Implementation of Suicide Risk Models in Health Systems

NCT ID: NCT06060535

Last Updated: 2025-12-15

Basic Information

• Recruitment Status: ENROLLING_BY_INVITATION
• Clinical Phase: NA
• Total Enrollment: 394000 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-10-04
• Study Completion Date: 2026-01-31

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.

Detailed Description

Suicide is a major public health concern in the United States; nearly 50,000 individuals die by suicide annually and almost 1.5 million attempt suicide. To date, identification of individuals at risk for suicide has relied on suicide risk screening practices, including using a variety of self-reported instruments. However, sensitivity of these measures is only moderate; more precise tools for identifying patients at risk for suicide are needed. Suicide risk models, developed by our team, incorporate health records data and historical self-report screening questionnaire responses to improve accuracy of risk prediction. Our models have outperformed traditional clinical screening and similar risk models for adults receiving care in outpatient mental health specialty settings. However, while statistically accurate, they have not been evaluated in real world care; whether the models actually increase identification or result in patients receiving more suicide prevention services, fewer crisis services, or making fewer suicide attempts is unknown. There is substantial clinical interest in implementing suicide risk models but little scientific evidence about the effectiveness of these models in real-world settings compared to standard screening practices alone. Additionally, there is almost no guidance for their implementation in healthcare. The proposed project leverages the NIMH-funded Mental Health Research Network (MHRN), a collaboration of large health systems with established clinical data infrastructure to support multi-site studies. MHRN members Henry Ford Health, Kaiser Permanente Northwest, and HealthPartners will participate in this project and collectively serve >170,000 behavioral health patients per year. The patient populations are diverse, including thousands of individuals with Medicaid and Medicare. Each of these systems has implemented a suicide prevention care model in their behavioral health departments, including robust suicide risk screening and assessment processes. However, none of these systems has implemented a suicide risk identification model. The proposed project includes a pragmatic trial approach with randomization of behavioral health clinics across the three participating health systems. It is innovative because it seeks to implement an MHRN suicide risk model (intervention) into each system's existing suicide prevention care model (usual care) to increase the reach and effectiveness of the suicide prevention care models. Sites will receive implementation planning support based on stakeholder feedback from preliminary studies and deliverables include an implementation planning tool kit to facilitate spread. This high-impact study has important clinical implications as health systems consider whether it makes sense to enhance their existing suicide prevention care models with a suicide risk model. It is timely because many health systems are advancing toward suicide risk model implementation without evidence to support this innovation.

Conditions

Suicide, Attempted; Suicide, Fatal

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: CROSSOVER
• Primary Study Purpose: PREVENTION
• Blinding Strategy: NONE

Study Groups

Usual Care

Usual care suicide prevention pathway

Group Type: ACTIVE_COMPARATOR

Suicide Attempt Risk Model Care Pathway

Intervention Type: BEHAVIORAL

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.

Intervention

Implementation of the suicide risk model

Group Type: EXPERIMENTAL

Suicide Attempt Risk Model Care Pathway

Intervention Type: BEHAVIORAL

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.

Interventions

Suicide Attempt Risk Model Care Pathway

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.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• 18+ years old
• 1+ visit to a behavioral health clinic at participating sites

Exclusion Criteria

• None

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Henry Ford Health System

OTHER

Sponsor Role: collaborator

HealthPartners Institute

OTHER

Sponsor Role: collaborator

National Institute of Mental Health (NIMH)

NIH

Sponsor Role: collaborator

Kaiser Permanente

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Bobbi Jo Yarborough, PsyD

Role: PRINCIPAL_INVESTIGATOR

Kaiser Permanente

Locations

Henry Ford Health System

Detroit, Michigan, United States

HealthPartners

Bloomington, Minnesota, United States

Kaiser Permanente Center for Health Research

Portland, Oregon, United States

Countries

United States

References

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.

Reference Type: BACKGROUND

PMID: 24567199 (View on PubMed)

Simon 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.

Reference Type: BACKGROUND

PMID: 29792051 (View on PubMed)

Hedegaard H, Curtin SC, Warner M. Increase in Suicide Mortality in the United States, 1999-2018. NCHS Data Brief. 2020 Apr;(362):1-8.

Reference Type: BACKGROUND

PMID: 32487287 (View on PubMed)

Yarborough 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.

Reference Type: BACKGROUND

PMID: 30993146 (View on PubMed)

Rossom 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.

Reference Type: BACKGROUND

PMID: 34189931 (View on PubMed)

Simon 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.

Reference Type: BACKGROUND

PMID: 31529095 (View on PubMed)

Simon 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.

Reference Type: BACKGROUND

PMID: 24036589 (View on PubMed)

Yarborough 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.

Reference Type: BACKGROUND

PMID: 33711562 (View on PubMed)

Coleman 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.

Reference Type: BACKGROUND

National Action Alliance for Suicide Prevention. A prioritized research agenda for suicide prevention: An action plan to save lives. Rockville, MD. 2014.

Reference Type: BACKGROUND

Stumbo 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.

Reference Type: DERIVED

PMID: 40200191 (View on PubMed)

Related Links

https://theactionalliance.org/sites/default/files/agenda.pdf

A Prioritized Research Agenda for Suicide Prevention: An Action Plan to Save Lives

Other Identifiers

1R01MH130548-01

Identifier Type: NIH

Identifier Source: secondary_id

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R01MH130548

Identifier Type: NIH

Identifier Source: org_study_id

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