The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines. Veterans who receive care from both VA and non-VA providers-known as dual-system users-have an inc...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
39670369
Accurate prediction of suicide risk is crucial for identifying patients with elevated risk burden, helping ensure these patients receive targeted care. The US Department of Veteran Affairs' suicide prediction model primarily leverages structured elec...
Journal of the American Medical Informatics Association : JAMIA
39530748
OBJECTIVE: Access to firearms is associated with increased suicide risk. Our aim was to develop a natural language processing approach to characterizing firearm access in clinical records.
Clinical orthopaedics and related research
39360774
BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tiss...
BACKGROUND: Literature on how to translate information extracted from clinical progress notes into numeric scores for 3-step theory of suicide (3ST) factors is nonexistent. We determined which scoring option would best discriminate between patients w...
OBJECTIVE: Substance use disorder (SUD) is clinically under-detected and under-documented. We built and validated machine learning (ML) models to estimate SUD prevalence from electronic health record (EHR) data and to assess variation in facility-lev...
Journal of psychopathology and clinical science
40111824
Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use an...
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
OBJECTIVES: To demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns.
BACKGROUND: The use of patient-reported outcome measures (PROMs) is an expected component of high-quality, measurement-based chiropractic care. The largest health care system offering integrated chiropractic care is the Veterans Health Administration...