Forecasting surgery-duration (SD) accurately is a pre-condition for efficient utilization of operating theatres. An explanatory model may provide a good tool to produce such forecasts.
In this post, I deliver essential details of a new article, published recently in a peer-reviewed journal (Shore, 2020; see details below). A new explanatory model for SD is developed, and empirically validated, using a database of ten-thousand surgeries, performed in an Israeli hospital.
The new publication indeed complements a previous article on the same subject, published by me over thirty years ago (Shore, 1986; see details below).
One may realize that this article in practice presents a general model for performance-time of any of the three possible categories of work-processes: Repetitive, semi-repetitive and non-repetitive/memoryless. However, applying the model does not require specifying in advance which category the work-process belongs to. This becomes apparent as a result of data analysis.
Part of the Abstract and a link to the new article are provided below (please share).
Article title: An explanatory bi-variate model for surgery-duration and its empirical validation
Journal: COMMUNICATIONS IN STATISTICS: CASE STUDIES, DATA ANALYSIS AND APPLICATIONS
DOI (press to read full Abstract and References):
Limited-number free downloads (please download only if seriously interested):
Other statistical applications on this blog (sample);
Modelling the distribution of surgery-duration has been the subject of much research effort. A common assumption of these endeavours is that a single distribution is shared by all (or most) subcategories of surgeries, though parameters’ values may vary. Various distributions have been suggested to empirically model surgery-duration distribution, among them the normal and the exponential. In this paper, we abandon the assumption of a single distribution, and the practice of selecting it based on goodness-of-fit criteria. Introducing an innovative new concept, work-content instability (within surgery subcategory), we show that the normal and the exponential are just two end-points on a continuous spectrum of possible scenarios, between which surgery-duration distribution fluctuates (according to subcategory work-content instability). A new explanatory bi-variate stochastic model for surgery-duration is developed, which reflects the two sources affecting variability— work-content instability and error…
Shore, H. 1986. “An Approximation for the Inverse Distribution Function of a Combination of Random Variables, with an Application to Operating Theatres.” Journal of Statistical Computation and Simulation 23 (3):157–181.