This paper is in the following e-collection/theme issue:

Machine Learning (1811) Diabetes (234) Diabetes (234) Diabetes-specific EHR Improvements (34) Electronic Health Records (1211) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (659) Diabetes-specific EHR Improvements (34) Electronic Health Records (1211) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (659)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46159, first published .
Social Determinants of Health Documentation in Structured and Unstructured Clinical Data of Patients With Diabetes: Comparative Analysis

Social Determinants of Health Documentation in Structured and Unstructured Clinical Data of Patients With Diabetes: Comparative Analysis

Social Determinants of Health Documentation in Structured and Unstructured Clinical Data of Patients With Diabetes: Comparative Analysis

Authors of this article:

Shivani Mehta1 Author Orcid Image ;   Courtney R Lyles1, 2, 3, 4 Author Orcid Image ;   Anna D Rubinsky5 Author Orcid Image ;   Kathryn E Kemper1 Author Orcid Image ;   Judith Auerbach6 Author Orcid Image ;   Urmimala Sarkar2, 3 Author Orcid Image ;   Laura Gottlieb7 Author Orcid Image ;   William Brown III1, 2, 4, 8, 9 Author Orcid Image
Article Authors Cited by (8) Tweetations (4) Metrics

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  2. Roy S, Morrell S, Zhao L, Homayouni R. Large-scale identification of social and behavioral determinants of health from clinical notes: comparison of Latent Semantic Indexing and Generative Pretrained Transformer (GPT) models. BMC Medical Informatics and Decision Making 2024;24(1) View
  3. Gregory M, Kasthurirathne S, Magoc T, McNamee C, Harle C, Vest J. Development and validation of computable social phenotypes for health-related social needs. JAMIA Open 2024;8(1) View
  4. Kim M, Miramontes S, Mehta S, Schwartz G, Kim Y, Yang Y, Hill‐Jarrett T, Cevallos N, Chen R, Glymour M, Ferguson E, Zimmerman S, Choi M, Sims K. Extracting Housing and Food Insecurity Information From Clinical Notes Using cTAKES. Health Services Research 2025;60(S3) View
  5. Dankovchik J, Gold R, Ochoa A, Donovan J, Gunn R, Morrissey S, Huebner Torres C, Mossman N, Berkowitz S. Identification of Social Risk‐Related Referrals in Discrete Primary Care Electronic Health Record Data: Lessons Learned From a Novel Methodology. Health Services Research 2025;60(S3) View
  6. Nimri R, Phillip M, Clements M, Kovatchev B. Closed-Loop, Artificial Intelligence-Based Decision Support Systems, and Data Science. Diabetes Technology & Therapeutics 2025;27(S1):S64 View
  7. Morrissey S, Bunce A, Donovan J, McGrath B, Gottlieb L, Pisciotta M, Watkins S, Gold R. Applying Realist Retroduction to EHR-Based Clinical Decision Support Tool Development. International Journal of Qualitative Methods 2025;24 View
  8. Decker H, Wick E. Homelessness Research Has a Data Problem. Annals of Surgery 2025;281(6):906 View