Maximizing OR and Recovery Room Capacity in an Era of Constrained Resources

Suzanne M Sokal, David L Craft, Yuchiao Chang, David L Berger
Massachusetts General Hospital, Boston, MA

Objective: Determine which of the following configurations of four operating rooms (OR) optimizes patient throughput and main recovery room (RR) workload: three parallel processing (concurrent induction and turnover) operating rooms (OR) and a dedicated three-bed recovery room (mini RR) four traditional ORs or four parallel processing ORs.
Design: Statistical and mathematical models projected the impact of parallel processing on case throughput and RR utilization.
Setting: AMC with 48 traditional ORs with serial induction and turnover and one experimental OR (ORF) with parallel processing.
Participants: All surgical cases from October 2002 - March 2004 (N= 49, 887).
Interventions: A statistical model projected the duration of induction, surgery, turnover and PACU stay for cases performed in a traditional OR (n = 48,667) based on ORF (n = 1220) experience. A stochastic model compared each OR configuration using interval and surgeon-case combination specific probability density functions.
Main Outcome Measures: Each OR configuration was evaluated for case throughput and minutes of work sent to the RR.
Results: Although all cases save OR time with parallel processing, only select surgeon-case combinations translate time saved into incremental cases per day (26%). Without additional RR slots, output from 4 parallel processing ORs further stresses the RR. Three parallel processing ORs and a mini RR balances incremental volume by offsetting RR utilization in 84% of cases.
Conclusions: In a RR constrained environment, three parallel processing OR with a mini RR configuration offers increased throughput and decreased RR workload.

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