Integrating Social Determinants of Health Into Risk Adjustment Models: An Opportunity to Improve Care Coordination Strategies For Medicaid Beneficiaries

项目总结 该项目的目的是为衡量健康的社会决定因素的价值提供证据。 (SDH)在医疗补助人口中。该项目将演示使用传统风险进行风险分层 除了将SDH信息包括在内，还可以显著改进调整模型(RAM 这些模型通常依赖的信息包括：年龄、性别和医疗诊断。此外，这个项目 将各种SDH因素对突发疾病的发病风险和累积风险量化为一 年期间，强调需要解决推动健康的社会和环境不利因素 因此，医疗补助计划可以实现三重目标：以更低的成本改善医疗保健和人口健康。 为了实现我们的目标，我们将进行一项前瞻性队列研究，纳入9600名成人医疗补助 受益人在华盛顿特区的两家医疗机构接受治疗。研究样本将是 主要是黑人(即90%)，女性比例略高(60%)。医疗补助受益人 参与人员将在初次就诊期间完成全面的SDH评估， 包括经过验证SDH问题，这些问题衡量住房稳定性、食品可获得性、财务压力、健康 行为、社会支持等。在注册后6个月和12个月，我们将进行电话跟踪 与受试者面谈，以确定他们的社会和环境是否有任何重大变化 情况。 我们将把面谈数据与DC Medicaid申请数据合并(投保前两年和投保后一年 日期)。我们将使用以前的索赔数据通过以下方式来描述医疗保健的使用和支出：(1) 不同类型的服务(即住院护理、门诊护理、处方药等)；(2)急性与慢性 治疗；以及(3)可预防与不可预防。我们将使用三种方法对研究样本进行风险分层 RAMS(即，慢性残疾和支付系统，约翰霍普金斯调整临床小组(ACG)) 系统和3M临床风险组(CRG)。我们将比较对明年医疗保健的预测 使用包括或不包括SDH的广义线性模型计算每个RAM的利用率和支出 变量。我们还将量化与不同SDH因素相关的事件和累积风险 使用广义估计方程模型在一年随访期内发病。 为了减少医疗补助人群中存在的巨大健康不平等，该项目旨在展示 在我们的护理提供战略中，迫切需要衡量和解决SDH。

PROJECT SUMMARY The purpose of this project is to provide evidence of the value of measuring social determinants of health (SDH) in the Medicaid population. This project will demonstrate that risk stratification using traditional risk adjustment models (RAMs) can be improved significantly with the inclusion of SDH information in addition to the information these models typically rely on: age, gender, and medical diagnoses. In addition, this project will quantify incident and cumulative risk of various SDH factors on the onset of incident disease within a one year period, highlighting the need to address social and environmental disadvantages that drive health inequities so that Medicaid can achieve the triple aim: improved care and population health at lower cost. To accomplish our objectives, we will conduct a prospective cohort study that will enroll 9,600 adult Medicaid beneficiaries treated at two medical facilities located in Washington, DC. The study sample will be predominately black (i.e. 90%) with a slightly higher percentage of females (60%). Medicaid beneficiaries who participate will complete a comprehensive SDH assessment during their initial medical encounter that will include validated SDH questions that measure housing stability, food availability, financial strain, health behaviors, social support, etc. Six and 12 months after enrollment, we will conduct a telephone follow-up interview with subjects to determine if there have been any major changes to their social and environmental circumstances. We will merge the interview data with DC Medicaid claims data (two years pre and one year post enrollment date). We will use the prior claims data to characterize health care utilization and expenditures by: (1) different types of service (i.e., inpatient care, outpatient care, prescription drugs, etc); (2) acute versus chronic treatments; and (3) preventable versus non preventable. We will risk stratify the study sample using three RAMs (i.e., Chronic Disability and Payment System, The Johns Hopkins Adjusted Clinical Groups (ACG) System, and 3M Clinical Risk Groups (CRGs). We will compare predictions of next year's health care utilization and expenditures for each RAM using generalized linear models that include or exclude SDH variables. We will also quantify the incident and cumulative risk associated with different SDH factors on disease onset during a one year follow-up period using generalized estimating equation models. To reduce the large health inequities that exist in the Medicaid population, this project aims to demonstrate the critical need to measure and address SDH in our care delivery strategies.