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

项目摘要 这个项目的目的是提供证据证明衡量健康的社会决定因素的价值 (SDH)在医疗补助人群中。本项目将证明，使用传统风险分层 调整模型（RAM）可以通过包括SDH信息而得到显著改进， 这些模型通常依赖的信息：年龄、性别和医疗诊断。此外，该项目 将量化事件和累积风险的各种SDH因素对发病的疾病在一个 强调需要解决影响健康的社会和环境不利因素， 这样，医疗补助就可以实现三个目标：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，将招募9，600名成人医疗补助计划 受益人在位于华盛顿的两家医疗机构接受治疗。研究样本将 主要是黑人（即90%），女性比例略高（60%）。医疗补助受益人 参与者将在初次就诊期间完成全面的SDH评估， 包括衡量住房稳定性、粮食供应、财政紧张、健康 行为、社会支持等。入组后6个月和12个月，我们将进行电话随访 与受试者进行访谈，以确定其社会和环境是否发生任何重大变化 情节 我们将合并访谈数据与DC Medicaid索赔数据（入组前两年和入组后一年 日期）。我们将使用先前的索赔数据来表征医疗保健利用和支出：（1） 不同类型的服务（即，住院治疗、门诊治疗、处方药等）;（2）急性与慢性 治疗;（3）可预防与不可预防。我们将使用三个风险分层研究样本 RAM（即，慢性残疾和支付系统，约翰霍普金斯调整的临床组（ACG） 系统和3 M临床风险组（CRG）。我们将比较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因素相关的事故和累积风险， 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大量健康不公平现象，该项目旨在证明 我们迫切需要在我们的护理提供战略中衡量和解决SDH问题。

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.