Clinical trial NCT06782516: Native-RISE (Risk Identification for Suicide and Enhanced Care)
Official title: Native-RISE (Risk Identification for Suicide and Enhanced Care)
Study type: INTERVENTIONAL
Overall status: ENROLLING_BY_INVITATION
Phase: NA
Conditions: Suicide Prevention
Lead sponsor: Johns Hopkins Bloomberg School of Public Health
Sponsor class: OTHER
First posted: 2025-01-20
Enrollment: 1687
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Native-RISE Model is a predictive algorithm for suicide risk in Native American populations. The algorithm was developed based on analysis of over 330,000 visits and designed to identify people at risk of a suicide attempt or death within 90 days of the last visit. The evaluation of the model initial results have been published with the model having an area under the ROC (AUROC) 0.83 \[0.80-0.86\]) and performing better than existing care (AUROC 0.64 \[0.61-0.67\]).
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: The goal of this research is to test a systems-level suicide prevention strategy, Native-RISE (Risk Identification for Suicide and Enhanced care), that combines predictive analytics and brief contact interventions (BCIs) to reduce suicide in health systems serving Native Americans (NAs). This project aims to prove the effectiveness and scalability of Native-RISE within three Indian Health Service (IHS) health care clinics (Whiteriver, Chinle and Shiprock) already implementing suicide prevention programs and serving the White Mountain Apache Tribe (WMAT) and Navajo Nation (NN).


Eligibility criteria: Inclusion Criteria:

* Adults aged 18-75
* Visit at least one of the three participating IHS clinics
* Identified as at risk of suicide by either an existing method or the new Native-RISE risk model algorithm

Exclusion Criteria:

* None

Primary outcomes:
measure: Rate of suicide attempts among individuals flagged at elevated risk
timeFrame: 12 months
Secondary outcomes:
measure: Number of contacts with Case Managers (Reach of Brief Contact Interventions (BCI))
timeFrame: 12 months
Other outcomes:
Locations:
city: Chinle
country: United States
facility: Chinle Navajo Nation Center for Indigenous Health
state: Arizona
city: Whiteriver
country: United States
facility: Whiteriver Center for Indigenous Health
state: Arizona
city: Shiprock
country: United States
facility: Shiprock Center for Indigenous Health
state: New Mexico
Study officials:
affiliation: Johns Hopkins University
name: Emily Haroz, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Haroz EE, Rebman P, Goklish N, Garcia M, Suttle R, Maggio D, Clattenburg E, Mega J, Adams R. Performance of Machine Learning Suicide Risk Models in an American Indian Population. JAMA Netw Open. 2024 Oct 1;7(10):e2439269. doi: 10.1001/jamanetworkopen.2024.39269.
citation: Adams R, Haroz EE, Rebman P, Suttle R, Grosvenor L, Bajaj M, Dayal RR, Maggio D, Kettering CL, Goklish N. Developing a suicide risk model for use in the Indian Health Service. Npj Ment Health Res. 2024 Oct 16;3(1):47. doi: 10.1038/s44184-024-00088-5.