aceDetecting Language-Related Disparities in Spiritual Care Using Artificial Intelligence
Introduction: Language barriers perpetuate health care disparities, yet traditional data sources overlook inequities in relationship‑based care. This study uses artificial intelligence to examine language‑related disparities in spiritual care, a domain largely documented in unstructured clinical notes. Methods: We analyzed electronic health records of 7,360 deceased adults aged ≥65 years from a tertiary hospital (2010-2023). Natural language processing identified spiritual care documentation, and structured flow…
Natural language processing of unstructured clinical notes found language-based inequities in spiritual care that structured data alone did not capture.
The data come from a single tertiary hospital and cover only deceased adults aged 65 and older, which limits how far the findings generalize to other patients and settings.
Evidence
- Peer-reviewedJournal of Transcultural Nursing2026-10-20
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Truvace Impact Record TRV-2026-2091, v1: “Detecting Language-Related Disparities in Spiritual Care Using Artificial Intelligence.” Truvace, 2026-10-21. /record/TRV-2026-2091 (accessed at citation time). sha256 7be515f9cf2342e9…
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