Recruitment

Recruitment Status
Not yet recruiting
Estimated Enrollment
Same as current

Summary

Conditions
  • Depression
  • Opioid Use Disorder
  • PTSD
Type
Interventional
Phase
Not Applicable
Design
Allocation: RandomizedIntervention Model: Parallel AssignmentIntervention Model Description: Modeling to Learn: Modeling to Learn is a facilitated health care quality improvement or evidence-based practice implementation strategy that includes frontline addiction and mental health staff running simulations of clinic improvement strategies to find the best approaches for improving the reach of evidence-based psychotherapy and evidence-based pharmacotherapy. Usual Quality Improvement: Usual quality improvement is a health care quality improvement or evidence-based practice implementation strategy that includes frontline addiction and mental health staff reviewing team data to find the best approaches for improving the reach of evidence-based psychotherapy and evidence-based pharmacotherapy. Anticipate that 720 frontline providers will participate across both arms of this trial. There will be no interaction with current patients for the purposes of research. No new data will be collected beyond data generated during routine care.Masking: None (Open Label)Primary Purpose: Health Services Research

Participation Requirements

Age
Between 18 years and 125 years
Gender
Both males and females

Description

Background: Evidence-based practices (EBPs) are the most high value treatments to meet Veterans' addiction and mental health needs, reduce chronic impairment, and prevent suicide or overdose. Over 10 years, VA invested in dissemination of evidence-based psychotherapies and pharmacotherapies based on...

Background: Evidence-based practices (EBPs) are the most high value treatments to meet Veterans' addiction and mental health needs, reduce chronic impairment, and prevent suicide or overdose. Over 10 years, VA invested in dissemination of evidence-based psychotherapies and pharmacotherapies based on substantial evidence of effectiveness as compared to usual care. Quality metrics also track progress. Despite these investments, patients with prevalent needs, such as depression, PTSD and opioid use disorder often don't receive EBPs. Systems theory explains limited EBP reach as a system behavior emerging dynamically from local components (e.g., patient demand/health service supply). Participatory research and engagement principles guide participatory system dynamics (PSD), a mixed-methods approach used in business and engineering, shown to be effective for improving quality with existing resources. Significance/Impact: This study is proposed in the high priority area of VA addiction and mental health care to improve Veteran access to VA's highest quality care. The PSD program, Modeling to Learn (MTL), improves frontline management of dynamic complexity through simulations of staffing, scheduling and service referrals common in healthcare, across generalist and specialty programs, patient populations, and provider disciplines/treatments. Innovation: Recent synthesis of VA data in the enterprise-wide SQL Corporate Data Warehouse (CDW) makes it feasible to scale participatory simulation learning activities with VA frontline addiction and mental health staff. MTL is an advanced quality improvement (QI) infrastructure that helps VA take a major step toward becoming a learning health care system, by empowering local multidisciplinary staff to develop change strategies that fit to local capacities and constraints. Model parameters are from one VA source and generic across health services. If findings show that MTL is superior to usual VA quality improvement activities of data review with facilitators from VA program offices, this paradigm could prove useful across VA services. The PSD approach also advances implementation science. Systems theory explains how dynamic system behaviors (EBP reach) are defined by general scientific laws, yet arise from idiographic local conditions. Empowering staff with systems science simulation encourages the safe prototyping of ideas necessary for learning, increasing ongoing quality improvement capacities, and saving time and money as compared to trial-and-error approaches. Specific Aims: Effectiveness: Test for superiority of MTL over usual QI for increasing the proportion of patients (1a) initiating, and (1b) completing a course of evidence-based psychotherapy (EBPsy) and evidence-based pharmacotherapy (EBPharm). Scalable: (2a) Evaluate usual QI and MTL fidelity. (2b) Test MTL fidelity for convergent validity with participatory measures. (2c) Test the participatory theory of change: Evaluate whether 12 month period EBP reach is mediated by team scores on participatory measures. Affordable: (3a) Determine the budget impact of MTL. (3b). Calculate the average marginal costs per 1% increase in EBP reach. Methodology: This study proposes a two-arm, 24-clinic (12 per arm) cluster randomized trial to test for superiority of MTL over usual QI for increasing EBP reach. Clinics will be from 24 regional health care systems (HCS) below the SAIL mental health median, and low on 3 of 8 SAIL measures associated with EBPs. Computer-assisted stratified block randomization will balance MTL and usual QI arms at baseline using Corporate Data Warehouse (CDW) data. Participants will be the multidisciplinary frontline teams of addiction and mental health providers. Next Steps/Implementation: MTL was developed in partnership with the VA Office of Mental Health and Suicide Prevention (OMHSP) and if shown to be effective, scalable, and affordable for improving timely Veteran access to EBPs, MTL will be scaled nationally to more clinics by expanding MTL online resources, and training more VA staff to facilitate MTL activities instead of usual QI.

Tracking Information

NCT #
NCT04208217
Collaborators
Not Provided
Investigators
Principal Investigator: Lindsey E. Zimmerman, PhD VA Palo Alto Health Care System, Palo Alto, CA