Participatory System Dynamics vs Usual Quality Improvement: Staff Use of Simulation as an Effective, Scalable and Affordable Way to Improve Timely Mental Health Care?

NCT04208217 | Completed

• 2 other identifiers: IIR 17-29412760065
• Study Type: interventional
• Target: 720
• Locations: 1 country
• Sites: 1

Brief Summary

Evidence-based VA care is best for meeting Veterans' mental health needs, such as depression, PTSD and opioid use disorder, to prevent suicide or overdose. But some key evidence-based practices only reach 3-28% of patients. Participatory system dynamics (PSD) helps improve quality with existing resources, critical in mental health and all VA health care. PSD uses learning simulations to improve staff decisions, showing how goals for quality can best be achieved given local resources and constraints. This study aims to significantly increase the proportion of patients who start and complete evidence-based care, and determine the costs of using PSD for improvement. Empowering frontline staff with PSD simulation encourages safe 'virtual' prototyping of complex changes to scheduling, referrals and staffing, before translating changes to the 'real world.' This study determines if PSD increases Veteran access to the highest quality care, and if PSD better maximizes VA resources when compared against usual trial-and-error approaches to improving quality.

Conditions

PTSD; Depression; Opioid Use Disorder

Keywords

implementation science; quality improvement; modeling to learn; usual quality improvement; evidence-based psychotherapy; evidence-based pharmacotherapy; addiction; mental health/behavioral health

Outcome Measures

Primary Outcomes (3)

• Proportion of patients initiating and completing a course of evidence-based psychotherapy (EBPsy) or evidence-based pharmacotherapy (EBPharm)

  Proportion evidence-based practice (EBP) reach is defined as the proportion of VA outpatient addiction and mental health patients who receive evidence-based psychotherapy and/or evidence-based pharmacotherapy for opioid use disorder, depression, or PTSD in routine outpatient VA care.

  Pre-/Post- 12-month period average of EBP reach (24 months total observation)]

• Number of completed EBPsy templates during sessions with a relevant CPT code

  Proportion of 3 EBPsy treatments for depression - Cognitive Behavior Therapy (CBT-D), Acceptance and Commitment Therapy (ACT), Interpersonal Psychotherapy (IPT) 2 EBPsy for PTSD - Prolonged Exposure (PE), and Cognitive Processing Therapy (CPT)

  Pre-/Post- 12-month period average of EBP reach (24 months total observation)]

• Number of combination of prescriptions placed with the VA pharmacy and sessions with a relevant CPT code

  Proportion of 2 EBPharm treatments for depression - 84 and 180 days therapeutic continuity at new antidepressant start and 2 EBPharm for Opioid Use Disorder (OUD) - methadone and buprenorphine

  Pre-/Post- 12-month period average of EBP reach (24 months total observation)]

Secondary Outcomes (14)

• Differences in team perceptions of MTL and QI assessed by the Acceptability of Intervention Measure (AIM)

  at 6 months

• Differences in team perceptions of MTL and QI assessed by the Intervention Appropriateness Measure (IAM)

  at 6 months

• Differences in team perceptions of MTL and QI assessed by the Feasibility of Intervention Measure (FIM)

  at 6 months

• Patient Aligned Care Team Burnout Measure (PACT)

  At baseline and 6 months

• Participatory Measure: Context

  At baseline and 6 months

Study Arms (2)

Modeling to Learn (MTL)

EXPERIMENTAL

12 clinics randomly assigned to MTL

Behavioral: Modeling to Learn (MTL)

Usual quality improvement (QI)

EXPERIMENTAL

12 clinics randomly assigned to usual QI

Behavioral: Usual quality improvement (QI)

Interventions

Usual quality improvement (QI) BEHAVIORAL

Usual quality improvement is a health care quality improvement or evidence-based practice implementation strategy that includes frontline addiction and mental health staff reviewing data to find the best approaches for improving the reach of evidence-based psychotherapy and evidence-based pharmacotherapy.

Usual quality improvement (QI)

Modeling to Learn (MTL) BEHAVIORAL

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.

Modeling to Learn (MTL)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• health care systems currently functioning below the median VA mental health recommendations for Strategic Analytics for Improvement \& Learning (SAIL) and below the median for 3 of 8 SAIL evidence-based treatment approaches.
• VA divisions and community-based outpatient clinics (CBOCs) or 'clinics' from regional VA health systems
• Must be below the overall VA quality median (as assessed by the Strategic Analytics for Improvement and Learning or SAIL), which includes 3 of 8 SAIL measures associated with four evidence-based psychotherapies and three evidence-based pharmacotherapies for depression, PTSD, and opioid use disorder.

You may not qualify if:

• Health care systems functioning above median VA mental health recommendations for Strategic Analytics for Improvement \& Learning (SAIL) and below the median for 3 of 8 SAIL evidence-based treatment approaches. Only one health care system can be included per arm - MTL vs QI.
• clinics with less than 12 months of data in 2018
• clinics involved in Office of Veterans Access to Care (OVACS) quality improvement program at baseline
• clinics where the VA Cerner electronic health record (EHR) implementation rollout will occur during the project period (Veterans Integrated Services Networks (VISNs) 20, 21 ,22, and 7)
• clinics who serve less than 122 unique patients each month on average
• clinics without an onsite multidisciplinary team of mental health or addiction service providers (minimum required: 1 psychiatrist, 1 psychologist, 1 social worker onsite)

Sponsors & Collaborators

• VA Office of Research and Development: lead

Study Sites (1)

VA Palo Alto Health Care System, Palo Alto, CA

Palo Alto, California, 94304-1207, United States

Location

Related Links

• Home page of Modelling To Learn
• Modelling to Learn simulation
• Modelling to Learn facilitator page
• Modelling to Learn data page
• Modeling to Learn power bi data UI test environment

MeSH Terms

Conditions

Stress Disorders, Post-Traumatic; Depression; Opioid-Related Disorders; Behavior, Addictive; Psychological Well-Being

Condition Hierarchy (Ancestors)

Stress Disorders, Traumatic; Trauma and Stressor Related Disorders; Mental Disorders; Behavioral Symptoms; Behavior; Narcotic-Related Disorders; Substance-Related Disorders; Chemically-Induced Disorders; Compulsive Behavior; Impulsive Behavior; Personal Satisfaction

Study Officials

• Lindsey E. Zimmerman, PhD

  VA Palo Alto Health Care System, Palo Alto, CA

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: FED
• Responsible Party: SPONSOR

Model Details: 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.

Study Record Dates

• First Submitted: December 18, 2019
• First Posted: December 23, 2019
• Study Start: July 22, 2021
• Primary Completion: January 31, 2026
• Study Completion: January 31, 2026
• Last Updated: May 11, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)