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6th UK and Ireland Implementation Science Research Conference 2023

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  • Plenary & Panel Speakers
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  • Meet the Experts
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  • Programme
  • Plenary & Panel Speakers
  • Organisation Team
  • Meet the Experts

Causal loop diagramming to model, tailor, and test sustainment strategies in multi-level, cross-context implementation efforts

O83

PRESENter

Erika Crable
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authors

Erika L. Crable, Thomas Engell, Ryan Kenneally, Teresa Lind and Gregory A. Aarons

Biography

Dr. Crable is an Assistant Professor at the University of California San Diego with expertise in health policy, health services research, and implementation science. Her research focuses on improving the use of evidence in policymaking, and testing dissemination and implementation strategies to promote access to evidence-based substance use treatment for safety-net and justice-involved populations. She is Principal Investigator of a NIDA-funded study testing dissemination strategies to improve access to medications for opioid use disorder in Medicaid benefit arrays. She is also an Investigator at the UC San Diego ACTRI Dissemination and Implementation Science Center, and alumna of the NIMH/NIDA-funded Implementation Research Institute Fellowship and the NIDA-funded Lifespan/Brown University Criminal Justice Research Training Program Fellowship. Prior to conducting academic research, Dr. Crable worked as a health policy consultant to federal health agencies in the United States including the Centers for Medicare and Medicaid Services, Substance Abuse and Mental Health Services Administration, and Assistant Secretary of Health and Human Services for Planning and Evaluation.

background

Approaches to tailor/test sustainment strategies are needed to ensure that service delivery and population health benefits gained during implementation persist over time. Causal loop diagramming (CLD) is a mixed methods, systems science approach to model causal relationships and feedback loops in complex dynamic health systems. This presentation describes CLD’s utility for understanding complex health systems interrelationships that influence implementation and sustainment. CLD methods are illustrated using a National Institutes of Health-funded study that aims to identify causal relationships critical to successful implementation and sustainment of a quality assurance tool (Lyssn) and evidence-based practice (motivational interviewing) for substance use treatment across a statewide behavioral health system in the U.S.

MEthod

The Exploration, Preparation, Implementation, Sustainment (EPIS) framework guided identification of multi-level outer (state government, service system) and inner (provider organization/clinic) system variables (e.g., agencies/organizations, multi-level actors, competing priorities, policies, money) and their causal interrelationships across implementation phases. Variable data for the CLD was generated by surveys, qualitative interviews, and document review. Member checking with policy, payor, and provider partners aided in confirming or adjusting causal relationships.

results

CLD revealed reinforcing causal relationships for sustainment within the inner context. However, system dynamics across outer-inner contexts balanced the effects on sustainment in the inner context. The CLD revealed potential bridging factors to support inner-outer context alignment and sustainment and were refined with systems partners.

Conclusion

Future system dynamics simulations will test model behavior over time and optimize strategies for sustainment. CLD is a useful mixed methods approach to design sustainment strategies across EPIS phases.