Using Z Codes to Document Social Risk Factors in the Electronic Health Record: A Scoping Review

Kelley M Baker; Mary A Hill; Debora G Goldberg; Panagiota Kitsantas; Kristen E Miller; Kelly M Smith; Alicia Hong

doi:10.1097/MLR.0000000000002101

Using Z Codes to Document Social Risk Factors in the Electronic Health Record: A Scoping Review

Med Care. 2024 Nov 15. doi: 10.1097/MLR.0000000000002101. Online ahead of print.

Authors

Kelley M Baker¹, Mary A Hill^{2

3}, Debora G Goldberg¹, Panagiota Kitsantas¹, Kristen E Miller⁴, Kelly M Smith^{2

3}, Alicia Hong¹

Affiliations

¹ Department of Health Administration and Policy, College of Public Health, George Mason University, Fairfax, VA.
² Department of Patient-Oriented Research, Michael Garron Hospital, Toronto, ON, Canada.
³ Institute for Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
⁴ National Center for Human Factors in Healthcare, MedStar Health Research Institute, Washington, DC.

PMID: 39570573
DOI: 10.1097/MLR.0000000000002101

Abstract

Introduction: Individual-level social risk factors have a significant impact on health. Social risks can be documented in the electronic health record using ICD-10 diagnosis codes (the "Z codes"). This study aims to summarize the literature on using Z codes to document social risks.

Methods: A scoping review was conducted using the PubMed, Medline, CINAHL, and Web of Science databases for papers published before June 2024. Studies were included if they were published in English in peer-reviewed journals and reported a Z code utilization rate with data from the United States.

Results: Thirty-two articles were included in the review. In studies based on patient-level data, patient counts ranged from 558 patients to 204 million, and the Z code utilization rate ranged from 0.4% to 17.6%, with a median of 1.2%. In studies that examined encounter-level data, sample sizes ranged from 19,000 to 2.1 billion encounters, and the Z code utilization rate ranged from 0.1% to 3.7%, with a median of 1.4%. The most reported Z codes were Z59 (housing and economic circumstances), Z63 (primary support group), and Z62 (upbringing). Patients with Z codes were more likely to be younger, male, non-White, seeking care in an urban teaching facility, and have higher health care costs and utilizations.

Discussion: The use of Z codes to document social risks is low. However, the research interest in Z codes is growing, and a better understanding of Z code use is beneficial for developing strategies to increase social risk documentation, with the goal of improving health outcomes.