Time-driven activity-based costing to model the utility of parallel induction redesign in high-turnover operating lists.

BACKGROUND: Value-based healthcare is strongly advocated to reduce the spiralling rise in healthcare expenditure. Operating room efficiency is an important focus of value-based healthcare delivery due to high costs and associated hospital revenue derived from procedural streams of care. A parallel induction design, utilising induction rooms for anesthetising patients, may improve operating room efficiency and optimise revenue. We used time-driven activity-based costing (TDABC) to model personnel costs for a high-turnover operating list to assess value of parallel induction redesign.

METHODS: We prospectively captured activity data from high-turnover surgery allocated to induction of anesthesia within the operating room (serial design) or within induction rooms prior to completion of preceding surgery (parallel design). Personnel costs were constructed using TDABC following assignment of a case-mix that integrated our activity data. This was contrasted against procedural revenue to assess value of projected case throughput.

RESULTS: Under a parallel induction design, projected operating list duration was reduced by 55 min at marginal increase (1.6%) in personnel costs as assessed by TDABC. This could facilitate an additional short duration surgical case (e.g. Wide Local Excision, with potential additional revenue of $2818 per day and $0.73 M per annum per operating room.

CONCLUSIONS: Parallel induction design reduces non-operative time at minimal increase in personnel costs for all-day, high turnover surgery. An additional short duration surgical case is likely feasible under this model and represents a value investment with minimal requirement for additional personnel resources.

IMPLICATIONS: A parallel induction design, within the constraints of finite healthcare funding, may help alleviate some of the global increase in demand for surgical capacity that accompanies an expanding and aging population.