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

> **NIH NIH R01** · GEORGE WASHINGTON UNIVERSITY · 2020 · $356,120

## Abstract

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.

## Key facts

- **NIH application ID:** 9919325
- **Project number:** 5R01MD011607-04
- **Recipient organization:** GEORGE WASHINGTON UNIVERSITY
- **Principal Investigator:** MELISSA L MCCARTHY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $356,120
- **Award type:** 5
- **Project period:** 2017-08-14 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9919325

## Citation

> US National Institutes of Health, RePORTER application 9919325, Integrating Social Determinants of Health Into Risk Adjustment Models:  An Opportunity to Improve Care Coordination Strategies For Medicaid Beneficiaries (5R01MD011607-04). Retrieved via AI Analytics 2026-06-25 from https://api.ai-analytics.org/grant/nih/9919325. Licensed CC0.

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