Markov Chain Monte Carlo methods for estimating surgery duration

The effect of few historical data on the performance of sample average approximation method for operating room scheduling

“…However, other random sequences also prevail when there are few historical data, that is, surgery duration distributions are log t . This result shows the importance of the reality (Luangkesorn and Eren‐Doğu, 2016; Dexter et al., 2018) that there are multiple cases with few historical data.…”

“…Few historical data and large proportional variability in duration are common for ambulatory surgery (Dexter and Macario, 2000; Dexter et al., 2010; Smallman and Dexter, 2010). A large fraction of surgeries will have very few or no historical data for use in predicting case duration even with several years of historical data (Luangkesorn and Eren‐Doğu, 2016). For example, nationwide in the United States, from 1994 to 1996, approximately 36% of ambulatory surgeries were of a procedure or combination of procedures performed overall once per facility per year (i.e., there would be too fewer than 10 historical data for duration estimation).…”

Strategies for daily operating room management of ambulatory surgery centers following resolution of the acute phase of the COVID-19 pandemic

“…After the peak of the COVID-19 pandemic has subsided, at facilities with a nearly unlimited queue of patients for surgery and with staff working at most 12 h daily, this mathematics can be skipped. These dual objectives will need to be met while relying on few historical data [116][117][118][119][120] for cases' operating room times by procedure because previously phase I post-anesthesia care was not in the operating rooms. Ambulatory surgery centers (i.e., facilities performing many brief cases) [36] should schedule cases into operating room hours selected by policy (e.g., 11 h) calculated for the end of the day to finish reliably by 12-h [121,122].…”

Feasibility of Anesthesiologists Giving Nurse Anesthetists 30-Minute Lunch Breaks and 15-Minute Morning Breaks at a University’s Facilities

“…The 5% lower prediction bounds were calculated by procedure, thus mitigating the effect of individual surgeons having small historical sample sizes for some procedures [ 13 ]. Uncommon procedures at one facility (e.g., one Children’s Hospital) tend to be uncommon at other such facilities [ 14 , 15 ], and there are uncommon procedures observed at many facilities [ 16 , 17 ]. In contrast, facilities have vastly different numbers of breaks and handoffs, reflecting personnel, culture, and organizational aims [ 18 , 19 ].…”