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Cited by 79Medical Coding and Health InformationElectronic Health Records SystemsNursing Diagnosis and Documentation

The adoption of social determinants of health documentation in clinical settings

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Kepper, Maura M., Walsh‐Bailey, Callie, Prusaczyk, Beth, Zhao, Min, Herrick, Cynthia, Foraker, Randi·2023·Health Services Research
DOI 10.1111/1475-6773.14039PMC PMC9836948
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Abstract

Objective: To understand the frequency of social determinants of health (SDOH) diagnosis codes (Z‐codes) within the electronic health record (EHR) for patients with prediabetes and diabetes and examine factors influencing the adoption of SDOH documentation in clinical care. Data Sources: EHR data and qualitative interviews with health care providers and stakeholders. Study Design: An explanatory sequential mixed methods design first examined the use of Z‐codes within the EHR and qualitatively examined barriers to documenting SDOH. Data were integrated and interpreted using a joint display. This research was informed by the Framework for Dissemination and Utilization of Research for Health Care Policy and Practice. Data Collection/Extraction Methods: We queried EHR data for patients with a hemoglobin A1c > 5.7 between October 1, 2015 and September 1, 2020 ( n = 118,215) to examine the use of Z‐codes and demographics and outcomes for patients with and without social needs. Semi‐structured interviews were conducted with 23 participants ( n = 15 health care providers; n = 7 billing and compliance stakeholders). The interview questions sought to understand how factors at the innovation‐, individual‐, organizational‐, and environmental‐level influence SDOH documentation. We used thematic analysis to analyze interview data. Principal Findings: Patients with social needs were disproportionately older, female, Black, uninsured, living in low‐income and high unemployment neighborhoods, and had a higher number of hospitalizations, obesity, prediabetes, and type 2 diabetes than those without a Z‐code. Z‐codes were not frequently used in the EHR (<1% of patients), and there was an overall lack of congruence between quantitative and qualitative results related to the prevalence of social needs. Providers faced barriers at multiple levels (e.g., individual‐level: discomfort discussing social needs; organizational‐level: limited time, competing priorities) for documenting SDOH and identified strategies to improve documentation. Conclusions: Providers recognized the impact of SDOH on patient health and had positive perceptions of screening for and documenting social needs. Implementation strategies are needed to improve systematic documentation.

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  • In clinical practice, there has been a lack of systematic collection and analysis of SDoH defined in the EHRs.

    “In clinical practice, there has been a lack of systematic collection and analysis of SDoH defined in the EHRs15–17.”

    From Social determinants of health extraction from clinical notes across institutions using large language models (2025) · cites this paper as [16]

    The Discussion reports low use of EHR Z-codes and says providers were not systematically using SDOH screeners or documenting social needs. This supports a lack of systematic collection and documentation, but the paper does not establish a lack of systematic analysis of SDOH data. Its findings also come from a single academic health system, limiting the broader claim about clinical practice. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • The literature on social risk factor documentation is hampered by a lack of data about the true prevalence of social risks in the clinical populations being studied.

    “But this literature is hampered by a lack of data about the true prevalence of social risks in the clinical populations being studied.[6][7][8][9]”

    From Structured and unstructured social risk factor documentation in the electronic health record underestimates patients’ self-reported risks (2024) · cites this paper as [8]

    The Discussion (page not available) says the study could not distinguish patients without social needs from those whose needs were undocumented or recorded outside Z-codes. That supports uncertainty about the true prevalence in this study’s clinical population, but the paper does not establish that the literature generally lacks such data. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Understanding the demographic and clinical characteristics of cancer patients with and without Z code claims will help generate appropriate hypotheses regarding the relationship between SDOH and outcomes, and enhance data collection strategies.

    “Understanding the demographic and clinical characteristics of cancer patients with and without Z code claims will help generate appropriate hypotheses regarding the relationship between SDOH and outcomes, and enhance data collection strategies19.”

    From Documentation of individual-level social determinants of health among adults diagnosed with cancer in the United States (2025) · cites this paper as [19]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • Documented Z codes available in claims may reflect out-of-date or inaccurate information related to the current or historical relevance of the SDOH factor from the patient's perspective.

    “Second, documented Z codes available in claims may reflect out-of-date or inaccurate information related to the current or historical relevance of the SDOH factor from the patient’s perspective19.”

    From Documentation of individual-level social determinants of health among adults diagnosed with cancer in the United States (2025) · cites this paper as [19]

    In Results §3.5 (page unavailable), providers worry that documented SDOH information may become outdated or incorrect, remain in the chart after a need resolves, and be disputed by the patient. This supports the concern about current relevance from the patient’s perspective, but the passage concerns EHR documentation rather than Z codes available in claims; the paper does not establish that claims-specific point. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Healthcare providers in endocrinology and key stakeholders acknowledged the impact of SDOH on patients' health but reported barriers at multiple levels when documenting SDOH.

    “Kepper et al. interviewed healthcare providers in endocrinology and key stakeholders, who acknowledged the impact of SDOH on patients’ health. However, they reported barriers at multiple levels when documenting SDOH19.”

    From Documentation of individual-level social determinants of health among adults diagnosed with cancer in the United States (2025) · cites this paper as [19]

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Cited by

Sorted by citations

Authors
Kepper, M. M., Walsh‐Bailey, C., Prusaczyk, B., Zhao, M., Herrick, C., & Foraker, R.
Affiliations
Washington University in St. Louis (US)
Corresponding author
Kepper, Maura M.
ORCID
Venue
Health Services Research
Publisher
Wiley
Published
2022-07-31
Volume
58
Issue
1
Pages
67-77
ISSN
  • 0017-9124 (ISSN-L)
  • 1475-6773
DOI
10.1111/1475-6773.14039
PMC
PMC9836948
OpenAlex
W4286489826
Cited by
79
References
4
Citations by year
2026: 19 · 2025: 23 · 2024: 15 · 2023: 20 · 2022: 2
FWCI
11.23
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Health Services Research (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Centers for Disease Control and Prevention (U48DP006395)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (K23HD096204)
  • National Heart, Lung, and Blood Institute (K12HL137942)
  • National Institute of Diabetes and Digestive and Kidney Diseases (P30DK092950)
  • National Institute on Minority Health and Health Disparities (T37 MD014218)
Topics
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
Keywords
social determinants of health, Z codes, electronic health records, prediabetes, type 2 diabetes, health disparities, health care utilization, implementation strategies, social needs screening
MeSH terms
Diabetes Mellitus, Type 2, Documentation, Female, Humans, Prediabetic State, Electronic Health Records, Social Determinants of Health

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