Optimizing Multi-Component Service Delivery Interventions for People with Opioid Use Disorder, Co-Occurring Conditions, and/or Suicide Risk (HEAL)
Presenter:
Michael C. Freed, Ph.D., EMT-B
Division of Services and Intervention Research
Goal:
In April 2018, the NIH launched the Helping to End Addiction Long-termSM Initiative, or HEAL SM Initiative, an aggressive, trans-agency effort to speed scientific solutions to stem the national opioid public health crisis. In response to this initiative, the National Institute of Mental Health (NIMH), in partnership with other NIH Institutes and Offices, intends to invite research that will optimize multi-component service delivery interventions for people with opioid use disorder (OUD) and co-occurring conditions, to include suicide risk. Here, the relative value of component services and interventions will be tested and evaluated to inform decisions about which components to implement broadly, which to de-implement, and/or how to sequence the implementation of components that are part of an overall service delivery package.
Rationale:
In August 2019, the HEAL Initiative Multi-Disciplinary Working Group called for research studies that seek to improve the provision of care for people with common co-occurring conditions associated with the opioid crisis (e.g., people with mental health disorders, chronic pain, suicide risk, alcohol misuse/alcohol use disorder, and/or other substance use disorders). A variety of approaches have been tested to address the complex needs of patients with co-occurring medical and psychiatric conditions, including multi-component interventions that coordinate treatment activities across multiple providers. For example, interventions delivered in primary care might include several service delivery elements (e.g., screening, evaluation, referral, and/or consultation) as well as specific preventive or therapeutic interventions (e.g., for OUD or for co-occurring interventions). Randomized Controlled Trials (RCTs) have evaluated the effectiveness of multi-element treatment packages, but these trials rarely provide information about the relative contribution of intervention components. Understanding the relative value of constituent components could result in leaner service delivery models for resource constrained environments.
This concept aims to support practice-relevant research that could identify essential components of multi-component service packages for OUD and co-occurring conditions that are associated with improved outcomes. It is expected that research projects would examine the effects of multiple practice-relevant independent variables and employ efficient designs that are powered to examine the effects of individual components. Approaches could include factorial designs and their derivatives (e.g., fractional factorial or partial factorial), Multiphase Optimization Strategy, interrupted time series designs, or other quasi-experimental approaches, where randomization may not be possible.