Utilizing Lean Methodology and Time-Driven Activity-Based Costing Together: An Observational Pilot Study of Hip...

Time-driven activity-based costing (TDABC) has been suggested as the cost-accounting arm of value-based care organizations seeking to address costing challenges from the bottom up by studying the actual processes used in patient care. Lean methodology is a system in which the care pathway is understood at a granular level. In the current study, we attempt to combine these 2 methodologies, providing a robust mechanism to detect meaningful variation. First, we used data from a single surgeon and examined differences in time and cost for patients released on postoperative days 1 or 2. Next, we compared the data from patients discharged on postoperative day 1 with those of patients who underwent an operation by a different surgeon and were also discharged on postoperative day 1.

Consecutive patients who underwent an anterior hip arthroplasty performed by 1 of 2 surgeons and who had degenerative pathology of the hip, an inpatient stay of 1 or 2 days, discharge to home, and no readmission within 30 days of the surgical procedure were identified. We obtained data on patient demographic characteristics and time spent on activities for each personnel role in 15-minute increments occurring during 4 time points of a surgical episode of care (preoperative bay, surgical procedure, post-anesthesia care unit, and inpatient). Personnel costs were set as a ratio relative to the cost of a registered nurse (RN).

Consistent with our hypotheses, both RNs and nursing assistants-certified (NA-Cs) spent more time with patients released on postoperative day 2 compared with those released on postoperative day 1. Also consistent with our hypotheses, we only found significant differences for the time that personnel spent in the surgical procedures.

For patients undergoing total hip arthroplasty for degenerative conditions, we demonstrate that, in the setting of lean methodology, TDABC can detect variability in a meaningful and predictable way. This combination may further enable clinicians and administrators to improve processes, to allocate appropriate resources to specific process steps, and to optimize various treatments across episodes of care.

Economic and Decision Analysis Level IV . See Instructions for Authors for a complete description of levels of evidence.