4.4 Article

Development of a Medicare Claims-Based Model to Predict Persistent High-Dose Opioid Use After Total Knee Replacement

Journal

ARTHRITIS CARE & RESEARCH
Volume 74, Issue 8, Pages 1342-1348

Publisher

WILEY
DOI: 10.1002/acr.24559

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Funding

  1. NIH (National Institute of Arthritis and Musculoskeletal and Skin Diseases) [R01AR069557]
  2. AbbVie
  3. Amgen
  4. Pfizer
  5. Corrona
  6. Genentech
  7. Janssen

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This study aimed to develop a claims-based model for predicting persistent high-dose opioid use among patients who underwent total knee replacement (TKR). The study utilized Medicare claims data and employed group-based trajectory modeling to identify different patterns of opioid use. The findings revealed that approximately 10.6% of older patients became persistent high-dose opioid users after TKR.
Objective To develop a claims-based model to predict persistent high-dose opioid use among patients undergoing total knee replacement (TKR). Methods Using Medicare claims (2010-2014), we identified patients ages >= 65 years who underwent TKR with no history of high-dose opioid use (mean >25 morphine milligram equivalents [MMEs]/day) in the year prior to TKR. We used group-based trajectory modeling to identify distinct opioid use patterns. The primary outcome was persistent high-dose opioid use in the year after TKR. We split the data into training (2010-2013) and test (2014) sets and used logistic regression with least absolute shrinkage and selection operator regularization, utilizing a total of 83 preoperative patient characteristics as candidate predictors. A reduced model with 10 prespecified variables, which included demographic characteristics, opioid use, and medication history was also considered. Results The final study cohort included 142,089 patients who underwent TKR. The group-based trajectory model identified 4 distinct trajectories of opioid use (group 1: short-term, low-dose; group 2: moderate-duration, low-dose; group 3: moderate-duration, high-dose; and group 4: persistent high-dose). The model predicting persistent high-dose opioid use achieved high discrimination (receiver operating characteristic area under the curve [AUC] 0.85 [95% confidence interval (95% CI) 0.84-0.86]) in the test set. The reduced model with 10 predictors performed equally well (AUC 0.84 [95% CI 0.84-0.85]). Conclusion In this cohort of older patients, 10.6% became persistent high-dose (mean 22.4 MME/day) opioid users after TKR. Our model with 10 readily available clinical factors may help identify patients at high risk of future adverse outcomes from persistent opioid use after TKR.

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