Identification of Social Risk-Related Referrals in Discrete Primary Care Electronic Health Record Data: Lessons Learned From a Novel Methodology.

IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Health Services Research Pub Date : 2025-02-06 DOI:10.1111/1475-6773.14443
Jenine Dankovchik, Rachel Gold, Aileen Ochoa, Jenna Donovan, Rose Gunn, Suzanne Morrissey, Cristina Huebner Torres, Ned Mossman, Seth A Berkowitz
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Abstract

Objective: To assess the utility of using discrete primary care electronic health record (EHR) data to identify social risk referrals in a national network of community-based clinics.

Data sources and study setting: Primary data were abstracted from the OCHIN network EHR (June 2016 to February 2022) of 1459 community-based clinics across the United States.

Study design: Structured data elements included 913 commonly used smartphrases and 53 procedure codes that were considered potential indicators of social risk referrals. Using stratified purposive sampling, we compared these discrete data with clinical notes to assess concordance of social risk referral documentation, and of the prevalence, types, and outcomes of such referrals.

Data collection/extraction methods: Smartphrases were classified into three categories (likely, possible, or unlikely to indicate a social risk referral); 50 chart notes were sampled for each of the 25 most frequently used smartphrases in each category, and for 53 of the most frequently used procedure codes. A total of 6104 chart notes were reviewed.

Principal findings: In 59% of chart notes where discrete data suggested a social risk referral occurred, there was no documentation of this in the note. Primary domains addressed were food insecurity (38%), financial stress (18%) and housing needs (18%). Common referral activities included providing contact information (26%), help with assistance applications (17%), and direct provision of resources (16%). Documentation indicated the patient received resources in 29% of notes.

Conclusions: EHR documentation of social risk referrals in structured data fields is inconsistent. Further work should establish best practices, especially given emerging policies that tie payments to documentation of social risk screening and intervention provision. Community health centers may struggle to use data elements such as smartphrases and procedure codes to monitor and report on their social risk referrals until standardized coding practices are established and effectively implemented.

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来源期刊
Health Services Research
Health Services Research 医学-卫生保健
CiteScore
4.80
自引率
5.90%
发文量
193
审稿时长
4-8 weeks
期刊介绍: Health Services Research (HSR) is a peer-reviewed scholarly journal that provides researchers and public and private policymakers with the latest research findings, methods, and concepts related to the financing, organization, delivery, evaluation, and outcomes of health services. Rated as one of the top journals in the fields of health policy and services and health care administration, HSR publishes outstanding articles reporting the findings of original investigations that expand knowledge and understanding of the wide-ranging field of health care and that will help to improve the health of individuals and communities.
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