Investigating the differential impact of psychosocial factors by patient characteristics and demographics on Veteran suicide risk through machine learning extraction of cross-modal interactions

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 …

Predictive accuracy of Natural Language Processing extracted 3-Step Theory of Suicide factor scores derived from Veterans' clinical progress notes

Abstract: OBJECTIVES: To compare predictive accuracy of 3-step theory of suicide (3ST) factor scores derived from natural language processing of Veterans Health Administration …

Development and validation of case-finding algorithms to identify periprosthetic joint infections after total hip arthroplasty in Veterans Health Administration data

Abstract: Purpose: To determine the positive predictive values (PPVs) of ICD-9- and ICD-10-based diagnostic coding algorithms to identify periprosthetic joint infection (PJI) …

Use of machine learning for early prediction of short-term mortality in Veterans with metabolic dysfunction-associated steatotic liver disease

Abstract: Background: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States …

Association between herpes zoster and risk of incident fragility fractures in US Veterans: A matched cohort study

Abstract: Background: Herpes zoster (HZ) and fragility fractures typically affect older adults and present major burdens to healthcare systems. While HZ is associated with an …

Provider perspectives on care for Veterans with electronic health record flags for high suicide risk: A mixed methods study

Abstract: Electronic health record (EHR) flags alert staff within the Veteran Health Administration (VHA) to patients at high suicide risk for the purpose of enhancing their care. …

Incidence and prevalence of polycystic ovary syndrome in adolescent and young adult US military dependents from 2018 to 2022

Abstract: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among people who menstruate. Adolescent and young adult (AYA) military dependents, a large, diverse …

Incidence and prevalence of polycystic ovary syndrome in adolescent and young adult US military dependents from 2018-2022

Abstract: Study Objective: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among people who menstruate. Adolescent and young adult (AYA) military dependents, …

Reliable symptom worsening among Veterans receiving cognitive processing therapy or prolonged exposure therapy for posttraumatic stress disorder in routine Veterans Health Administration care

Abstract: Clinical practice guidelines recommend trauma-focused evidence-based psychotherapy (EBP) to treat posttraumatic stress disorder (PTSD). Some veterans and clinicians …

Comparing major comorbidity indices as predictors of all-cause mortality in the Veterans Affairs healthcare system

Abstract: Objective: The Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Index (ECI), and the Functional Comorbidity Index (FCI) are validated clinical measures of …

Comparison of health measures between survey self-reports and electronic health records among Millennium Cohort Study participants receiving Veterans Health Administration care

Abstract: Background: Surveys are a useful tool for eliciting self-reported health information, but the accuracy of such information may vary. We examined the agreement between …

Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large Veterans affairs population

Abstract: Objective: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic …