To address chronic complaints about “OR inefficiency” due to inaccurate case times and scheduling, a hospital utilizes their new surgical services computer information system to track case times. The plan is to then be able to compute a newly scheduled case’s expected duration based on analysis of previous cases’ surgical times.
However, 6 months after adoption of this new scheduling approach using historical data, the accuracy of the OR schedule has not improved. The hospital vice president notes that approximately the same number of complaints from surgeons and patients continue.
Why has accuracy not improved using analysis of historical data? It turns out that scheduling case durations correctly is a more complex undertaking than expected and the level of certainty desired by many stakeholders is often not possible. Best practice is to have OR management accept and manage some of the uncertainty in how long an individual case may last.
The take home message from this white paper is that averaging historical data for case duration predictions does not increase prediction accuracy as much as most people think it should. This is due to several key principles:
• The combination of a great variety of procedures and the large number of surgeons on most hospitals staffs makes it such that on average half of the cases scheduled in a hospital’s surgery suite will have less than 5 previous cases of the same primary procedure type & same surgeon during the preceding year. In other words, often there are not enough similar enough cases to make a prediction regardless of whether statistics are used or how long one goes back in the system to pull out similar cases.
• Also, if case durations for a surgeon performing a particular operative procedure vary significantly due to the nature of the surgery (cancer resection is one example as every tumor is different), then it is also intrinsically very difficult to make accurate predictions, no matter how many previous cases are examined.
• Yet another barrier to truth in scheduling is the statistical distribution of case times which most often are not bell shaped (normal) distributions. This variance, for example, complicates using the average of historical case durations because unusually long cases (outliers) have a disproportionately large effect
The surgeon and the surgical procedure are the two most important determinants of surgical time. Some case lengths are easier to predict than others. These include surgical specialties that operate on the body surface or extremities, where operations are often standardized. On the other hand, surgery duration for many cases is intrinsically difficult to predict especially if the procedure is complex, and the operative steps are not standardized such as for ENT cancer surgery and major intra-abdominal procedures.
Various methods to estimate case duration can be utilized. (Table 1)
Table 1. Models to predict case duration
• mean of historical case duration
• surgeon estimate
• use surgeon estimate in combination with historical data to create new estimate
• adjust for case complexity (e.g. simple, average, or complex)
• some combination of the above
The variance of statistical distributions of case times complicates just using the mean of historical case durations because unusually long cases (outliers) have disproportionately large effect. (Table 2)
Table 2. Possible values that can be computed from historical data
• Median – decreases the impact of unusually long cases
• Trimmed mean – delete lower & upper 10% of the durations and then take the average
• Geometric mean – At some hospitals surgeons consistently shorten their case duration estimates if they perceive they have too little OR time and need to make sure they “fit” their cases into the O