Evaluating Effectiveness and Implementation of a Risk Model for Suicide Prevention Across Health Systems

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.