Protocol for Designing a Model to Predict the Likelihood of Psychosis From Electronic Health Records Using Natural Language Processing and Machine Learning.

Introduction: Rapid identification of individuals developing a psychotic spectrum disorder (PSD) is crucial because untreated psychosis is associated with poor outcomes and decreased treatment response. Lack of recognition of early psychotic symptoms often delays diagnosis, further worsening these outcomes.

Methods: The proposed study is a cross-sectional, retrospective analysis of electronic health record data including clinician documentation and patient-clinician secure messages for patients aged 15-29 years with ≥ 1 primary care encounter between 2017 and 2019 within 2 Kaiser Permanente regions.

Improved Survival of Advanced-Stage Anaplastic Thyroid Cancer With Systemic Therapy.

Objectives: Anaplastic thyroid cancer (ATC) is the most aggressive and fatal thyroid malignancy. Currently, there still exists a paucity of literature studying the relationship between available ATC-targeted therapy, immunotherapy, and survival. We aim to investigate how systemic therapies affect survival outcomes in ATC.

Risk Factors for Incident Polycystic Ovary Syndrome Diagnosis.

While highly prevalent, risk factors for incident polycystic ovary syndrome (PCOS) are poorly delineated. Using a population-based cohort, we sought to identify predictors of incident PCOS diagnosis. A matched case-control analysis was completed utilizing patients enrolled in Kaiser Permanente Washington from 2006 to 2019.

Improving physical activity among prostate cancer survivors through a peer-based digital walking program.

Physical activity is important for prostate cancer survivors. Yet survivors face significant barriers to traditional structured exercise programs, limiting engagement and impact. Digital programs that incorporate fitness trackers and peer support via social media have potential to improve the reach and impact of traditional support.