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Table 5 Second of the 3 scenarios for which the described practice of the operating room manager of Hospital A did not match decision-making based on maximizing efficiency of use of operating room time

From: Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

5a. Adapted scenario printed on single page in landscape orientation using Arial 16 point font
    At 12 noon, both OR 1 and OR 13 expect to be ready for their next patient in 45 minutes.
Preparing each of the patients for surgery will take approximately the same amount of time.
    Allocated OR time is from 7:30 AM to 5:00 PM. OR 1 is ahead of schedule by 30 minutes.
OR 13 is behind schedule by 30 minutes. OR 1 is scheduled to end its cases at 7:00 PM.
OR 13 is scheduled to end its cases at 5:00 PM.
    Preparing which of the two patients should be a higher priority?
    OR management, staffing, and case scheduling decisions are made based on four ordered
priorities: Safety, Access, OR efficiency, and Reducing patient waiting on the day of surgery.
    Maximizing OR efficiency (i.e., minimizing over-utilized OR time) is a higher-priority than
reducing patient waiting from scheduled start times. Therefore, preparing the patient for OR 1
is a higher priority than for OR 13, even though OR 13 is behind schedule.
5b. Paragraphs 1, 2, and 5 as stored in computerized library (line breaks added for clarity)
    At 12 noon, both [S1] and [S2] expect to be ready for their next patient in 45 minutes.
Preparing each of the patients for surgery will take approximately the same amount of time.
    Allocated OR time is from [S3] to [S5]. [S1] is ahead of schedule by 30 minutes.
[S2] is behind schedule by 30 minutes. [S1] is scheduled to end its cases at [S4].
[S2] is scheduled to end its cases at [S5].
    Maximizing OR efficiency (i.e., minimizing over-utilized OR time) is a higher-priority than
reducing patient waiting from scheduled start times. Therefore, preparing the patient for [S1]
is a higher priority than for [S2], even though [S2] is behind schedule.
5c. Unsolicited comments based on non-adapted scenario, shown with the corresponding stored parameters. None of the comments relate to the process of decision-making.
  S1 OR 1 is being renovated
  S2 We don't have an OR 13
  S2 OR 13 is in a different building
  S2 OR 13 patients are cardiac, they need more time
  S3 We start the workday at 7:15 AM
  S4, S5 Our workday is supposed to end at 3:30 PM
5d. Steps performed by software to adapt parameters S1 and S2 automatically
  1. Using the most recent 9 four-week periods of data [1, 12], calculated the ORs with the most cases and the second most number of cases. These are S1 and S2. Before using the names of the ORs, checked their names for inclusion of the terms "OR" in upper case or "rm" in either uppercase or lower case. If absent, added a preceding word "OR". The use of 9 periods is based on previous empirical study using training-testing datasets, which showed that each increase in the number of four-week periods resulted in a statistically significant reduction in mean labor costs [12].
5e. Automatic selection of S4 and S5 (i.e., realistic times for ends of workdays in selected ORs)
  2. Using the most recent 9 four-week periods of data [1, 12], excluded cases that were urgent, performed Sunday through Wednesday, Friday, or Saturday. Thursdays are used for the automation because workweeks in different countries are Monday though Friday or Sunday through Thursday.
  3. Identified the last case of the day in each OR on each Thursday, and for every Thursday counted the number of such last cases. Calculated 0.60 multiplied by that number of cases, where 0.60 is the optimal percentile based on over-utilized OR time costing 1.5 times as much as under-utilized OR time [21]. Derivation of optimality is shown on pages 313-316 of Reference [21].
  4. Using the data from step 2, determined for each Thursday the earliest time at which a case exited from an OR while the number of still running ORs was less than the number of cases from step 3.
  5. Took the median of the times from step 4. Set S5 to be the median rounded up to the next 15 minutes (e.g., 4:00 PM would be 4:00 PM whereas 4:01 PM would be 4:15 PM). However, before using it in the scenarios, the space between the numbers and the "PM" was changed to a non-breaking space.
  6. Set S4 equal to S5 plus 2 hr, printed with a non-breaking space between the numbers and the "PM".
5f. Automatic selection of S3 (i.e., realistic time for start of the workday)
  7. Using the cases from step 2, excluded cases starting before 6:45 AM or after 10:00 AM.
  8. From among those cases, selected the first case of the day in each OR on each Thursday.
  9. Rounded each of the start times to the nearest 15 minutes. Created a histogram for the number of ORs among all Thursdays with the same rounded start times.
  10. Set S3 equal to the most common time from step 9, printed with a non-breaking space between the numbers and the "AM".
  1. Choosing staffing is synonymous with calculating optimal allocation of operating room (OR) time based on minimizing the expected inefficiency of use of OR time.