Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach.
Suranga N KasthurirathnePaul G BiondichShaun J GrannisSaptarshi PurkayasthaJoshua R VestJosette F JonesPublished in: Journal of medical Internet research (2019)
This study demonstrates the ability to automate screening for patients in need of advanced care for depression across (1) an overall patient population or (2) various high-risk patient groups using structured datasets covering acute and chronic conditions, patient demographics, behaviors, and past visit history. Furthermore, these results show considerable potential to enable preventative care and can be easily integrated into existing clinical workflows to improve access to wraparound health care services.
Keyphrases
- healthcare
- end stage renal disease
- health information
- machine learning
- ejection fraction
- palliative care
- newly diagnosed
- case report
- chronic kidney disease
- quality improvement
- primary care
- intensive care unit
- mental health
- affordable care act
- artificial intelligence
- deep learning
- single cell
- data analysis
- human health