healthcare use and costs. The majority of SDH were moderately to strongly correlated with one another. LCA yielded four distinct social risk groups. Group 1 reported the least social risks with the most employed. Group 2 was distinguished by financial strain and housing instability with fewer employed. Group 3 were mostly unemployed with limited car and internet access. Group 4 had the most social risks and most unemployed. The social risk groups demonstrated meaningful differences in health, acute care utilization and healthcare costs with group 1 having the best health outcomes and group 4 the worst (p < 0.05). LCA is a practical method of aggregating correlated SDH data into a finite number of distinct social risk groups. Understanding the constellation of social challenges that patients face is critical when attempting to address their social needs and improve health outcomes.