Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center

Author:

Howell Carrie R1ORCID,Bradley Heather2,Zhang Li3ORCID,Cleveland John D3,Long Dustin3,Horton Trudi1,Krantz Olivia1,Mugavero Michael J4,Williams Winter L5,Amerson Alesha1,Cherrington Andrea L1

Affiliation:

1. Department of Medicine, Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

2. Care Transitions, University of Alabama at Birmingham, Birmingham, AL, USA

3. Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

4. Department of Medicine, Division of Infectious Diseases, University of Alabama at Birmingham, Birmingham, AL, USA

5. Department of Medicine, Division of General Internal Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

Abstract

ObjectiveTo describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR).MethodsWe employed the collection of the PRAPARE tool in the EMR of a large academic health system in the ambulatory clinic and emergency department setting. After integration, we evaluated SDoH prevalence, levels of missingness, and data anomalies to inform ongoing collection. We summarized responses using descriptive statistics and hand-reviewed data text fields and patterns in the data. Data on patients who were administered with the PRAPARE from February to December 2020 were extracted from the EMR. Patients missing ≥ 12 PRAPARE questions were excluded. Social risks were screened using the PRAPARE. Information on demographics, admittance status, and health coverage were extracted from the EMR.ResultsAssessments with N = 6531 were completed (mean age 54 years, female (58.6%), 43.8% Black). Missingness ranged from 0.4% (race) to 20.8% (income). Approximately 6% of patients were homeless; 8% reported housing insecurity; 1.4% reported food needs; 14.6% had healthcare needs; 8.4% needed utility assistance; and 5% lacked transportation related to medical care. Emergency department patients reported significantly higher proportions of suboptimal SDoH.ConclusionsIntegrating the PRAPARE assessment in the EMR provides valuable information on SDoH amenable to intervention, and strategies are needed to increase accurate data collection and to improve the use of data in the clinical encounter.

Funder

National Institute on Minority Health and Health Disparities

National Institutes of Health

American Heart Association

Publisher

SAGE Publications

Subject

Health Information Management,Computer Science Applications,Health Informatics,Health Policy

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5. National Association of Community Health Centers. PRAPARE implementation and action toolkit: responding to social determinants of health data, track enabling services, https://www.nachc.org/wp-content/uploads/2019/04/NACHC_PRAPARE_Chpt10.pdf (2019, accessed 25 August 2020).

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