This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2872) Machine Learning (1780) Depression and Mood Disorders; Suicide Prevention (1541) Decision Support for Health Professionals (1367) Focus Groups and Qualitative Research for Human Factors Research (1072) Methods and New Tools in Mental Health Research (504)

Published on in Vol 6, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30946, first published .
Implementing Machine Learning Models for Suicide Risk Prediction in Clinical Practice: Focus Group Study With Hospital Providers

Implementing Machine Learning Models for Suicide Risk Prediction in Clinical Practice: Focus Group Study With Hospital Providers

Implementing Machine Learning Models for Suicide Risk Prediction in Clinical Practice: Focus Group Study With Hospital Providers

Authors of this article:

Kate H Bentley1, 2, 3 Author Orcid Image ;   Kelly L Zuromski2 Author Orcid Image ;   Rebecca G Fortgang2 Author Orcid Image ;   Emily M Madsen1, 4 Author Orcid Image ;   Daniel Kessler2 Author Orcid Image ;   Hyunjoon Lee1, 4 Author Orcid Image ;   Matthew K Nock2 Author Orcid Image ;   Ben Y Reis3, 5 Author Orcid Image ;   Victor M Castro6 Author Orcid Image ;   Jordan W Smoller1, 3, 4 Author Orcid Image
Article Authors Cited by (14) Tweetations (18) Metrics

Journals

  1. Vuscan M, Vica M, Balici S, Nicula G, Rusu S, Siserman C, Coman H, Matei H. Association of HLA class II alleles with suicidal behavior in a Transylvanian population. Revista Romana de Medicina de Laborator 2023;31(1):15 View
  2. Shortreed S, Walker R, Johnson E, Wellman R, Cruz M, Ziebell R, Coley R, Yaseen Z, Dharmarajan S, Penfold R, Ahmedani B, Rossom R, Beck A, Boggs J, Simon G. Complex modeling with detailed temporal predictors does not improve health records-based suicide risk prediction. npj Digital Medicine 2023;6(1) View
  3. Kleiman E, Glenn C, Liu R. The use of advanced technology and statistical methods to predict and prevent suicide. Nature Reviews Psychology 2023;2(6):347 View
  4. Ripperger M, Kolli J, Wilimitis D, Robinson K, Reale C, Novak L, Cunningham C, Kasuske L, Grover S, Ribeiro J, Walsh C. External Validation and Updating of a Statistical Civilian-Based Suicide Risk Model in US Naval Primary Care. JAMA Network Open 2023;6(11):e2342750 View
  5. Davis M, Dysart G, Doupnik S, Hamm M, Schwartz K, George-Milford B, Ryan N, Melhem N, Stepp S, Brent D, Young J. Adolescent, Parent, and Provider Perceptions of a Predictive Algorithm to Identify Adolescent Suicide Risk in Primary Care. Academic Pediatrics 2024 View
  6. Giddings R, Joseph A, Callender T, Janes S, van der Schaar M, Sheringham J, Navani N. Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review. The Lancet Digital Health 2024;6(2):e131 View
  7. Mortier P, Amigo F, Bhargav M, Conde S, Ferrer M, Flygare O, Kizilaslan B, Latorre Moreno L, Leis A, Mayer M, Pérez-Sola V, Portillo-Van Diest A, Ramírez-Anguita J, Sanz F, Vilagut G, Alonso J, Mehlum L, Arensman E, Bjureberg J, Pastor M, Qin P. Developing a clinical decision support system software prototype that assists in the management of patients with self-harm in the emergency department: protocol of the PERMANENS project. BMC Psychiatry 2024;24(1) View
  8. Hibi A, Cusimano M, Bilbily A, Krishnan R, Tyrrell P. Impact of Automated Prognostication on Traumatic Brain Injury Care: A Focus Group Study. Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 2024;51(6):819 View
  9. Adams R, Haroz E, Rebman P, Suttle R, Grosvenor L, Bajaj M, Dayal R, Maggio D, Kettering C, Goklish N. Developing a suicide risk model for use in the Indian Health Service. npj Mental Health Research 2024;3(1) View
  10. O’Reilly L, Fazel S, Rickert M, Kuja-Halkola R, Cederlöf M, Hellner C, Larsson H, Lichtenstein P, D’Onofrio B. Evaluating Machine Learning for Predicting Youth Suicidal Behavior up to 1 Year After Contact With Mental-Health Specialty Care. Clinical Psychological Science 2025;13(3):614 View
  11. Bentley K, Kennedy C, Khadse P, Brooks Stephens J, Madsen E, Flics M, Lee H, Smoller J, Burke T. Clinician Suicide Risk Assessment for Prediction of Suicide Attempt in a Large Health Care System. JAMA Psychiatry 2025;82(6):599 View
  12. Horowitz L, Lowry N, Shi T, Merai R, Pao M, Bridge J. Detecting Suicide Risk Among Pediatric Patients: Screening, Clinical Pathways, and Care. Annual Review of Clinical Psychology 2025;21(1):305 View
  13. Dayal R, Yang P, Sisson L, Bajaj M, Archuleta S, Yao S, Park H, Fujii-Rios H, Haroz E. Exploring the perspectives of pediatric healthcare providers, youth patients, and caregivers on machine learning suicide risk classification using a mixed-methods approach (Preprint). Journal of Medical Internet Research 2024 View

Books/Policy Documents

  1. Salgado-Baez E, Näher A, Friedrich M, Kremser G, Braune K, Balzer F. Health Data Management. View