PTSDNCT04208217
Participatory System Dynamics vs Usual Quality Improvement: Staff Use of Simulation as an Effective, Scalable and Affordable Way to Improve Timely Mental Health Care?
A study testing Modeling to Learn (MTL) and Usual quality improvement (QI) in people with PTSD and Depression, run by VA Office of Research and Development at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- PTSD, Depression, Opioid Use Disorder
- What is being tested?
- Modeling to Learn (MTL) and Usual quality improvement (QI)
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 720 participants
- Where
- 1 siteUnited States
- Study dates
- 22 Jul 2021to 31 Jan 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 24 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.
Who cannot join
- 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)
Trial locations and contacts
1 site in 1 country.
United States1 site
VA Palo Alto Health Care System, Palo Alto, CA
Palo Alto, California, 94304-1207
About this study
Official title: Participatory System Dynamics vs Usual Quality Improvement: Is Staff Use of Simulation an Effective, Scalable and Affordable Way to Improve Timely Veteran Access to High-quality Mental Health Care?
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.
Read the detailed 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 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.
- Conditions
- PTSD, Depression, Opioid Use Disorder
- Being tested
- Modeling to Learn (MTL), Usual quality improvement (QI)
- Keywords
- implementation science, quality improvement, modeling to learn, usual quality improvement, evidence-based psychotherapy, evidence-based pharmacotherapy, addiction, mental health/behavioral health
- Medical subject headings
- Stress Disorders, Post-Traumatic, Depression, Opioid-Related Disorders, Behavior, Addictive, Psychological Well-Being
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Modeling to Learn (MTL)Behavioural
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 (QI)Behavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Modeling to Learn (MTL) | Experimental | 12 clinics randomly assigned to MTL Receives: Behavioral: Modeling to Learn (MTL) |
| Usual quality improvement (QI) | Experimental | 12 clinics randomly assigned to usual QI Receives: Behavioral: Usual quality improvement (QI) |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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)
Measured: 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
Measured: 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)
Assesses differences in team perceptions of MTL and QI using the 4 item survey 'Acceptability of Intervention Measure (AIM)'.
Scale: 1-5, in 1 point increments (1 = completely disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = completely agree)
Measured: at 6 months
Differences in team perceptions of MTL and QI assessed by the Intervention Appropriateness Measure (IAM)
Assesses differences in team perceptions of MTL and QI using the 4 item survey 'Intervention Appropriateness Measure (IAM)'.
Scale: 1-5, in 1 point increments (1 = completely disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = completely agree)
Measured: at 6 months
Differences in team perceptions of MTL and QI assessed by the Feasibility of Intervention Measure (FIM)
Assesses differences in team perceptions of MTL and QI using the 4 item survey 'Feasibility of Intervention Measure (FIM)'.
Scale: 1-5, in 1 point increments (1 = completely disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = completely agree)
Measured: at 6 months
Patient Aligned Care Team Burnout Measure (PACT)
Quality of work satisfaction and burnout in a 4-item descriptive measure from VA team-based primary care that tracks 1) years of experience with the team, 2) working on more than one team, 3) turnover/change in team staff, 4) team overwork, and the single-item 5) self-reported burnout (sensitivity 83.2% and specificity 87.4%).
Higher turnover numbers and high reported levels of burn out are considered negative.
Measured: At baseline and 6 months
Participatory Measure: Context
Assesses differences in MTL and QI decision context Scale: 1-5 (1 = VA Central Office, 2 = VA Facility Leadership, 3 = Clinic Managers, 4 = Our team, 5 = Individual providers on our team)
Measured: At baseline and 6 months
Participatory Measure: Partnership Structural Values
Assess differences in MTL and QI partnership structural values in a 22-item measure with subscales a) partner focus, b) core values, c) participation, d) cooperation, e) respect, and f) trust
Subscale a) partner focus Scale: 1-5, in 1 point increments (1 = not at all , 5 = to a great extent) Alpha = 0.82
Subscale b-f) core values, participation, cooperation, respect, trust) Scale: 1-5, in 1 point increments (1 = strongly disagree, 5 = strongly agree) Subscale b) Alpha = 0.89 Subscale c) Alpha = 0.78 Subscale d) Alpha = 0.83 Subscale e) Alpha = 0.83 Subscale f) Alpha = 0.86
Measured: At 6 months
Participatory Measure: Relationships
Assess differences in MTL and QI relationships in a 15-item measure with subscales a) participatory decision-making, b) leadership, and c) use of resources
Subscale a) participatory decision-making Scale: 1-5, in 1 point increments (1 = never, 5 = always) Alpha = 0.83
Subscale b) leadership Scale: 1-5, in 1 point increments (1 = very ineffective, 5 = very effective) Alpha = 0.94
Subscale c) use of resources Scale: 1-5, in 1 point increments (1 = makes poor use, 5 = makes excellent use) Alpha = n/a
Measured: At 6 months
Participatory Measure: Synergy
Assess differences in MTL and QI synergy in a 5-item measure.
Scale: 1-5, in 1 point increments (1 = not at all, 5 = to a great extent) Alpha = 0.90
Measured: At 6 months
Participatory Measure: Capacity-Building Index
Assess differences in MTL and QI capacity-building index in a 5-item measure
Scale: 1-5, in 1 point increments (1 = Not at all, 2 = Very Little, 3 = Somewhat, 4 = To a Large Extent, 5 = To a Very Great Extent) Alpha = 0.90
Measured: At 6 months
Facilitator Quality: Engagement Principles
10-item engagement principles measure that assesses investigator readiness to conduct participatory implementation science research. Assesses team and co-facilitator self-ratings of co-facilitators' use of engagement principles, such as building trusting relationships, knowledge of local conditions, and support for existing local capacities
Scale: 1-5, in 1 point increments (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree)
Response options range from 1 (strongly disagree) to 5 (strongly agree). Items will be summed for analyses, and the investigators will evaluate for convergence/divergence across facilitator and team ratings
Measured: At 6 months
MTL Fidelity Checklist for 12-Session Plan
Track MTL arm fidelity to 12-Session plan resources, sessions, online outputs, and standardized weekly emails
Measured: Throughout 6 months
QI Fidelity Checklist for 12-Session Plan
Track QI arm fidelity to 12-Session plan resources, sessions, online outputs, and standardized weekly emails
Measured: Throughout 6 months
Quality Improvement Activity Tracking
Tracking form adapted from a current VA operations-focused, implementation facilitation trial by the VA Team-Based Behavioral Health QUERI Program with four strengths specific to our study of: 1) assessment of activity costs readily comparable to other another VA multisite trial, 2) measure from Behavioral Health Interdisciplinary Program (BHIP) Enhancement Project, team-focused MH care, like PSD, 3) emphasis on quantifying a) staff and b) facilitator time, rather than categorizing content, 4) prior use in VA.
Measured: Throughout 6 months
Demographic Measures
4 item measure assessing ethnic (Hispanic, Latino, Latina, or Latinx), racial (American Indian/Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Black or African American, White, More than One Race) and gender (Man, Woman, Non-binary) identity of respondent.
All items include a "Prefer not to say" option. Categories for demographic measures determined based on NIH reporting standards.
Measured: At baseline and 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Dec 2019
- Study start22 Jul 2021
- Primary completion31 Jan 2026
- Study completion31 Jan 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for PTSDStudies of the same condition, open and under way.
- More trials run by VA Office of Research and DevelopmentThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- 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)
- Enrolment
- 720 participants (actual)
Sponsor and investigators
- Lead sponsor
- VA Office of Research and Development
- Sponsor type
- US federal agency
- Responsible party
- Sponsor
- Investigators
- Lindsey E. Zimmerman, PhD, Principal investigator, VA Palo Alto Health Care System, Palo Alto, CA
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04208217
- Sponsor's protocol ID
- IIR 17-294
- Other IDs
- 12760065
- Status last verified
- May 2026
- First submitted
- 18 Dec 2019
- Last updated
- 11 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Participatory System Dynamics vs Usual Quality Improvement: Is Staff Use of Simulation an Effective, Scalable and Affordable Way to Improve Timely Veteran Access to High-quality Mental Health Care?
- ClinicalTrials.gov ID
- NCT04208217
- Acronym / sponsor ID
- IIR 17-294
- 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
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 720 participants (actual)
- Lead sponsor
- VA Office of Research and DevelopmentUS federal agency
- Study start
- 22 Jul 2021 (actual)
- Primary completion
- 31 Jan 2026 (actual)
- Study completion
- 31 Jan 2026 (actual)
- First posted
- 23 Dec 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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 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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- 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.
| Arm | Type | Receives |
|---|---|---|
| Modeling to Learn (MTL) | Experimental | Behavioral: Modeling to Learn (MTL)12 clinics randomly assigned to MTL |
| Usual quality improvement (QI) | Experimental | Behavioral: Usual quality improvement (QI)12 clinics randomly assigned to usual QI |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- 24 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.
Key exclusion criteria (6 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Modeling to Learn (MTL)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. | Behavioural | Modeling to Learn (MTL) |
| Usual quality improvement (QI)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. | Behavioural | Usual quality improvement (QI) |
Primary outcome
Proportion of patients initiating and completing a course of evidence-based psychotherapy (EBPsy) or evidence-based pharmacotherapy (EBPharm)
Time frame: Pre-/Post- 12-month period average of EBP reach (24 months total observation)]
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.
Number of completed EBPsy templates during sessions with a relevant CPT code
Time frame: Pre-/Post- 12-month period average of EBP reach (24 months total observation)]
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)
Number of combination of prescriptions placed with the VA pharmacy and sessions with a relevant CPT code
Time frame: Pre-/Post- 12-month period average of EBP reach (24 months total observation)]
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
14 secondary outcomes
Differences in team perceptions of MTL and QI assessed by the Acceptability of Intervention Measure (AIM)
Time frame: at 6 months
Differences in team perceptions of MTL and QI assessed by the Intervention Appropriateness Measure (IAM)
Time frame: at 6 months
Differences in team perceptions of MTL and QI assessed by the Feasibility of Intervention Measure (FIM)
Time frame: at 6 months
Patient Aligned Care Team Burnout Measure (PACT)
Time frame: At baseline and 6 months
Participatory Measure: Context
Time frame: At baseline and 6 months
Participatory Measure: Partnership Structural Values
Time frame: At 6 months
Participatory Measure: Relationships
Time frame: At 6 months
Participatory Measure: Synergy
Time frame: At 6 months
Participatory Measure: Capacity-Building Index
Time frame: At 6 months
Facilitator Quality: Engagement Principles
Time frame: At 6 months
MTL Fidelity Checklist for 12-Session Plan
Time frame: Throughout 6 months
QI Fidelity Checklist for 12-Session Plan
Time frame: Throughout 6 months
Quality Improvement Activity Tracking
Time frame: Throughout 6 months
Demographic Measures
Time frame: At baseline and 6 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 May 2026.
- Home page of Modelling To LearnLink provided by the sponsor.
- Modelling to Learn simulationLink provided by the sponsor.
- Modelling to Learn facilitator pageLink provided by the sponsor.
- Modelling to Learn data pageLink provided by the sponsor.
- Modeling to Learn power bi data UI test environmentLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Lindsey E. Zimmerman, PhD principal investigator
VA Palo Alto Health Care System, Palo Alto, CA
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Modeling to Learn (MTL) and Usual quality improvement (QI) in people with PTSD and Depression, run by VA Office of Research and Development at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 11 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion of patients initiating and completing a course of evidence-based psychotherapy (EBPsy) or evidence-based pharmacotherapy (EBPharm) (time frame: Pre-/Post- 12-month period average of EBP reach (24 months total observation)]). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 May 2026.