Anesthesia Providers, Reentry Into Practice, Relapse Prevention, Return to Use, Strategies Predicting Relapse, Substance Use Disorder



  1. Carter, T'Anya PhD, CRNA
  2. Heaton, Karen PhD, COHN-S, FNP-BC, FAAN, FAAOHN
  3. Merlo, Lisa J. PhD, MPE
  4. Roche, Bernadette T. EdD, APN, CRNA, FAANA
  5. Puga, Frank PhD


Background: Relapse prevention for those with substance use disorder (SUD) is an evolving practice. Initiatives focused on relapse prevention from other populations may provide the foundation for future considerations and recommendations for recovering anesthesia providers in the workplace. The purpose of this scoping review was to examine what is known about return-to-use prediction and prevention strategies in various populations struggling with SUDs to inform future considerations and implications for recovering anesthesia providers with a history of SUD.


Methods: The Arksey and O'Malley framework was used to conduct a scoping review of the literature. A systematic search was conducted across three databases (PubMed, CINAHL, and PsycInfo) for relevant literature. Search terms used were "measures predicting relapse in substance use disorder" and "relapse prevention in substance use disorder AND anesthesia." Data from articles that met the eligibility criteria were extracted and summarized by the primary author.


Results: The search identified 46 articles highlighting various relapse prediction and prevention strategies related to craving and stress, underlying biological factors, neuroimaging, and mindfulness. Relapse prediction and prevention strategies ranged from cell phone applications, monitoring biological markers, and functional neuroimaging of the brain.


Conclusions: Relapse is a concern for individuals with a history of SUD. For anesthesia providers, immediate access to powerful anesthesia medications requires return-to-use prediction and prevention strategies when anesthesia providers return to work after SUD treatment. Although some identified strategies are practical, more research is needed to predict and prevent return to use for recovering anesthesia providers.