ArticleJournal of the American Medical Informatics Association : JAMIA2023
Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations.
Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Recommended guidelines concerning artificial intelligence and health equity: a scoping review.Health affairs scholar · 2026Review
- Extracting Social Determinants of Health From Electronic Health Records: Development and Comparison of Rule-Based and Large Language Model Methods.JMIR medical informatics · 2026Article
- Comparing regular expression and machine learning approaches to predict immigrant status from primary care electronic medical record data in Ontario, Canada.PLOS digital health · 2026Article
- Safeguarding Social Determinants of Health Data at a Managed Health Plan.Advances in health information science and practice · 2026Article
- Extracting social determinants of health from electronic health records: development and comparison of rule-based and large language models-based methods.medRxiv : the preprint server for health sciences · 2025Article
- Extracting Social Determinants of Health from Dental Clinical Notes.Applied clinical informatics · 2025Article
- Patient and clinician acceptability of automated extraction of social drivers of health from clinical notes in primary care.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study.Journal of medical Internet research · 2025Article
- Advancements in extracting social determinants of health information from narrative text.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Leveraging natural language processing to augment structured social determinants of health data in the electronic health record.Journal of the American Medical Informatics Association : JAMIA · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Identifying patients' social needs is a first critical step to address social determinants of health (SDoH)-the conditions in which people live, learn, work, and play that affect health. Addressing SDoH can improve health outcomes, population health, and health equity. Emerging SDoH reporting requirements call for health systems to implement efficient ways to identify and act on patients' social needs. Automatic extraction of SDoH from clinical notes within the electronic health record through natural language processing offers a promising approach. However, such automated SDoH systems could have unintended consequences for patients, related to stigma, privacy, confidentiality, and mistrust. Using Floridi et al's "AI4People" framework, we describe ethical considerations for system design and implementation that call attention to patient autonomy, beneficence, nonmaleficence, justice, and explicability. Based on our engagement of clinical and community champions in health equity work at University of Washington Medicine, we offer recommendations for integrating patient voices and needs into automated SDoH systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.