Background: Rotator cuff repair (RCR) is a frequently performed outpatient orthopaedic surgery, with substantial financial implications for health-care systems. Time-driven activity-based costing (TDABC) is a method for nuanced cost analysis and is a valuable tool for strategic health-care decision-making. The aim of this study was to apply the TDABC methodology to RCR procedures to identify specific avenues to optimize cost-efficiency within the health-care system in 2 critical areas: (1) the reduction of variability in the episode duration, and (2) the standardization of suture anchor acquisition costs. Methods: Using a multicenter, retrospective design, this study incorporates data from all patients who underwent an RCR surgical procedure at 1 of 4 academic tertiary health systems across the United States. Data were extracted from Avant-Garde Health’s Care Measurement platform and were analyzed utilizing TDABC methodology. Cost analysis was performed using 2 primary metrics: the opportunity costs arising from a possible reduction in episode duration variability, and the potential monetary savings achievable through the standardization of suture anchor costs. Results: In this study, 921 RCR cases performed at 4 institutions had a mean episode duration cost of $4,094 ± $1,850. There was a significant threefold cost variability between the 10th percentile ($2,282) and the 90th percentile ($6,833) (p < 0.01). The mean episode duration was registered at 7.1 hours. The largest variability in the episode duration was time spent in the post-acute care unit and the ward after the surgical procedure. By reducing the episode duration variability, it was estimated that up to 640 care-hours could be saved annually at a single hospital. Likewise, standardizing suture anchor acquisition costs could generate direct savings totaling $217,440 across the hospitals. Conclusions: This multicenter study offers valuable insights into RCR cost as a function of care pathways and suture anchor cost. It outlines avenues for achieving cost-savings and operational efficiency. These findings can serve as a foundational basis for developing health-economics models. Level of Evidence: Economic and Decision Analysis Level III. See Instructions for Authors for a complete description of levels of evidence.
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