BACKGROUND: Demand for surgical treatment is rising while operating room (OR) resources are limited. Requests for more resources therefore can only be partly met by repartitioning the existing sparse resources. OBJECTIVE: Our goal is to define a method to allocate OR block times among surgical disciplines in such a way that patients can be treated within an acceptable time after the need for surgery is established. In this paper, we introduce and explore the potential of the concept of the individual patient deviation from the optimal due time (DT) as a potential driver for OR (re-) allocation. STUDY DESIGN AND SETTING: Using retrospective data for abdominal and gynecologic surgery, we analyzed DT deviation and 3 additional modifiers. From this analysis, a reallocation of OR time to the different (sub-) specialties was calculated using a simple model. RESULTS: The results show the capability of measuring and visualizing relative overcapacity versus undercapacity of OR resources with respect to this patient-centered metric of DT. The reallocation results from the model show a potentially significant shift between programs. CONCLUSIONS: We propose the "due-time" concept as a valid measure to quantify OR resource use. The use of a DT-based model provides a transparent, acceptable system for regular reallocation of OR times between and within specialties.
BACKGROUND: Demand for surgical treatment is rising while operating room (OR) resources are limited. Requests for more resources therefore can only be partly met by repartitioning the existing sparse resources. OBJECTIVE: Our goal is to define a method to allocate OR block times among surgical disciplines in such a way that patients can be treated within an acceptable time after the need for surgery is established. In this paper, we introduce and explore the potential of the concept of the individual patient deviation from the optimal due time (DT) as a potential driver for OR (re-) allocation. STUDY DESIGN AND SETTING: Using retrospective data for abdominal and gynecologic surgery, we analyzed DT deviation and 3 additional modifiers. From this analysis, a reallocation of OR time to the different (sub-) specialties was calculated using a simple model. RESULTS: The results show the capability of measuring and visualizing relative overcapacity versus undercapacity of OR resources with respect to this patient-centered metric of DT. The reallocation results from the model show a potentially significant shift between programs. CONCLUSIONS: We propose the "due-time" concept as a valid measure to quantify OR resource use. The use of a DT-based model provides a transparent, acceptable system for regular reallocation of OR times between and within specialties.