See also:
“SHS2013 Resolving Resistance to OR Scheduling”
“SHS2013 Clarifying OR Turnover Time Concept Graph”
“SHS2013 Clarifying OR On Time Starts”
Many PreOp holding areas have a large variance in their usage. To keep PreOp from being a constraint (bottleneck) for surgery (surgeons complain about waiting for patients to arrive) many are quite large, or they can expand into the PACU during maximum utilization.
We’ll start where I left off on my last post (room starts are at 7am) but with a few changes: The white horizontal bar labeled ‘Schlicter’ is for Dr. Schliter who is the constraint in his 2 rooms (flipping). The horizontal bar beneath that is labeled ‘Multiple’ because there will be four different surgeons (Smith, Jones, Able, White) following each other in only one room but doing the same type of case. The last horizontal bar is for Dr. Green who follows himself in only one room and never has delays (no changes until the last graph where his cut time is 7am). I’m using a more realistic scenario for PreOp times for each case since some of the focus will be on the significant influence on PreOp crowding from non-planned-for late starts throughout the day. As you’ll see, the effects of a late surgeon ripple through the OR and beyond. You’ll need 3 PreOp nurses at least until noon for the Baseline day.
Baseline <click on graph to enlarge)
The next graph shows the effect of prolonging the surgical time in each case by 30 minutes (no changes for Dr. Green who is used as a reference). As you can see, you would need 3 PreOp slots (1 nurse per slot) only for starting the first cases of the day; 2 slots after that, and at least one PreOp nurse for an additional hour until 16:30. There’s an OR downside with the extra hour of overtime in the ‘Multiple’ room. The room downtimes between Schlicter’s cases –1st and 3rd– and –2nd and 4th– are both an hour, but short procedures can be placed in those 1 hour periods with the concomitant use of two more slots for those cases in PreOp (not shown).
The following graph goes back to baseline, then adds a 30 minute delay to each of the 4 cases in the ‘Multiple’ room to show the effect if each surgeon is 30 minutes late. Schlicter is 30 minutes late for the first case, but since he’s flipping rooms he’s always present and doesn’t delay his following cases. No changes for Dr. Green who is still used as a reference.
Notice that Schlicter finishes at 14:30, but the Multiple room doesn’t finish until 19:00. There’s an advantage to flipping rooms with the same surgeon…they’re present, not late for the following cases.
Also notice the extra 30 minute duration of the Multiple room patients. Due to the surgeons’ late arrivals the room is ready, but the patient is still held in PreOp. With more rooms going, more overlapping of PreOp patients will be likely.
The graph below shows results from surgeons’ choices for cut times, with some surgeons arriving late, together for comparison.
Green has his scheduled cut time at 07:00, is never late, and finishes by 16:15. Schlicter has his scheduled cut time at 10:00 am, is never late, and also finishes by 16:15. Multiple has a scheduled cut time at 07:00, but every surgeon in that room arrives late by 30 minutes; the room is finished at 18:15, 2 hours later than the other two rooms.
The PreOp area needs 2 slots most of the time, but a third one for about 15 minutes from 08:45 until 09:00. This is due to spreading the case load through a longer time period. If the PACU nurses can also cover PreOp, then only two full-time PreOp nurses would be needed. There is no concomitant increase in downtime for Schlicter’s rooms, and it is unlikely that an additional procedure can be placed in the 30 minute room downtime periods.
There is great potential for synergy in OR scheduling between concepts and computerized information with simulation capability.
The above graphs show several concepts: room starts, surgeon starts, early starts, late-day starts, surgeon-caused delays, flip-rooms, follow rooms, surgeon turnover time (sTOT), room turnover time (rTOT), and PreOp congestion.
Policy considerations need to strike a balance among money, time, risk management, clinical personnel, patients, power struggles, marketing, the present and the future. Depending on your background, the above graphs will help clarify the interplay between these forces.
The actual results for a schedule will vary depending on the facility, personnel, and cases. I’ve discussed only a few of the relationships in these graphs. Comparing start-times and end-times (in and between the graphs) for all the cases will give you more insight to determine policy and adapt to a changing schedule throughout the day.
See you at SHS2013 in New Orleans.
Copyright 2012 Brian D Gregory, MD, MBA www.hsea.biz