Measuring Use of Evidence Based Psychotherapy for Posttraumatic Stress Disorder in a Large National Healthcare System.
Shira MaguenErin MaddenOlga V PattersonScott L DuVallLizabeth A GoldsteinKristine BurkmanBrian ShinerPublished in: Administration and policy in mental health (2019)
To derive a method of identifying use of evidence-based psychotherapy (EBP) for post-traumatic stress disorder (PTSD), we used clinical note text from national Veterans Health Administration (VHA) medical records. Using natural language processing, we developed machine-learning algorithms to classify note text on a large scale in an observational study of Iraq and Afghanistan veterans with PTSD and one post-deployment psychotherapy visit by 8/5/15 (N = 255,968). PTSD visits were linked to 8.1 million psychotherapy notes. Annotators labeled 3467 randomly-selected psychotherapy notes (kappa = 0.88) to indicate receipt of EBP. We met our performance targets of overall classification accuracy (0.92); 20.2% of veterans received ≥ one session of EBP over the study period. Our method can assist with identifying EBP use and studying EBP-associated outcomes in routine clinical practice.
Keyphrases
- posttraumatic stress disorder
- machine learning
- clinical practice
- healthcare
- deep learning
- quality improvement
- public health
- smoking cessation
- artificial intelligence
- autism spectrum disorder
- mental health
- nuclear factor
- big data
- adipose tissue
- metabolic syndrome
- inflammatory response
- toll like receptor
- computed tomography
- transcranial direct current stimulation
- risk assessment
- health information
- immune response
- social media
- high intensity
- borderline personality disorder
- tyrosine kinase
- weight loss