Trajectories of prescription opioids filled over time
Autoři:
Jonathan Elmer aff001; Riccardo Fogliato aff002; Nikita Setia aff003; Wilson Mui aff003; Michael Lynch aff004; Eric Hulsey aff005; Daniel Nagin aff002
Působiště autorů:
Departments of Emergency Medicine, Critical Care Medicine and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
aff001; Department of Statistics and Data Science, Carnegie Mellon University, PA, United States of America
aff002; Heinz College, Carnegie Mellon University, Pittsburgh, PA, United States of America
aff003; Department of Emergency Medicine, Division of Medical Toxicology, University of Pittsburgh School of Medicine, Pittsburgh PA, United States of America
aff004; Allegheny County Department of Human Services, Pittsburgh, PA, United States of America
aff005
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0222677
Souhrn
We performed a retrospective cohort study that aimed to identify one or more groups that followed a pattern of chronic, high prescription use and quantify individuals’ time-dependent probabilities of belonging to a high-utilizer group. We analyzed data from 52,456 adults age 18–45 who enrolled in Medicaid from 2009–2017 in Allegheny County, Pennsylvania who filled at least one prescription for an opioid analgesic. We used group-based trajectory modeling to identify groups of individuals with distinct patterns of prescription opioid use over time. We found the population to be comprised of three distinct trajectory groups. The first group comprised 83% of the population and filled few, if any, opioid prescriptions after their index prescription. The second group (12%) initially filled an average of one prescription per month, but declined over two years to near-zero. The third group (6%) demonstrated sustained high opioid prescriptions utilization. Using individual patients’ posterior probability of membership in the high utilization group, which can be updated iteratively over time as new information become available, we defined a sensitive threshold predictive of sustained future opioid utilization. We conclude that individuals at risk of sustained opioid utilization can be identified early in their clinical course from limited observational data.
Klíčová slova:
Public and occupational health – Mental health and psychiatry – Criminal justice system – Opioids – Pain management – Epidemiology – African American people – Pennsylvania
Zdroje
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