# Development, Piloting and Dissemination of an Integrated Clinical and Social Multi-level Decision Support Platform to Address Social Determinants of Health Among Minority Populations in Baltimore City

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2021 · $695,707

## Abstract

 PROJECT SUMMARY
Achieving a comprehensive assessment of a person's health and addressing health disparities goes beyond just
documenting clinical diseases and medical interventions. We must also capture, standardize, analyze, and report
reliable information on Social Determinants of Health (SDOH) within operational Clinical Decision Support (CDS)
systems that are built-into electronic health records (EHRs). Moreover, to truly have an impact on decreasing health
disparities, data analysis is not enough. At the point of care, we must digitally support interactions between medical
and social services. Our proposed project addresses many of the hurdles in this process through the application of
informatics, social science, health services research, implementation science, and stakeholder engaged research. This
project will be undertaken by an experienced interdisciplinary team of investigators with many pre-existing resources.
To maximize impact, the academic team will be complemented by an exceptional network of collaborating
community, operational information technology, and stakeholder agencies from both the region and nationally. Our
goal is to facilitate the integration of available digital information regarding SDOH needs and services into provider
EHRs with the intent of improving care for minority and disadvantaged populations with chronic diseases.
The first aim will be to integrate both clinical and non-clinical large-scale databases (e.g., EHRs, social
risk assessments, and neighborhood characteristics) in order to develop a multi-level CDS tool inclusive of a
comprehensive social risk score. As part of this CDS, in collaboration with the Maryland Health Information
Exchange, we will also develop an interoperable closed loop referral system between primary care
practices and 3 community based (social service) organizations (CBOs). These and all other development
phases will build on extensive preliminary work the study collaborators have completed in related domains.
The second aim will be to integrate the CDS tool into the established care management support
system and workflow and to pilot this Health IT-based intervention using a randomized clinical trial
(RCT) design at four primary care practices within the Johns Hopkins Health System (JHHS). The main intent of
this CDS-based intervention will be to identify and assess SDOH of African-American adult patients (18+) with low
incomes and a high burden of chronic illness, and as needed to refer them to the CBOs participating in this pilot.
The third aim will be to assess the acceptability of the CDS tool (including its risk score and referral
module) and to initiate dissemination of the data platform in support of its implementation across the JHHS
institution, the Maryland statewide (CPC+) primary care program, and potentially nationally. To accomplish this aim,
we will collaborate closely with clinical providers, CBOs, and an advisory board made up of the local and national
leaders, a...

## Key facts

- **NIH application ID:** 10119945
- **Project number:** 1R01MD015844-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Elham Hatef-Naimi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $695,707
- **Award type:** 1
- **Project period:** 2021-07-20 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10119945

## Citation

> US National Institutes of Health, RePORTER application 10119945, Development, Piloting and Dissemination of an Integrated Clinical and Social Multi-level Decision Support Platform to Address Social Determinants of Health Among Minority Populations in Baltimore City (1R01MD015844-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10119945. Licensed CC0.

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