Social risk factor documentation in emergency departments
Open accessAbstract
STUDY OBJECTIVE: Social Z codes are International Classification of Diseases, Tenth Revision, Clinical Modification codes that provide one way of documenting social risk factors in electronic health records. Despite the utility and availability of these codes, no study has examined social Z code documentation prevalence in emergency department (ED) settings. METHODS: In this descriptive, cross-sectional study of all ED visits included in the 2018 Nationwide Emergency Department Sample, we estimated the prevalence of social Z code documentation and used logistic regression to examine the association between documentation and patient and hospital characteristics. RESULTS: Of more than 35.8 million adult and pediatric ED visits, there was a 1.21% weighted prevalence (n=452,499) of at least 1 documented social Z code. Social Z codes were significantly more likely to be documented in ED visits among patients aged 35 to 64 compared to patients aged 18 to 34 (18.6/1000 [16.9 to 20.4] versus 12.7/1000 [11.5 to 14.0], odds ratio (OR) 1.47 [1.42 to 1.53]), male patients (16.6/1000 [15.1 to 18.2] versus female 8.5/1000 [7.8 to 9.2], OR 1.97 [1.89 to 2.06]), patients with Medicaid compared to patients with private insurance (15.9/1000 [14.4 to 17.6] versus (6.6/1000 [6.0 to 7.2], OR 2.45 [1.30 to 1.63]), and patients who had a Charlson Comorbidity Index≥1 compared to those with a Charlson Comorbidity Index of 0 (ranges 15.0 to 16.6/1000 versus 10.6/1000 [9.6 to 11.7], ORs ranging 1.43 to 1.58). ED visits with a primary diagnosis of mental, behavioral, and neurodevelopmental illness had the strongest positive association with social Z code documentation (85.6/1000 [78.4 to 93.4], OR 10.75 [9.88 to 11.70]) compared to ED visits without this primary diagnosis. CONCLUSION: We found a very low prevalence of social Z code documentation in ED visits nationwide. More systematic social Z code documentation could support targeted social interventions, social risk payment adjustments, and future policy reforms.
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Prior work investigating social risk factor documentation using ICD-10 codes has suggested that these codes are underutilized, and one study found that ICD codes were used less frequently to document social risk factors when compared to note narratives (unstructured data).
“Prior work investigating social risk factor documentation using International Statistical Classification of Diseases and Related Health Problems (ICD-10) codes, specifically, has suggested that these codes are underutilized, 3,4 and 1 study found that ICD codes were used less frequently to document social risk factors when compared to note narratives (unstructured data).5”
From Structured and unstructured social risk factor documentation in the electronic health record underestimates patients’ self-reported risks (2024) · cites this paper as [3]
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Part II: a qualitative study of social risk screening acceptability in patients and caregivers
Byhoff, E., De Marchis, E. H., Hessler, D., Fichtenberg, C., Adler, N., Cohen, A. J., Doran, K. M., Ettinger de Cuba, S., Fleegler, E. W., Gavin, N., et al. (2019) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2019.07.016 · Cited by 255 · see citing works
Self-citationTruong, H. P., Luke, A. A., Hammond, G., Wadhera, R. K., Reidhead, M., & Joynt Maddox, K. E. (2020) · Medical Care · doi:10.1097/mlr.0000000000001418 · Cited by 203 · see citing works
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Research works printed but not linked: 19
- Alderwick H, Hood-Ronick CM, Gottlieb LM. Medicaid investments to address social needs in Oregon and California. Health Aff (Millwood). 2019;38:774-781.
- Tripoli S, Fishman E, Hewitt A, et al. To advance health equity, federal policy makers should build on lessons from state Medicaid experiments. Health Aff. Accessed November 14, 2021. https://www.healthaffairs. org/do/10.1377/hblog20210409.908010/full/ · DOI
- Bleser W, Shen H, Crook H, et al. Pandemic-driven health policies to address social needs and health equity. Health Affairs Brief. Accessed May 19, 2022. https://www.healthaffairs.org/do/10.1377/ hpb20220210.360906/full/ · DOI
- National Academies of Sciences E and Medicine. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health. Washington: National Academies Press; 2019.
- Cartier Y, Gottlieb L. The prevalence of social care in US health care settings depends on how and whom you ask. BMC Health Serv Res. 2020;20:481.
- Cantor MN, Thorpe L. Integrating data on social determinants of health into electronic health records. Health Aff (Millwood). 2018;37:585-590.
- Jaffery J, Safran D. Addressing social risk factors in value-based payment: adjusting payment not performance to optimize outcomes and fairness | Health Affairs Forefront. Accessed May 27, 2022. https:// www.healthaffairs.org/do/10.1377/forefront.20210414.379479/full/ · DOI
- Torres JM, Lawlor J, Colvin JD, et al. ICD social codes: an underutilized resource for tracking social needs. Med Care. 2017;55:810-816.
- Guo Y, Chen Z, Xu K, et al. International Classification of Diseases, Tenth Revision, Clinical Modification social determinants of health codes are poorly used in electronic health records. Medicine (Baltimore). 2020;99:e23818-e23819.
- McCormack LA, Madlock-Brown C. Social determinant of health documentation trends and their association with emergency department admissions. AMIA Annu Symp Proc. 2020;2020:823-832.
- Molina MF, Li CN, Manchanda EC, et al. Prevalence of emergency department social risk and social needs. West J Emerg Med. 2020;21:152-161.
- Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43:1130-1139.
- Bibbins-Domingo K. Integrating social care into the delivery of health care. JAMA. 2019;322:1763-1764.
- Greenwood-Ericksen MB, Kocher K. Trends in emergency department use by rural and urban populations in the United States. JAMA Netw Open. 2019;2:e191919-e191920.
- Pantell MS, Kaiser SV, Torres JM, et al. Associations between social factor documentation and hospital length of stay and readmission among children. Hosp Pediatr. 2020;10:12-19.
- Gottlieb L, Tobey R, Cantor J, et al. Integrating social and medical data to improve population health: opportunities and barriers. Health Aff (Millwood). 2016;35:2116-2123.
- Coben JH, Steiner CA, Barrett M, et al. Completeness of cause of injury coding in healthcare administrative databases in the United States, 2001. Inj Prev. 2006;12:199-201.
- Wallace AS, Luther BL, Sisler SM, et al. Integrating social determinants of health screening and referral during routine emergency department care: evaluation of reach and implementation challenges. Implement Sci Commun. 2021;2:114.
- Hamity C, Jackson A, Peralta L, et al. Perceptions and experience of patients, staff, and clinicians with social needs assessment. Perm J. 2018;22:18-105.
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Iott, B. E., Rivas, S., Gottlieb, L. M., Adler-Milstein, J., & Pantell, M. S. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocad261 · Cited by 17 · see citing works
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- Authors
- Molina, M. F., Pantell, M. S., & Gottlieb, L. M.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Molina, Melanie F.
- Venue
- Annals of Emergency Medicine
- Publisher
- Elsevier BV
- Published
- 2023-01
- Volume
- 81
- Issue
- 1
- Pages
- 38-46
- ISSN
- 0196-0644 (ISSN-L)
- OpenAlex
- W4303021236
- Cited by
- 10
- References
- 2
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 4 · 2023: 2
- FWCI
- 1.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Annals of Emergency Medicine (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- social risk factors, emergency department documentation, electronic health records, social determinants of health, Medicaid, Charlson Comorbidity Index, mental health diagnoses, patient demographics, Nationwide Emergency Department Sample, ICD-10-CM coding, hospital characteristics, quality improvement, patient engagement
- MeSH terms
- Adult, Child, Cross-Sectional Studies, Emergency Service, Hospital, Female, Humans, Male, Medicaid, Risk Factors, United States, International Classification of Diseases
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