Development of a Medicare Claims–Based Model to Predict Persistent High‐Dose Opioid Use After Total Knee Replacement. Issue 8 (22nd April 2022)

• Record Type: Journal Article
• Authors: Gopalakrishnan, Chandrasekar; Desai, Rishi J.; Franklin, Jessica M.; Jin, Yinzhu; Lii, Joyce; Solomon, Daniel H.; Katz, Jeffrey N.; Lee, Yvonne C.; Franklin, Patricia D.; Kim, Seoyoung C.
• Is Part Of: Arthritis care & research. Volume 74:Issue 8(2022)
• Page Start: 1342
• Page End: 1348
• Publication Date: 2022-04-22
• Subjects: Arthritis -- Periodicals; Rheumatism -- Periodicals; 616.72
• DOI: 10.1002/acr.24559
• Languages: English
• ISSNs: 2151-464X

Abstract

Abstract : 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.