Implementation of Suicide Risk Models in Health Systems
Evaluating Effectiveness and Implementation of a Risk Model for Suicide Prevention Across Health Systems
2 other identifiers
interventional
394,000
1 country
3
Brief Summary
The goal of this clinical trial is to evaluate a suicide risk model in patients receiving behavioral health care treatment. The main question it aims to answer is: Does the implementation of the suicide risk model reduce suicide attempts? Researchers will compare the outcomes of patients identified by the model to those in a usual care group.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Oct 2022
Longer than P75 for not_applicable
3 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
October 4, 2022
CompletedFirst Submitted
Initial submission to the registry
August 13, 2023
CompletedFirst Posted
Study publicly available on registry
September 29, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
January 1, 2026
CompletedStudy Completion
Last participant's last visit for all outcomes
January 1, 2026
CompletedDecember 15, 2025
October 1, 2025
3.2 years
August 13, 2023
December 11, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Suicide attempt, 90 days post-index encounter
The number and proportion of visits followed by any suicide attempt (ICD-10 diagnosis codes) occurring within 90 days of an index visit.
90 days post-index encounter
Secondary Outcomes (4)
Identification
Through study completion, an average of 18 months
Recognition
Through study completion, an average of 18 months
Evidence-based suicide care
Through study completion, an average of 18 months
Any 14-day follow-up care in behavioral health
14 days post-index encounter
Study Arms (2)
Usual Care
ACTIVE COMPARATORUsual care suicide prevention pathway
Intervention
EXPERIMENTALImplementation of the suicide risk model
Interventions
The suicide attempt risk model uses documented histories of medical and psychiatric diagnoses, medications, and health service utilization to predict risk of a suicide attempt in the 90 days following an outpatient visit in behavioral health clinics.
Eligibility Criteria
You may qualify if:
- + years old
- + visit to a behavioral health clinic at participating sites
You may not qualify if:
- None
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Henry Ford Health Systemcollaborator
- HealthPartners Institutecollaborator
- National Institute of Mental Health (NIMH)collaborator
- Kaiser Permanentelead
Study Sites (3)
Henry Ford Health System
Detroit, Michigan, 48202, United States
HealthPartners
Bloomington, Minnesota, 55425, United States
Kaiser Permanente Center for Health Research
Portland, Oregon, 97227, United States
Related Publications (11)
Ahmedani BK, Simon GE, Stewart C, Beck A, Waitzfelder BE, Rossom R, Lynch F, Owen-Smith A, Hunkeler EM, Whiteside U, Operskalski BH, Coffey MJ, Solberg LI. Health care contacts in the year before suicide death. J Gen Intern Med. 2014 Jun;29(6):870-7. doi: 10.1007/s11606-014-2767-3. Epub 2014 Feb 25.
PMID: 24567199BACKGROUNDSimon GE, Johnson E, Lawrence JM, Rossom RC, Ahmedani B, Lynch FL, Beck A, Waitzfelder B, Ziebell R, Penfold RB, Shortreed SM. Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records. Am J Psychiatry. 2018 Oct 1;175(10):951-960. doi: 10.1176/appi.ajp.2018.17101167. Epub 2018 May 24.
PMID: 29792051BACKGROUNDHedegaard H, Curtin SC, Warner M. Increase in Suicide Mortality in the United States, 1999-2018. NCHS Data Brief. 2020 Apr;(362):1-8.
PMID: 32487287BACKGROUNDYarborough BJH, Ahmedani BK, Boggs JM, Beck A, Coleman KJ, Sterling S, Schoenbaum M, Goldstein-Grumet J, Simon GE. Challenges of Population-based Measurement of Suicide Prevention Activities Across Multiple Health Systems. EGEMS (Wash DC). 2019 Apr 12;7(1):13. doi: 10.5334/egems.277.
PMID: 30993146BACKGROUNDRossom RC, Richards JE, Sterling S, Ahmedani B, Boggs JM, Yarborough BJH, Beck A, Lloyd K, Frank C, Liu V, Clinch SB, Patke LD, Simon GE. Connecting Research and Practice: Implementation of Suicide Prevention Strategies in Learning Health Care Systems. Psychiatr Serv. 2022 Feb 1;73(2):219-222. doi: 10.1176/appi.ps.202000596. Epub 2021 Jun 30.
PMID: 34189931BACKGROUNDSimon GE, Shortreed SM, Johnson E, Rossom RC, Lynch FL, Ziebell R, Penfold ARB. What health records data are required for accurate prediction of suicidal behavior? J Am Med Inform Assoc. 2019 Dec 1;26(12):1458-1465. doi: 10.1093/jamia/ocz136.
PMID: 31529095BACKGROUNDSimon GE, Rutter CM, Peterson D, Oliver M, Whiteside U, Operskalski B, Ludman EJ. Does response on the PHQ-9 Depression Questionnaire predict subsequent suicide attempt or suicide death? Psychiatr Serv. 2013 Dec 1;64(12):1195-202. doi: 10.1176/appi.ps.201200587.
PMID: 24036589BACKGROUNDYarborough BJH, Stumbo SP. Patient perspectives on acceptability of, and implementation preferences for, use of electronic health records and machine learning to identify suicide risk. Gen Hosp Psychiatry. 2021 May-Jun;70:31-37. doi: 10.1016/j.genhosppsych.2021.02.008. Epub 2021 Mar 4.
PMID: 33711562BACKGROUNDColeman KJ, Stewart CC, Bruschke C, et al. Identifying people at risk for suicide: Implementation of screening for the Zero Suicide Initiative in large health systems. Advances in Psychiatry and Behavioral Health. 2021;1(1):67-76.
BACKGROUNDNational Action Alliance for Suicide Prevention. A prioritized research agenda for suicide prevention: An action plan to save lives. Rockville, MD. 2014.
BACKGROUNDStumbo SP, Hooker SA, Rossom RC, Miley K, Ahmedani BK, Lockhart E, Yeh HH, Yarborough BJH. Study protocol for a stepped-wedge, randomized controlled trial to evaluate implementation of a suicide risk identification model among behavioral health patients in three large health systems. BMC Psychiatry. 2025 Apr 8;25(1):344. doi: 10.1186/s12888-025-06760-0.
PMID: 40200191DERIVED
Related Links
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Bobbi Jo Yarborough, PsyD
Kaiser Permanente
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- PREVENTION
- Intervention Model
- CROSSOVER
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
August 13, 2023
First Posted
September 29, 2023
Study Start
October 4, 2022
Primary Completion
January 1, 2026
Study Completion
January 1, 2026
Last Updated
December 15, 2025
Record last verified: 2025-10
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP
- Time Frame
- Materials will be shared, upon request, to interested researchers beginning 6 months after publication of the main analyses for up to one year.
- Access Criteria
- Materials will be shared with interested researchers through the MHRN website, data may be shared for secondary analyses through a secure file transfer site.
We will make our documentation, research methods and protocol, data collection tools, and a de-identified dataset of data that underlie results in publications freely available, upon request, to interested researchers beginning 6 months after publication of the main analyses. Materials will be shared through the MHRN website or a secure file transfer. Creation of a deidentified dataset for sharing may include redaction of some information to prevent re-identification or because the data is proprietary. The de-identified dataset will be available for non-commercial research use to external investigators via a data-sharing agreement and under the auspices of the Site-PIs. Users must agree to the conditions of use governing access to the data. The study team will be available for support. Information related to errors in the data, future releases, and publication lists will also be shared with users.