Clinical trial NCT06060535: Implementation of Suicide Risk Models in Health Systems
Official title: Evaluating Effectiveness and Implementation of a Risk Model for Suicide Prevention Across Health Systems
Study type: INTERVENTIONAL
Overall status: ENROLLING_BY_INVITATION
Phase: NA
Conditions: Suicide, Attempted
Suicide, Fatal
Lead sponsor: Kaiser Permanente
Sponsor class: OTHER
Collaborators: name: Henry Ford Health System
name: HealthPartners Institute
name: National Institute of Mental Health (NIMH)
First posted: 2023-09-29
Enrollment: 394000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Intervention model description: Clinics are the unit of randomization, all behavioral health clinics will be randomized, over the course of three waves, to cross over from usual care to intervention (implementation of the suicide risk model).
Primary purpose: PREVENTION

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.

Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

* None

Primary outcomes:
measure: Suicide attempt, 90 days post-index encounter
timeFrame: 90 days post-index encounter
Secondary outcomes:
measure: Identification
timeFrame: Through study completion, an average of 18 months
measure: Recognition
timeFrame: Through study completion, an average of 18 months
measure: Evidence-based suicide care
timeFrame: Through study completion, an average of 18 months
measure: Any 14-day follow-up care in behavioral health
timeFrame: 14 days post-index encounter
Other outcomes:
Locations:
city: Detroit
country: United States
facility: Henry Ford Health System
state: Michigan
city: Bloomington
country: United States
facility: HealthPartners
state: Minnesota
city: Portland
country: United States
facility: Kaiser Permanente Center for Health Research
state: Oregon
Study officials:
affiliation: Kaiser Permanente
name: Bobbi Jo Yarborough, PsyD
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.
citation: Hedegaard H, Curtin SC, Warner M. Increase in Suicide Mortality in the United States, 1999-2018. NCHS Data Brief. 2020 Apr;(362):1-8.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: National Action Alliance for Suicide Prevention. A prioritized research agenda for suicide prevention: An action plan to save lives. Rockville, MD. 2014.