Our overarching, long-range goal is to identify rigorous, scaleable implementation innovations that are effective for improving the implementation of evidence-based practices (EBP) in healthcare systems. PTSD, depression and substance use disorders are highly prevalent and debilitating, and are primary reasons Veterans seek care in the Veterans Health Administration (VA). Despite investment in increasing EBP adoption for these disorders among providers, EBPs have wide variability in time-to-receipt and limited reach among the outpatient population. Without improving timely access to high-quality services, Veterans with unmet mental health and addiction needs are at risk for chronic impairment and death. EBPs require multiple appointments coordinated within multidisciplinary service delivery teams and across generalist and specialty programs. Redesigning interdependent processes, such as scheduling practices, referral procedures, patient flows, and staffing allocations must be locally tailored and require considerable stakeholder buy in and support. To advance as a field, implementation science must move beyond descriptions of system barriers and facilitators to address this system complexity. Participatory system dynamics modeling meets this need by triangulating stakeholder perspectives, administrative data and model simulations, conferring rigor and specificity regarding the mechanisms by which EBP implementation is effective or ineffective in local settings. Our short-term objective is to evaluate whether participatory system dynamics modeling helps to improve EBP timing and reach in two VA outpatient systems that were selected due to differences in resources and complexity (high vs. low). VA experts, local leaders and providers, and Veterans with experience as mental health and addiction patients engage in a modeling process to address multidimensional EBP delivery dynamics. Models test stakeholder hypotheses about improvement strategies and formally specify system capacity for implementation alternatives accounting for local constraints. Model simulations evaluate system impacts of new EBP policies or procedures prior to implementation, saving time and resources as compared to trial-and-error approaches. Administrative data is synthesized in models and made newly actionable to stakeholders who develop site-specific restructuring plans. Effectiveness aims test for: 1) increased reach of EBPs among the patient population, and 2) reduced time from intake to EBP, over a 12-month follow-up period, as compared to twelve months before modeling/redesign. Participatory system dynamics modeling holds promise for implementation scientists seeking innovative methods for engaging stakeholders around more precise understandings of EBP delivery dynamics and context to improve implementation outcomes. If shown to be effective, participatory system dynamics modeling can be used to address the critical need for strategies that improve EBP implementation in health service systems, and thereby, help to meet national priorities to ensure timely, high-quality health care.

Public Health Relevance

Limited access and delays to high-quality, evidence-based mental health and addiction treatments can lead to patients getting too little or ineffective care and contribute to chronic patient impairment, relapse, and death by suicide or overdose. This study evaluates a system for resolving problems with patient flow and organization in health care systems, using electronic medical record systems and a high-level of input from healthcare leadership, frontline providers and patients. Using innovative approaches from engineering, stakeholders identify optimal ways to align existing resources to best meet patients? needs, mathematically evaluating the impact of different organizational fixes before undertaking difficult systems changes; this helps health systems avoid ineffective improvement strategies and increases the supply of the most effective treatments to meet patients? needs.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Exploratory/Developmental Grants (R21)
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Dissemination and Implementation Research in Health Study Section (DIRH)
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Wiley, Tisha R A
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Palo Alto Veterans Institute for Research
Palo Alto
United States
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