Real-World Evaluation of an Automated Algorithm to Detect Patients With Potentially Undiagnosed Hypertension Among Patients With Routine Care in Hawai'i.
Mika D ThompsonYan Yan WuBlythe NettLance K ChingHermina TaylorTiffany LemmenTetine Lynn SentellMeghan D McGurkCatherine M PirklePublished in: Journal of the American Heart Association (2023)
This evaluation provided evidence that a clinical algorithm implemented within a large health system's electronic health records could detect patients in need of follow-up to determine hypertension status, and it identified key individual characteristics, clinical and health system factors, and timing considerations that may contribute to undiagnosed hypertension among patients receiving routine care.
Keyphrases
- blood pressure
- electronic health record
- healthcare
- end stage renal disease
- palliative care
- machine learning
- clinical practice
- ejection fraction
- deep learning
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- clinical decision support
- affordable care act
- arterial hypertension
- neural network
- chronic pain