aceExtraction of Pain Severity and Functional Interference From Clinical Narratives Using Domain-Informed Large Language Models: Protocol for a Development and Validation Study
Background Chronic pain is a leading cause of disability and requires multidimensional assessment of pain intensity and functioning, yet electronic health records rarely capture these measures systematically. By contrast, surveys collecting patient-reported outcomes can assess pain over multiple dimensions but remain resource-intensive and difficult to scale for continuous population-level monitoring. Objective The objective of this study is to develop and validate a domain-informed natural language processing f…
Language models may let health systems track pain severity and functional interference from existing clinical notes instead of relying on resource-intensive patient surveys, though this is not yet validated.
This is a protocol with expert validation still in progress, and final results from the knowledge distillation and validation stages are not expected until the first half of 2027, so accuracy is not yet established.
Evidence
- Peer-reviewedJMIR Research Protocols2026-10-07
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Truvace Impact Record TRV-2026-1762, v1: “Extraction of Pain Severity and Functional Interference From Clinical Narratives Using Domain-Informed Large Language Models: Protocol for a Development and Validation Study.” Truvace, 2026-10-18. /record/TRV-2026-1762 (accessed at citation time). sha256 c313524431241545…
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