Optimizing Care to Prevent Diabetes and Promote Cardiovascular Health Among Younger Adults with Severe Mental Illness

Grant Details

Funder: NIMH

Grant number: 1K23MH126078

Grant period: 4/1/2022 – 3/31/2027

Brief narrative: People with severe mental illness (SMI) face double the risk for type 2 diabetes compared to the general population, contributing to higher rates of cardiovascular disease and premature death. Common use of antipsychotic medications contributes to these health risks due to prevalent metabolic side effects. Many younger adults with SMI do not receive targeted, evidence-based cardiometabolic disease prevention care. Underused strategies include: prescribing alternative, less obesogenic psychotropic medications; lifestyle change supports; additional risk-reducing medications; and smoking cessation therapies. Our preliminary qualitative data with patients and clinicians identified a need for tools to match prevention care to individuals’ risk level and preferences, and tools suited to population-based care strategies. Clinical Decision Support (CDS) tools are computer algorithms that use patients’ data, predictive analytics, and clinical guidelines to promote evidence-based care by helping patients and clinicians navigate complex treatment decisions. Through this mentored K23 career development award, Esti Iturralde, PhD will build upon her background as a clinical psychologist and behavioral diabetes researcher. Through planned mentoring, coursework, and career development activities, Dr. Iturralde will gain a strong understanding of psychopharmacology and cardiometabolic health, advanced predictive analytics, and implementation science, including methods for stakeholder-engaged intervention design and pragmatic clinical trials. As a researcher in the Kaiser Permanente Northern California (KPNC) Division of Research (DOR), she will leverage robust, longitudinal electronic health record (EHR) data (> 50,000 adults from diverse racial/ethnic groups) and stakeholder insights (patients, clinicians, and health system decision-makers) within health systems including KPNC and 2 others belonging to the NIMH-funded Mental Health Research Network (HealthPartners Institute and Henry Ford Health System). The proposed research will support the training goals while contributing to the development of a novel CDS tool seeking to increase targeted, evidence-based diabetes and cardiovascular disease prevention care for adults under age 45 who are starting antipsychotic medications. Specific research aims are to: (1) inform predictive analytics of the CDS tool by developing and validating diabetes risk prediction models for the target population; (2) engage stakeholders in the design of CDS tool messaging and implementation pathways; and field-test CDS tool messaging through a pragmatic clinical trial conducted within an existing KPNC telehealth-based population management program serving this population. A future R01 application will build on the results from this project to further refine and test the CDS tool within multiple health systems. The linked research and training aims will directly prepare Dr. Iturralde for success as an embedded health system researcher and prepare her to lead a programmatic line of studies developing and implementing data-driven, feasible, scalable interventions improving the cardiometabolic health of people with SMI.

Lead site: KPNC (PI Esti Iturralde)

Current Status

Summary of Findings

Publications

Trans-America Consortium of the Health Care Systems Research Network for the All of Us Research Program

Grant Details

Funder: NIH Office of the Director

Grant Number: OT2OD026550

Grant Period: 1/4/2018 – 3/31/2023

Narrative:

Lead Site: HFHS (co-PIs Christine Johnson and Brian Ahmedani)

Participating Sites:

Current Status:

Ongoing recruitment, enrollment and retention of 100,000 participants and members.

Summary of Findings:

Publications:

Cronin, R.M., Jerome, R.N., Mapes, B.M., Andrade, R., Johnston, R., Ayala, J., Schlundt, D., Bonnet, K.R., Kripalani, S., Goggins, K., Wallston, K.A., Couper, M.P., Elliott, M.R., Harris, P.A., Begale, M.A., Munoz, F.A., Lopez-Class, M., Cella, D., Condon, D.M., AuYoung, M., Mazor, K.M., Mikita, S., Manganiello, M., Borselli, N., Fowler, S.L., Rutter, J.L., Denny, J.C., Karlson, E.W., Ahmedani, B.K., O’Donnell, C.J. Vanderbilt University Medical Center Pilot Team, and the Participant Provided Information Committee. (2019). Development of the Initial Surveys for the All of Us Research Program. Epidemiology, 30(4), 597-608.. doi: 10.1097/EDE.0000000000001028. PMID: 31045611. 

Ramirez AH, Sulieman L, Schlueter DJ, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman KN, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark CR, Cohn E, Ohno-Machado L, Schully SD, Ahmedani BK, Argos M, Cronin RM, O’Donnell C, Fouad M, Goldstein DB, Greenland P, Hebbring SJ, Karlson EW, Khatri P, Korf B, Smoller JW, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney SA, Gebo K, Denny JC, Carroll RJ, Glazer D, Harris PA, Hripcsak G, Philippakis A, Roden DM; All of Us Research Program. (2022). The All of Us Research Program: Data quality, utility, and diversity. Patterns (N Y); 3(8), 100570. doi: 10.1016/j.patter.2022.100570. PMID: 36033590.

Cronin, R.M., Halvorson, A.E., Springer, C., Feng, X., Sulieman, L., Loperena-Cortes, R., Mayo, K., Carroll, R.J., Chen, Q., Ahmedani, B.K., Karnes, J., Korf, B., O’Donnell, C.J., Qian, J., Ramirez, A.H., All of Us Research Program Investigators.  (2021). Comparison of Family Health History in Surveys versus Electronic Health Records in the All of Us Research Program. Journal of the American Medical Informatics Association, 28(4):695-703. doi: 10.1093/jamia/ocaa315. PMID: 33404595. 

Effectiveness of Task Shifting to Peer Delivery of Behavioral Activation for Depression among Pregnant Women

Grant Details

Funder: NIMH

Grant Number: R34MH110478

Grant Period: 9/14/2016 – 7/31/2019

Narrative: Depression is a prevalent problem during pregnancy, with adverse and potentially enduring correlates and consequences for mothers and infants; however, there is a persistent failure to provide intervention for the majority of depressed pregnant women, despite the fact that efficacious behavioral interventions exist. A widely recognized barrier to treatment engagement is the lack of effective, available care that is well aligned with women’s preferences. Pregnant women prefer care that is non-pharmacological and that is integrated within the obstetric setting, and they consult informal sources more than professional ones regarding mental health. Thus, to close the gap between treatment need and receipt among depressed pregnant women, it is imperative to examine delivery methods that are efficacious, non-pharmacological, and accessible in the obstetric setting and that expand options beyond traditional professional mental health care. This work is very timely given that recent clinical guidelines require obstetric providers not only to screen for depression but also to initiate medical treatment or refer women who screen positively for depression. As a result, many obstetric settings are likely to face increased detection without corresponding availability of mental health services. We address the pressing need for such interventions by developing and pilot testing the model of “task shifting” to peers, building on work in low- and middle-income countries within the global mental health context. Behavioral Activation (BA) is an excellent candidate for task shifting to peers to treat depression during pregnancy because it was developed to maximize scalability, has strong evidence of efficacy in the general population and among pregnant women, a clear and empirically supported conceptual framework, and evidence of efficacy as delivered by non-specialist and lay counselors. Peer delivery offers pragmatic advantages, is consistent with pregnant women’s preferences, and may engage social putative targets of depression care that are relevant to depression among women. Using a three-phase structure, the proposed research will develop BA peer delivery and web-based peer training and fidelity monitoring tools, and will evaluate the feasibility, tolerability, acceptability, safety, and preliminary effectiveness of BA peer delivery within obstetric practice settings. The proposed research also seeks to advance current research paradigms by integrating, within a pragmatic clinical trial context, a conceptually and empirically driven approach to the study of transdiagnostic outcomes and putative targets, consistent with an experimental therapeutics and RDoC approach. We combine the use of established self-report measures, which can be routinely used in clinical settings to maximize practice-relevance, and rigorous laboratory paradigms developed to probe key mechanistic processes specific to BA (negative and positive valence system processes) and potentially to peer delivery (social processes).

Lead Site: University of Colorado (PI Sona Dimidjian)

Participating Sites

Current Status

Summary of Findings

Publications

Building Capacity for Stakeholder Engagement in the MHRN

Grant Details

Funder: PCORI

Grant Number

Grant Period: 4/1/2018 – 3/31/2020

Narrative:

Background: The Mental Health Research Network (MHRN) is designed to apply the learning health system model to 13 health systems that serve approximately 12.5 million patients across 15 states (17 percent of whom have a mental health condition). Without robust engagement of patients, caregivers, and families, and the community and advocacy groups who represent them, researchers may not be addressing the most meaningful research to patients.

Proposed Solution to the Problem: The project team will develop a patient-engaged research infrastructure at both the national and local health system levels. The national health systems engagement strategy will support a governance structure to integrate patient stakeholders into the MHRN executive leadership team. The local health system engagement strategy will employ a PCORI-funded stakeholder engagement model. It was developed by the Henry Ford Health System for patient-engaged research within health systems—in one MHRN health system as a model to be spread to other health systems in the MHRN.

Objectives:

  • Add the patient, caregiver, and family stakeholder voice and the community and advocacy groups who represent them to the national MHRN executive leadership team to develop a shared direction for the network and a shared national voice for mental health comparative effectiveness research (CER)
  • Develop and pilot a strategy for stakeholder engagement within one MHRN-affiliated health system and the communities it serves to identify priorities for mental health CER
  • Develop at least one research question using the processes above

Activities: The proposed national health systems engagement strategy will train and engage a small group of patient stakeholders who will be integrated into the MHRN steering committee as the stakeholder collaborative advisory panel and the local health system engagement strategy will pilot the flexible engagement strategy created by Henry Ford Health System in one MHRN health system.

Outcomes/Outputs: The projected outcomes/outputs for the proposed study are as follows:

  • At least one fully-developed mental health research question
  • Training curricula for co-learning for both stakeholders and investigators
  • Adaptation of partner participatory research models to a single MHRN health system that can be disseminated throughout all MHRN health systems
  • National engagement processes to obtain patient and other stakeholder input for research ideas, study design, and materials.

Patient and Stakeholder Engagement Plan: In addition to the PCORI Engagement Rubric, the project team will use the community-based participatory research (CBPR) framework to: recognize patient partners and their caregivers and families as a unit of identity; involve them in research done by the MHRN from development of the questions to dissemination of the results; and promote co-learning and empowerment among patients and other stakeholders.

Lead Site: KPSC (PI Karen Coleman)

Participating Site: HFHS (Co-I Karen Kippen)

Current Status

Summary of Findings

Publications

Implementing Predictive Models for Identifying Suicide Risk in Adolescents

Grant Details

Funder: NIMH (MHRN III Feasibility Pilot Program)

Grant Number: U19MH121738

Project Period: 7/1/2022 – 6/30/2023

Narrative:

Background: Adolescent suicide is an urgent public health crisis. Suicide is currently the second leading cause of death among adolescents ages 10-24. Despite decades of research, suicide attempt rates continue to rise across the U.S., particularly among adolescents. Furthermore, new data suggests that adolescents were disparately impacted by the COVID-19 pandemic, with some states reporting increased rates of suicide among youth, galvanizing the urgency for increased prevention. People who die by suicide often see healthcare providers, and specifically primary care providers prior to death, including adolescents. Therefore, identifying suicide risk in healthcare settings among adolescents is an important prevention opportunity.

Mental Health Research Network (MHRN) researchers (led by Greg Simon) have developed suicide risk prediction algorithms that have potential to vastly improve identification of individuals at high risk of suicide, including adolescents. While promising, there is very little evidence to guide routine use of this powerful suicide risk identification method during healthcare encounters with adolescents. A recently completed MHRN project (led by Bobbi Jo Yarborough) explored barriers and facilitators of the use of suicide risk algorithms among adult patients, clinicians, and administrators across three MHRN systems. These stakeholders were generally supportive of implementation, but some patient participants expressed concerns about suicide risk information resulting in coercive treatment, and clinician participants expressed desire for opportunities supporting their role in implementation decision-making.

No studies (to our knowledge) have explored perspectives of adolescents, their parents/guardians or adolescent providers about how suicide risk prediction models should be implemented. Therefore, we plan to build from prior MHRN work and qualitatively elicit adolescent care providers’ perceived barriers and facilitators to implementation of these models in care delivery and their ideologies regarding risk thresholds and risk-concordant care. Simultaneously, we plan to build a qualitative understanding adolescents and family perceptions, ideas, and preferences regarding the use of suicide risk prediction models in their care.

Research questions: (1) What perspectives do primary care providers have on suicide risk prediction algorithms and what suggestions or considerations do they have for clinical practice? (2) How do primary care providers envision risk concordant care delivery to look like in clinical practice? (3) What are adolescent and parent/caregiver perceptions and preferences on the use of suicide risk predications models as a tool for enhanced clinical care? (4) What ideas or suggestions do adolescents and parents/caregivers have for comfortable and effective implementation of risk prediction algorithms in primary care?

Methods: Provider interview guides will be developed based on interview findings by the prior qualitative MHRN study (described above) which used the Consolidated Framework for Implementation Research (CFIR), with additional questions aimed at understanding risk thresholds and associated concordant care. Caregiver and adolescent interviews will explore their thoughts, ideas, and preferences regarding EHR-based suicide risk prediction models as part of patient standard of care. We will aim to interview 10-15 adolescent care providers and 10-15 caregiver-adolescent dyads across the two sites. Care providers will be purposively selected in consultation with KPWA leaders involved in an initiative to improve adolescent access to timely mental health care. The suicide risk prediction algorithm will be used to purposively sample adolescents at high risk of suicide and their parent/guardian caregivers. Identified dyads will be recruited via mailed and telephone invitation materials (developed from a prior project recruiting adolescents & caregivers). Interviews will be audio-recorded, transcribed and double-coded to support thematic content analysis.

Planned products: A synthesis of stakeholder needs/perspectives to support suicide risk prediction model implementation in routine care delivery for adolescents. This key deliverable will be used to support: 1) current predictive analytic implementation efforts across MHRN sites 2) an external grant submission to NIMH focused on application of Human-Centered Design methods to design, build, and test clinical decision support for identifying and engaging adolescents at high-risk of suicide in evidence-based healthcare, 2) a peer-reviewed manuscript submission led by Taylor Ryan, MS (PhD student in Health Systems & Population Health at the University of Washington) & Julie Richards, MPH, PhD (MHRN researcher and faculty advisor at UW).

Lead Site: KPWA (PI Julie Richards)

Participating Sites: N/A

Current Status:

Summary of Findings:

Publications:

Syncing Screening and Services for Suicide Prevention across Health and Justice Systems

Grant Details

Title: Project 1: Syncing Screening and Services for Suicide Prevention across Health and Justice Systems

Funder: NIMH

Parent project number: 1P50MH127512

Sub-project ID: 8576

Project period: 08/22/2022 – 07/31/2027

Brief Narrative: This is a 5-year Signature Project within the NIMH-funded P50 Suicide Prevention Center, titled The National Center for Health and Justice Integration for Suicide Prevention. As suicide rates in the United States continue to rise, with nearly 50,000 suicide deaths and over 1 million suicide attempts annually per most recent data, increased attention has been paid to how to best integrate and coordinate suicide risk identification and prevention across multiple sectors, where some of our most vulnerable community members “fall through the cracks” in the continuum of care. Perhaps nowhere is this need for coordination and integration more pronounced than at the intersection of the US jail system, with over 10 million admissions per year, and the community healthcare system; an intercept known to impact individuals at disproportionately high risk for suicide. Given that roughly 10% of all suicides in the US with known circumstances occur following a recent criminal legal stressor (often arrest and jail detention), reducing suicide risk in the year after jail detention could have a noticeable impact on national suicide rates. There is thus a vital need to develop suicide risk care pathways between jails and healthcare systems to offer immediate access to care. Yet this process has been stymied by major fissures in the integration of data and clinical information between jails and health systems, preventing effective coordination of care between these community sectors. To address these needs, the proposed Signature Project is a Hybrid Type I effectiveness-implementation trial that harmonizes local jail booking and release data with healthcare records at two large healthcare systems in Minnesota and Michigan, to identify health system patients who are released from jail, and to pair the data linkage with randomization into usual care or a multi-level health system suicide prevention care pathway (consisting of care coordination, Safety Planning, Caring Contacts, and a telehealth delivered Coping Long- Term with Active Suicide Program). In so doing, this project leverages the study team’s experience in health system data linkage in the NIMH-funded Mental Health Research Network, from which the participating healthcare systems were chosen, as well as in suicide prevention around the period of jail detention and release (i.e., in the SPIRIT Trial), and in telephone-based suicide prevention intervention (i.e., in ED-SAFE). The proposed project will randomize 1050 individuals into the 5S intervention at both sites (comparing to more than 60,000 people in a usual care no contact comparison arm). Findings on suicide attempt and death outcomes, healthcare utilization mechanisms, cost- effectiveness, and implementation factors will provide data for a future fully scaled implementation trial and widespread adoption in community settings. Notably, the proposed Signature Project will be the first trial of a comprehensive health system intervention to prevent suicide in response to patients’ justice involvement.

  • Lead MHRN site: HFHS (PI: Brian Ahmedani)
  • Participating site: HPI (co-I: Rebecca Rossom)

Stakeholder Engagement

MHRN aims to address questions relevant to people who live with mental health conditions, clinicians, health system leaders, and policy makers.  We believe that the priorities and preferences of all stakeholders – and especially those of people living with mental health conditions – should guide our development of research infrastructure and selection of research questions.  True stakeholder engagement must happen “upstream” when research questions are selected – and not be limited to “downstream” decisions about how to answer questions that researchers have already selected.  MHRN stakeholder engagement includes:

  • Patient representation in governance – Patient/consumer stakeholders participate as full voting members of the MHRN steering committee, participating in regular steering committee meetings, strategic planning discussions, and decision-making regarding selection of pilot-feasibility projects and allocation of network resources.  Incorporation of patient stakeholders into the MHRN steering committee was supported by an Engagement Award from the Patient-Centered Outcomes Research Institute. These representatives have undergone an application process that is designed to identify those with lived experience with mental health conditions who value application of their experience to contribute specifically to the strategic decision-making and resource allocation for MHRN activities.
  • External Stakeholder Advisory Panel – An advisory panel including health system leaders, university-based mental health researchers, and policy makers meets three times each year to review MHRN projects, advise regarding potential projects, and advise regarding new collaborative relationships.
  • Local health system engagement – In each MHRN health system, investigators engage regularly with health plan and medical group leaders regarding research priorities, data infrastructure, and potential new research projects.

MHRN III Pilot Project 2: Outreach to Reduce Depression Treatment Disparities

Funder: NIMH

Grant Number: U19MH121738

Project Period: 07/01/2021 – 06/30/2024

Brief Narrative:

Failure to initiate treatment is a major gap in care for depression – A recent Mental Health Research Network (MHRN) study involving more than 240,000 patients in 5 health systems with a new diagnosis of depression in primary care found that only about a third (36%) had completed a psychotherapy visit or filled a prescription for antidepressant medication within 90 days of a new depression diagnosis.
Large racial and ethnic disparities in depression treatment initiation exist – In that MHRN study the odds of Asians, Blacks and Hispanics initiating treatment were 30% lower than for Non-Hispanic Whites.
Previous research has focused on care after treatment initiation – Collaborative care and care management programs can reduce disparities, improving outcomes among traditionally under-served racial and ethnic groups. This work, however, has usually focused on those who have already initiated treatment.
Interventions to improve treatment initiation must accommodate diversity of patient experience and preferences –Underserved racial and ethnic groups may prefer psychotherapy over medication and may also prefer alternative treatments or alternative care providers. One size of depression treatment does not fit all.
eHealth technologies have the potential to address failures in treatment initiation – Previous research by MHRN investigators and others demonstrates that online messaging and other telehealth technologies can effectively and efficiently improve depression treatment adherence. These interventions, however, have focused on adherence after treatment initiation and have been tested primarily in non-Hispanic white patients.
Proposed trial: This pilot study will refine, adapt and test an outreach intervention to improve depression treatment initiation among patients recently receiving a new diagnosis of depression in primary care. Focusing on African American, Asian, Native Hawaiian/Pacific Islander and Hispanic patients, the study will leverage existing MHRN work to implement an automated outreach program with follow-up care facilitation by mental health clinicians. The intervention will utilize analytic and technological expertise developed by the MHRN to rapidly identify patients, send outreach messages, conduct assessments and facilitate care for patients with depression who fail to initiate treatment in a timely manner. The intervention will be developed with the input of patients in the target racial and ethnic minority populations and providers. Approximately 400 eligible patients in two MHRN health systems will be randomized to the intervention group or usual care. Outcomes (treatment initiation and rates recorded depression remission and response) will be ascertained from health system records. Analyses will examine intervention participation and compare the primary outcome (treatment initiation) and secondary outcomes (recorded depression remission and response) between groups. Results will inform a subsequent full-scale pragmatic trial to assess reduction in population-level disparities.

  • Lead Site:
    • KPHI (PI Vanessa Simiola)
  • Participating Sites:
    • HFHS (Site PI Lisa Matero)
    • KPWA (Co-I Greg Simon)
  • Awarded Budget (total costs):
    • Year 1: $112,382

Current Status

Over the reporting period Institutional Board Approval has been granted and focus group materials have been finalized as part of the formative research. Eligible participants were identified within the health care systems via distributed SAS code. Participant recruitment is currently underway within one (KPHI) of the two health care systems, with online focus groups scheduled in the beginning of May. The second health care system (HFHS) is awaiting local IRB approval and will begin recruitment immediately following. Provider surveys are scheduled for the end of the reporting period.

Summary of findings

Not yet available

Publications

None

Documents

Funding Announcement

Notice of Award

Personnel Contact List

Human Subjects: YES

IRB Review: KPSC is single IRB reviewing for KPHI, HFHS, and KPWA. File #12874.

Clinical Trial: YES

MHRN Post-Doctoral Fellowship Program

About

The MHRN T32 Post-Doctoral Fellowship is an NIMH-supported, two-year fellowship program. Aspiring independent researchers are trained broadly in health systems/health services research with a focus on mental health conditions and services, as well as suicide prevention. Areas of particular interest and training are in clinical interventions, healthcare service delivery, big data, implementation science, comorbidities, health equity, and health policy. The overall goal of the program is to support fellows in the transition to becoming independent mental health services researchers able to pursue NIMH-funding to support research within health system settings.

Fellows work locally alongside a primary mentor at HFHS or KPNC. They also receive high-quality mentorship and training from other scientists within multiple formats across the entire MHRN. In addition to one-on-one mentoring in the fellows’ areas of interest, they receive training in grant writing, manuscript development, health systems research methods (e.g., case-control designs, big data science, multi-site trials, dissemination and implementation), quantitative and qualitative methods, ethics, professional/career development, and conducting clinical trials. Teaching opportunities may also be available, as will clinical experiences for those seeking licensure.

Two fellows are enrolled each year. Applicants should have a PhD, MD, or other doctoral degree in a related field. Open to U.S. citizens or permanent residents enrolled in research or clinical doctoral or postdoctoral programs.

The Program Lead is Brian Ahmedani (HFHS). The Training Directors are Stacy Sterling (KPNC) and Jordan Braciszewski (HFHS).

A full description of the program and the application process can be viewed at https://www.henryford.com/hcp/research/public-population-research/health-policy/research .

Current Fellows

Seminar Schedule

seminar materials

Contact

For more information about the MHRN Fellowship program, contact MHRNT32@hfhs.org.

MHRN III Pilot Project 1: Stakeholder Views on Implementation of Suicide Risk Prediction Models

Grant Details

Funder: NIMH

Grant Number: U19MH121738

Grant Period: 09/24/2019 – 6/30/2021

Narrative: Age-adjusted suicide rates have been increasing in the U.S. over the past two decades. In 2017, more than 47,000 Americans died of suicide. Health care visits represent opportunities for suicide prevention because most individuals make an outpatient health care visit within a year of their suicide death and almost half have a visit within a month of their death. However, suicide risk is not always easily recognizable to clinicians—traditional clinical prediction is hardly better than chance. Predictive modeling that identifies patterns in “big data” from administrative and electronic health records has proven superior to clinical suicide risk prediction and routinely used suicide screening instruments. While predictive modeling holds promise for suicide prevention, how models should be implemented in routine clinical practice and the contextual factors that influence their use are understudied. The potential benefits of any risk prediction model, including those designed to identify suicide risks, are dependent on making sure that the models are deployed in a manner that does not harm patients, supports clinical care management, and is sustainable for health care delivery systems. We propose a pre-implementation pilot study in three settings, using one-on-one, in-depth interviews to explore health system administrators’, clinicians’, and patients’ expectations, experiences with, concerns, and suggestions for the early use of suicide risk prediction models. In the first setting, health system administrators are still considering what might be the best implementation approach. Interviews will help us understand how various stakeholder expectations match what is actually occurring in the two other settings where small pilot studies will be in process. One of these settings is planning outreach to high-risk patients independent of health care visits while the other is planning delivery of risk scores at the point of care. By studying different implementation strategies, we can compare relative advantages and disadvantages. We are particularly interested in effects on clinical workflows, clinician-patient relationships, and patient experiences. While there is an emerging literature supporting the promise of predictive models in health care, implementation factors and patient impacts have been largely ignored. Yet decisions regarding design and modeling methods and implementation processes should be driven by stakeholder requirements. Results of this pilot study will have important clinical implications and will not only inform large-scale implementation of suicide risk prediction models in health systems across the country but will also inform development of future risk prediction models and associated care processes tailored to stakeholders needs more generally (not limited to suicide risk). The long-term goals of this pilot project are to inform ongoing health system-level efforts to reduce suicide prevalence and prevent suicides by optimizing the use of suicide risk prediction tools.

  • Lead Site:
    • Overall PI: KPNW (Bobbi Jo Yarborough)
  • Participating Sites/Subcontractors:
    • HPI (site project lead Rebecca Rossom)
    • KPWA (site project lead Julie Richards; site PI Greg Simon)
  • Funder Contacts
    • Science Officer: Susan Azrin
    • Program Official: Michael Freed
    • Grants Management Official: Julie Bergerud

Documents

Funding Announcement

Notice of Award

Personnel Contact List

Current Status

We have completed and analyzed interviews with 10 health care administrators, 30 clinicians in behavioral health departments, and 62 patients across three health systems.

Summary of Findings

Administrators and clinicians

  • Use of a suicide risk prediction model and two differing implementation approaches were acceptable.
  • Clinicians desired opportunities for input on implementation decision-making.
  • They wanted to know how this manner of risk identification enhanced existing suicide prevention efforts.
  • They wanted additional training on how the models determined risk and why some patients appeared at risk while others do not.
  • Clinicians were concerned about lack of suicide prevention resources for newly identified patients.
  • They wanted clear procedures for situations when they could not reach patients or when patients remained at-risk over a sustained period.
  • They would like consolidated suicide risk information in a dedicated module in the EHR to increase efficiency.

Patients

  • Patients were generally supportive of suicide risk prediction models derived from EHR data.
  • Concerns included: 1) apprehension about inducing anxiety and suicidal thoughts, or 2) triggering coercive treatment, particularly among those who reported prior negative experiences seeking mental health care.
  • Participants engaged in mental health care or case management expected to be asked about suicide risk and largely appreciated suicide risk conversations
  • Patients preferred conversations to come from clinicians comfortable discussing suicidality.

Publications

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.

Yarborough BJH, Stumbo SP, Schneider JL, Richards JE, Hooker SA, Rossom RC . Patient expectations of and experiences with a suicide risk identification algorithm in clinical practice. BMC Psychiatry. 2022 Jul 23;22(1):494. doi: 10.1186/s12888-022-04129-1 .