Face-to-face screenings, electronic health record-based machine learning algorithms, or a combination of both: which provides greater health benefit when discussing suicide prevention?
In his new JAMA Network Open article, “Suicide Risk Prediction in Clinical Settings—Additional Considerations for Face-to-Face Screening and Machine Learning Approaches,” GSS Associate Professor Dr. Jordan DeVylder assesses a previous work on the JAMA Network Open platform done by Wilimitis and colleagues which set out to answer this very question, while also providing some additional insights.
DeVylder summarizes the advantages and disadvantages of both face-to-face screening and machine-learning, citing patient denial as an issue for the former, and privacy concerns as an issue for the latter.
“Wilimitis and colleagues have provided us with valuable data on the potential benefits of a combined approach, which can now be weighed against some of these other considerations to determine the best approach for a particular clinical setting.”
