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

Arthritis Care Res (Hoboken). 2021 Jan 15;10.1002/acr.24559. doi: 10.1002/acr.24559. Online ahead of print.


Objective: To develop a claims-based model to predict persistent high-dose opioid use amongst patients undergoing total knee replacement (TKR).

Methods: Using Medicare claims (2010-2014), we identified patients ≥65 years who underwent TKR with no history of high-dose opioid use (>25 mean morphine equivalents (MME)/day) in the year prior. 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 (LASSO) regularization utilizing a total of 83 pre-operative patient characteristics as candidate predictors. A reduced model with ten pre-specified variables which included demographics, 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 (area under the receiver operating characteristic curve (AUC) of 0.85; 95% CI, 0.84-0.86)) in the test set. The reduced model with ten predictors performed equally well (AUC=0.84; 95% CI, 0.84-0.85).

Conclusions: 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.