TY  - JOUR
PY  - 2021//
TI  - Detection of self-harm and suicidal ideation in emergency department triage notes
JO  - Journal of the American Medical Informatics Association
A1  - Witt, Katrina
A1  - Rozova, Vlada
A1  - Verspoor, Karin
A1  - Li, Yan
A1  - Robinson, Jo
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - OBJECTIVE: Accurate identification of self-harm presentations to Emergency Departments (ED) can lead to more timely mental health support, aid in understanding the burden of suicidal intent in a population, and support impact evaluation of public health initiatives related to suicide prevention. Given lack of manual self-harm reporting in ED, we aim to develop an automated system for the detection of self-harm presentations directly from ED triage notes. <br><br>MATERIALS AND METHODS: We frame this as supervised classification using natural language processing (NLP), utilizing a large data set of 477 627 free-text triage notes from ED presentations in 2012-2018 to The Royal Melbourne Hospital, Australia. The data were highly imbalanced, with only 1.4% of triage notes relating to self-harm. We explored various preprocessing techniques, including spelling correction, negation detection, bigram replacement, and clinical concept recognition, and several machine learning methods. <br><br>RESULTS: Our results show that machine learning methods dramatically outperform keyword-based methods. We achieved the best results with a calibrated Gradient Boosting model, showing 90% Precision and 90% Recall (PR-AUC 0.87) on blind test data. Prospective validation of the model achieves similar results (88% Precision; 89% Recall). <br><br>DISCUSSION: ED notes are noisy texts, and simple token-based models work best. Negation detection and concept recognition did not change the results while bigram replacement significantly impaired model performance. <br><br>CONCLUSION: This first NLP-based classifier for self-harm in ED notes has practical value for identifying patients who would benefit from mental health follow-up in ED, and for supporting surveillance of self-harm and suicide prevention efforts in the population.<p />  <p>Language: en</p>
LA  - en
SN  - 1067-5027
UR  - http://dx.doi.org/10.1093/jamia/ocab261
ID  - ref1
ER  -