Background: Over the past decade, hospitals and health systems have increasingly adopted interventions to address the needs of patients with substance use disorders. The Opioid Use Disorder (OUD) Cascade of Care provides a framework for organizing and tracking patient health milestones over time, and can assist health systems in identifying areas of intervention to prevent overdose and maximize the impact of evidence-based services for patients with OUD. However, detailed protocols are needed to guide health systems in how to operationalize the OUD Cascade and track outcomes using their systems' electronic medical records (EMR).
Objective: In this paper, we describe the process of operationalizing and implementing the OUD Cascade in one large, urban, public hospital system.
Methods: Through this case example, we describe the technical processes around data mining, as well as the decision-making processes, challenges encountered, and lessons learned from compiling patient data and defining stages and outcome measures for the OUD Cascade of Care. The current established framework and process will set the stage for subsequent research studies that quantify and evaluate patient progression through each stage of OUD treatment across the health system and identify target areas for quality improvement initiatives to better engage patients in care and improve health outcomes.
Results: The current paper can therefore serve as a primer for other health systems seeking to implement a data-informed approach to guide more efficient care and improved substance use-related outcomes.
Conclusion: An OUD Cascade of Care must be tailored to local systems based on inherent data limitations and services design.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614983 | PMC |
| http://dx.doi.org/10.1101/2023.10.19.23297271 | DOI Listing |
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Department of Global Health, University of Washington Schools of Medicine and Public Health, 3980 15th Ave NE, Seattle, WA, 98105, USA.
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Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States; APT Foundation, New Haven, CT, United States; Center for Interdisciplinary Research on AIDS, Yale University, New Haven, CT, United States; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States; Yale School of Public Health, Department of Epidemiology of Microbial Diseases, New Haven, CT, United States. Electronic address:
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