Previous studies of shared decision making for elective surgical care between the patient and the health care provider have examined the patients’ understanding of treatment options and the decision whether to have surgery.1 In our survey, we examine patients’ perspectives on surgical case scheduling, including wait time. Suppose that a scheduler assumes that his/her role is to inform the patient that the surgeon whom the patient saw in clinic is available Monday or Wednesday in 5 weeks and to facilitate the choice of those dates. From the perspective of the average (median) patient, the survey tries to determine whether the scheduler’s assumption represents an example of the surgical team’s failure in its responsibility to discuss all treatment options with the patient. Such an assumption would deprive the patient of the knowledge necessary for the patient to participate in a decision influencing his/her health care options.
The survey was deemed exempt from institutional review board (IRB) review on July 22, 2016, by the Mayo Clinic IRB (IRB application 16-002308). Completion of the web survey by patients served as implicit consent to participate in the study.
For clarity, throughout this article, we refer to our “survey” as being composed of “demographic questions” followed by “study questions.” In the Discussion, we describe the many restrictions on the potential study questions, which led to the final survey design.2–12
The following study questions were used to assess each patient’s maximum waiting time sufficient to discuss having another surgeon perform their procedure:
There are several reasons to wait for surgery. Some patients are not ready medically for surgery. Some patients want to wait for surgery to be convenient for their family members. We are interested in learning your preferences as if neither of these reasons was an issue.
Following these instructions, the patients were asked:
- 1. Assume the consultant surgeon (ie, the surgeon in charge) you met in clinic did not have time available to do your surgery within the next 4 workdays, but his/her colleague would have had time to do your surgery within the next 4 workdays. Would you have wanted to discuss with a member of the surgical team (eg, the scheduler) the availability of surgery with a different, equally qualified surgeon at Mayo Clinic who had time available within the next 4 workdays, on a date of your choosing?
If the answer was No, then the next study question appeared:
- 2. Assume the consultant surgeon (ie, the surgeon in charge) you met in clinic did not have time available to do your surgery within the next 2 weeks, but his/her colleague would have had time to do your surgery in 1 or 2 weeks. Would you have wanted to discuss with a member of the surgical team (eg, the scheduler) the availability of surgery with a different, equally qualified surgeon at Mayo Clinic who had time available in 1 or 2 weeks, on a date of your choosing?
If the answer to this second study question was No, then the third study question appeared, substituting “4 weeks” for “2 weeks” and “3 or 4 weeks” for the “1 or 2 weeks.” If that answer was No, the fourth study question appeared, substituting “8 weeks” for “4 weeks” and “5 to 8 weeks” for the “3 or 4 weeks.” Finally, if that answer was No, then the fifth study question appeared, substituting “12 weeks” for “8 weeks” and “9 to 12 weeks” for the “5 to 8 weeks.”
To illustrate the sequence of the survey’s questions, suppose that a patient answered the second question as “No,” but then saw the third question, and decided to change the response to the second question. If that happened, then the third question disappeared from the web page, based on the answer to the second question. The patient, therefore, had 3 options for responding to the study questions: close the web browser (ie, answer all of the demographic questions and none of the study questions); answer “Yes” to one and only one of the study questions; or answer “No” to every study question. In the “Survey Design” section, below, we address why the study questions were presented sequentially to all patients (who completed demographic questions).
Prior data suggested the importance of 2 weeks and 4 weeks as options. Among parents in California arranging for their children’s surgery, the 25th, 50th, and 75th percentiles of the “ideal waiting time” were 2, 3, and 4 weeks, respectively.13 The percentiles of the “longest acceptable waiting” time were 4, 6, and 10 weeks, respectively.13 From our prior simulation study, use of a maximum wait of 4 weeks (and performing the case in overutilized operating room (OR) time if necessary to maintain that maximum) results in an average waiting time of approximately 2 weeks.7 Among a mixture of adult patients and parents in Iowa, the 25th, 50th, and 75th percentiles for the longest acceptable waiting time were 1, 2, and 4 weeks, respectively.7 Among adults in Germany, waiting times of 1 week were preferred to 2 weeks, and a waiting time of 4 weeks was associated with reduced chance of choosing that facility for surgery.14 To have a maximum waiting time category that might be selected, but rarely so, between the options of 8 or 12 weeks (see Discussion), we selected 8 weeks, because 12 weeks was greater than the observed 75th percentile of the “longest acceptable waiting” time of 10 weeks.13
One Demographic Question to Assess Convergent Validity
There are 3 attributes to the study questions: each patient’s desire (or not) to discuss the option of changing the surgeon, the maximum waiting time,7,13,14 and the choice of the date of surgery within the waiting time interval.15 As summarized in the Discussion, the attribute with the strongest prior evidence of importance was the maximum waiting time. We asked a demographic question about the patient’s actual waiting time to provide some assessment as to whether the study questions were indeed assessing, at least in part, perceptions related to waiting time. This question assessed “convergent validity,” the degree to which 2 measures of constructs that theoretically should be related are in fact related. We asked: “how long was it from when you first met the surgeon who performed your surgery until the date your surgery was performed?” We used the same categories as for our study questions: within 4 workdays; between 5 workdays and 2 weeks; between 3 and 4 weeks; between 5 and 8 weeks; between 9 and 12 weeks; or longer than 12 weeks.
Two Demographic Questions and Studied Categories of Procedures for Adjusted Estimates
As described below, since we used a web survey and expected to have a low response rate, we incorporated 3 approaches to mitigate the potential influence of response bias. One of these approaches was to design the study to include the plan to compensate for heterogeneity between the nationwide sex and age distribution of the procedure versus that of the respondents, if necessary, based on the results.
The US Agency for Healthcare Research and Quality (AHRQ) provides the sex and age distribution nationwide for categories of surgical procedures using Clinical Classification Software (CCS).16 These are downloadable from HCUPnet.17 Two CCS-included procedures that are principally elective surgery and sufficiently common that standard errors of incidences are narrow even when stratified by sex and age are CCS 36, “lobectomy” or “pneumonectomy” (lung surgery) and CCS 84, “cholecystectomy” and “common duct exploration” (gallbladder surgery). We used these 2 categories of procedures in our previous study of patient-centered decision making in response to anesthesia drug shortages (see Discussion).18 At the time of the design of the current study, AHRQ had online the CCS defined using the 2013 surgical Current Procedural Terminology (CPT) codes.19 We used those 2013 CPT codes to obtain potential respondents from the Mayo Clinic database.
To have the option of adjusting our results based on the sex and age distribution nationally, the demographic questions asked of each patient included sex and age. We used “sex” rather than “gender,” and current age in categories of 18 to 44, 45 to 64, 65 to 84, and 85+ years, to match precisely the information available from HCUPnet. Only adults at the time of surgery were sent e-mail invitations.
Suppose that sex and/or age were associated with responses. Then, we planned a priori to use that knowledge to extrapolate, from our sample, an estimate of the nationwide percentage of patients undergoing lung resection or cholecystectomy who want to be asked about having another surgeon perform their procedure to reduce waiting time.
Among patients undergoing lung resection, some patients receive chemotherapy within 3 months before surgery. These patients would usually have a mandatory waiting period of 4 to 8 weeks before surgical resection to allow the patient to recover from any side effects from the chemotherapy. These patients’ mindsets about waiting might be different from those of patients not scheduled for chemotherapy. In the e-mail cover letter to the patients who had undergone lung resection, the study exclusion criterion was explained. Also, if a potential lung resection patient selected the hyperlink and proceeded to the survey, the first question asked the patient about chemotherapy. If the patient answered “No” to having received chemotherapy within 3 months prior to lung resection, the demographic questions were presented. If the patient answered “Yes” to the chemotherapy question, the patient no longer could access the demographic or study questions.
Two Demographic Questions to Assess Generalizability of Results to Other Procedures
Each patient’s choice for the maximum waiting time sufficient to consider having another surgeon perform their procedure may be related to the proximity of their home to the hospital where surgery was to be performed. For example, patients who traveled great distances to receive care at the Mayo Clinic (eg, international patients) may prefer not to return months later.15,20 We asked: “What was the driving time from your residence when you had surgery to Mayo Clinic?” As used previously,15 options for driving times provided were 0 to 29 minutes, 30 to 59 minutes, 60 to 89 minutes, 90 to 119 minutes, 120 to 179 minutes, or 180 minutes or longer (including flying to the city).
Patients who have had multiple ambulatory clinic visits with a surgeon may be hesitant to have a different surgeon perform the surgical procedure. However, at the University of Iowa, both among patients undergoing outpatient surgery and among all patients who were outpatient preoperatively, the median number of visits at the surgeon’s clinic before surgery was 2. This number remained the same even when calculations were weighted by American Society of Anesthesiologists’ Relative Value Guide units.21 Therefore, we asked the number of office visits that the patient had with the surgeon before the day of their surgery.21 Among all surgical procedures at a University hospital, there were 4 or fewer visits for 84% of patients, weighted by the procedure’s American Society of Anesthesiologists’ Relative Value Guide Units.21 Therefore, we asked: “how many office visits that lasted at least 5 minutes did you have with your surgeon before the day of your surgery?” The categories we provided were 0, 1, 2, 3, 4, or 5 or greater number of office visits.21
As described above, one approach that we used to address nonresponse was to ensure that, if results were sensitive to sex and/or age, we could adjust the results based on the US nationwide sex and age distribution of the procedure. The second and third approaches that we followed were based on our e-mail and web survey designs.
Potential respondents could not see the study questions until after they had submitted the demographic questions. The study questions were, realistically, complicated (ie, not predictable from our e-mail). The cover e-mail was limited to a single sentence about the survey: “you are being asked to participate in a research survey evaluating patient opinions about whether surgeons should discuss the option to schedule surgery with another qualified surgeon to reduce the time that patients may have to wait for surgery.” Although postal mail probably would have increased our response rate, we did not want the patients to be able to review the questions and then choose whether to respond based on perceptions of what their answer should be.
The survey was organized as 2 submissions: the first contained demographic questions, while the second contained study questions. Therefore, we designed the survey to include 2 sensitivity analyses based on the patients who completed demographic questions and then dropped out of the study. First, we repeated analyses assuming that all of these patients would have answered that they wanted to discuss having the procedure performed by a different surgeon, within 4 days (ie, the minimum). Second, we repeated analyses assuming that all of these patients would have chosen “No” to all study questions (ie, would prefer not to discuss the option of another surgeon).
E-mails to the patient were not secure. Therefore, working with the IRB, we obtained a population of e-mail addresses for each of the 2 categories of procedures, but no other information such as sex, date/year of surgery, or Mayo Clinic campus. The patients considered for inclusion in the study were those who had provided their e-mail address to Mayo Clinic and had undergone 1 of the 2 categories of procedures (lung or gallbladder surgery) between January 1, 2011, and March 31, 2016, at the Jacksonville, FL, or Phoenix, AZ, hospitals. The final date was chosen to ensure a sufficient period for patient recovery and conclusion of postoperative treatment (eg, radiation or chemotherapy) before receipt of the survey e-mail.
The first e-mail was sent on October 31, 2016. For each of the 2 categories of procedures, 490 patients’ e-mail addresses were selected at random (see Power Analysis, below). When sent, the e-mails that “bounced back” were counted. An equal number of additional e-mail addresses (without duplication) were selected randomly from the patient list to replace the e-mails that were returned as undeliverable. The process was continued until there were 490 valid e-mail addresses for each of the 2 categories of procedures. This required 565 e-mails to patients who had undergone lung lobectomy and 529 for cholecystectomy. A single follow-up reminder e-mail was sent to the 980 valid e-mail addresses on November 11. The website was closed on December 15, 2016. The last responses were obtained on December 11 for lung lobectomy and December 4 for cholecystectomy.
The survey was built and executed using the REDCap Survey Software, version 4.13.17 (© 2016 Vanderbilt University, Nashville, TN).22 E-mails and clicked hyperlinks were tracked by REDCap so that the same e-mail address could not provide more than 1 response. REDCap (4.13.17) does not have capability to randomly generate the study question sequence based on each patient’s individual response. Furthermore, if this had been done, there would not have been the ensured ordinal response (eg, 4 workdays < 2 weeks), resulting in greater error variance. The sample size was already the maximum feasible for the organization.
The sample size of 490 valid e-mail addresses for each of the 2 categories of procedures was based on there being one study question to be answered per category of procedure: the median value for the maximum waiting time (if any) sufficient to consider having another surgeon provide their surgical care. Testing for the median was done based on the standard of informed consent (in some jurisdictions) being that of the expectations of a “reasonable patient.”23 By definition, the median (average) patient is “reasonable.” The interval from 1 day to the maximum waiting time for the median patient incorporates every possible choice of waiting times consistent with individualized and patient-centered decision making. Unfortunately, the prior data available were not in units of weeks, but percentages of patients. In Alberta, Canada, 35% of surveyed patients “would change to a surgeon with a shorter waiting time” for hip or knee arthroplasty.24 With 2-sided α = .05/2, there would be 90% statistical power to differentiate 50% (corresponding to median) and 35% (from Alberta) with 133 respondents. The “0.05/2” corresponded both (a) to 2 medians if responses differ between groups or (b) 1 test to establish that the groups do not differ and a second single test for the median in that circumstance. In our previous postal survey of Mayo Clinic patients after laparoscopic cholecystectomy, the response rate was 27.2%.18 Therefore, the number of patients to recruit for the survey from each of the 2 CCS was approximately 490, where 490 = 133/27.2%. We expected that the response rate we would obtain by e-mail would be less than the 27.2%. However, we also expected that the sample size needed for a narrow confidence interval for the median waiting time would be less than the 133 respondents.
The confidence interval for the median waiting time response was calculated using the exact binomial distribution method of Blyth-Still-Casella (StatXact-11; Cytel, Cambridge, MA).25 The association between waiting time response and category of procedure was tested using the Wilcoxon-Mann-Whitney test and the Kolmogorov-Smirnov tests. The 2-sided P values were exact. Associations with actual reported waiting time, male sex, age in categories, driving time, and number of office visits were quantified using the Kendall τb. P values also were 2-sided and exact.
Among the 980 invited patients, 135 respondents completed the survey, plus 6 completed the demographic questions but dropped out after the study questions were displayed.
The median responding patient wanted to discuss having another surgeon perform his or her procedure even if the wait would be 4 days or less (Table 1). The 97.5% 2-sided (conservative) confidence interval for the median maximum wait was 4 days to 4 days.
Patients’ choices for the maximum waiting time sufficient to discuss having another surgeon perform the procedure did not differ between those who underwent lung resection or cholecystectomy (Wilcoxon-Mann-Whitney test P = .91 and Kolmogorov-Smirnov test P = .98). The percentages of patients whose response to the study questions was 4 days were 58.8% (40/68) among the lung resection patients and 58.2% (39/67) among the cholecystectomy patients.
As one extreme option, suppose that all 6 respondentsa who dropped out would have answered “Yes” to discussing the possibility of another surgeon performing the procedure if the resulting wait for surgery would be 4 workdays or less. Then, the 97.5% confidence interval for the median would be 4 days to 4 days. As the other extreme of the sensitivity analysis, suppose that all 6 of these patients would have answered “No” to discussing the option of another surgeon performing the procedure, even if the wait were >12 weeks. Then, the median response would still have been 4 days. However, the 97.5% 2-sided confidence interval for the median would have equaled 4 days to 2 weeks (ie, “Yes” discuss the option of a surgical colleague performing the procedure within 1 or 2 weeks).
There was a positive association between the maximum waiting time sufficient to discuss having another surgeon perform the procedure and the reported actual waiting time (Kendall τb = 0.22, P = .0014; Table 2). Pairwise, the maximum waiting times sufficient for discussion were less than the actual waiting times (Wilcoxon signed-ranks test 2-sided P = .0013). Although 58.5% (79/135) of respondents wanted to discuss having surgery within 4 days, only 20.7% (28/135) of these Mayo Clinic patients actually underwent surgery within 4 days. These results suggest that the study questions were indeed measuring an attribute related to waiting time.
Generalizability and Adjustment of Estimates
There was no association between the maximum waiting times to discuss having a different surgeon perform the procedure and male sex (τb = −0.00, P = .99) or age (τb = 0.05, P = .55). Thus, our waiting time results were not adjusted using national data based on the patients’ sex and age distribution.
Generalizability of Findings
Results were also not associated with covariates likely specific to the studied procedures and hospital. There was no association between the maximum waiting times to discuss having a different surgeon perform the procedure and travel time to the hospital (τb = −0.02, P = .75) or number of office visits before surgery (τb = 0.10, P = .20).
Whether our results are interpreted as a median of 4 days, or the upper confidence limit for the sensitivity analysis is used when incorporating nonresponse bias (2 weeks), the implication generally would be practically the same because often 1 week is needed for a patient to be prepared for surgery. The implication is that, if more than 1 surgeon at a hospital performs a particular procedure, and another surgeon has OR time sooner, more than 50% of the patients would want to discuss the option of having surgery performed by the different surgeon if the waiting time were decreased and the patient contributes to the choice of the day of surgery. By definition, the median patient’s expectations should be considered reasonable. Consequently, our findings essentially are that it is medically paternalistic not to discuss with the patient the option of another surgeon performing the procedure if the surgery cannot be performed right away. Since the choice of surgeon and opportunity to undergo a procedure sooner are important health care decisions, it is considered the ethical duty of clinicians to share such decisions with patients.26 Our results indicate that bringing up the option with the patient of changing surgeons when a colleague is available and has the OR time available to perform the procedure sooner is being respectful of most patients’ individual preferences (ie, offering such a choice is patient centered). The shared decision making would also result in a considerable reduction in mean patient waiting times, underutilized OR time, overutilized OR time, and the hours that anesthesiologists, nurse anesthetists, and OR nurses work late (see below).7,27
Previous OR Management Results Influencing the Study and Its Applications
The survey did not consider the process of deciding which surgeon sees the patient for the initial clinic visit. Such an intervention would generally not decrease patients’ mean times to surgery.2 The use of “a pooled appointment list and scheduling appointments with the first available” surgeon, not necessarily the one receiving the referral, “increases the chances of getting an appointment” promptly.2 However, it also can increase the time from appointment to surgery, because the surgeon with a clinic appointment available sooner often does not have promptly available OR time.2 The total time from referral to surgery generally does not differ from such an intervention.2
The survey did not consider coordination of clinic and OR schedules, because consideration of surgeons’ available OR times by the scheduler when making clinic appointments can be counterproductive for the hospital: it decreases both OR productivity (eg, productivity of anesthesiologists) and the surgical group’s productivity.3 In previous work, we studied such coordination of clinic schedules among general thoracic surgeons.3 We relied on the fact that when the number of patients in a surgeon’s OR queue is considered, the OR scheduler functions similarly to a store clerk who counts supplies in inventory. The delay from when a patient is scheduled into a surgeon’s clinic until the patient is booked for surgery is analogous to the time it takes for a distributor to deliver supplies to the store. “Just as the delay impacts inventory management, the delay affects the size of OR queues.” When the clerk considers “the size of the surgeons’ OR queues,” but disregards the patients who were scheduled into the clinic but not yet seen (and thus not yet scheduled for surgery), variability in the OR workload will necessarily increase.3 The resulting increase in variability in OR workload will, necessarily, increase underutilized OR time, increase overutilized OR time, decrease OR productivity, and decrease surgical group productivity.3 To reduce patient waiting times while not substantively reducing OR productivity, the decisions of which surgeon sees the patient during the clinic appointment and which surgeon does surgery need to be 2 separate decisions.3 Thus, in the survey, we considered patients’ preferences on shared decision making to reduce patient waiting times over the period from (1) decision made to have surgery until (2) surgery.
The survey did not consider changes in the hospital where surgery was performed, even though previous studies of shared decision making for surgical scheduling have included the choice of the hospital.4 For surgery that is inpatient postoperatively (eg, lung resection), 78% of patients reported that “surgeon reputation” “would influence their” decision of the hospital “a lot, followed by the hospital having nationally recognized surgeons (63%).”5 Among patients undergoing major surgery including lung resection, “42% of patients said they decided equally with their physician about where to have surgery; 22% of patients said they were the main decision maker”; “5% indicated that the role belonged to a family member,” and “the remaining 31% of patients said the physician was the main decision maker of where they would have surgery.”6 Therefore, the study questions were designed only to consider a change in the surgeon, not a change in the hospital, and this plan was repeated in each of the study questions (see below).
The survey was not based on the mean (expected) waiting time, but on the patient’s maximum possible waiting time. Mean waiting times cannot be measured reliably for individual surgeons, just as the mean underutilized OR time, overutilized OR time, and/or OR utilization cannot be measured accurately by surgeon.7 To appreciate why this is so, consider that it is straightforward statistically to measure the available OR time for a surgeon who has essentially no extra OR time.8 However, this is not so for the surgeon with a moderate adjusted OR utilization.8 Surgeons with relatively long case durations (eg, lung resection) have small numbers of cases per week. Typically, the difference is just 1 case between one of the surgeon’s OR days having a modestly below (the surgeon’s) average adjusted utilization versus modestly greater than average utilization.7–9 Consequently, random variations in the times between successive patients’ requests to be scheduled for surgery result in substantial variability in the weeks that patients wait.7,8
The survey did not consider maximum possible patient waiting time categories briefer than 4 days. The maximum waiting time categories had to be: (1) multiples of the period of the OR’s master surgical schedule; and (2) greater than 1 period of that master schedule.10,11 At Mayo Clinic, where the survey was performed, an every-other-day surgical scheduling system was used. Thus, the briefest possible maximum wait was 4 days. Consequently, our first category was “within 4 workdays.”
The survey did not limit specification of case scheduling to the maximum wait time.12 The study questions included an explanation for how the date of surgery would be chosen within a waiting time interval (eg, 9–12 weeks). For instance, an airline may consider a service to be flying between 2 cities (eg, Iowa City to Chicago). The city pairing is like a surgical procedure. However, customers (ie, patients) do not consider the service to be a flight from Iowa City to Chicago, but consider it to be a flight on a particular date of the patient/customer’s choosing (eg, January 1). Previously, we found this was so for cataract surgery.15 Most patients who underwent cataract surgery would have been “willing to travel” extra time so that they “can choose the day” of surgery.15 Consequently, in the study questions, within the waiting period specified, the patient was said to choose the date of surgery. Provided that a case is not scheduled into overutilized OR time, this vague specification of how cases are scheduled has negligible influence on overutilized OR time, underutilized OR time, and anesthesia group (OR) productivity.7,9,28–31
Finally, the survey did not consider reductions in patient waiting time by performing the case late in the workday or on weekends, because outcomes and/or OR team members sometimes differ.32–38 The following hypothetical scenario describes how to combine the preceding case scheduling restrictions to apply our study’s results:
A surgical suite has nurses and other hourly personnel scheduled from 6:45 am to 5:15 pm. The allocated hours of operating room (OR) time into which cases are scheduled are from 7:15 am to 4:30 pm.
Several surgeons of the same specialty perform similar procedures at the hospital. There are no indications of differences in outcomes among the surgeons. The surgeons and anesthesiologists are all in the same multiple specialty practice.
Surgeon X operates each Monday and Wednesday at the hospital. Surgeon X has filled his/her OR schedule for the next 4 weeks. Based on historical case duration data, the surgeon’s 8 OR days (“lists”) are expected to finish around 5:30 pm, where 8 = (2 days per week × 4 weeks). The surgeon sees patients in the outpatient clinic at the hospital on Fridays for the full day and has an outreach clinic and OR time at another hospital on the other 2 days of the week.
Surgeon Y operates at the hospital on Tuesdays and currently has 1 case scheduled to be finished by 11:00 am next week.
A patient who is seen by surgeon X in clinic on Friday needs a left upper lobectomy. Surgeon X has little personal interest in scheduling the elective case to start at/after 6:00 pm on one of his/her OR days. Generally, the hospital would not do so either because of the overutilized OR time and OR nursing overtime. Surgeon X would therefore not be able to perform the procedure within the next 4 weeks.
Surgeon Y could do the procedure the next Tuesday.
Our findings were that approximately 76% of patients would want Surgeon X and/or his/her team (eg, the group’s surgical scheduler) to discuss with the patient the potential option for (the named) Surgeon Y to perform the procedure sooner rather than having to wait for Surgeon X for 5 weeks.
There is large potential economic benefit to the simultaneous reduction in patient waiting times and/or underutilized OR time.7 Suppose that patients choose to have surgery as soon as there is OR time. Consider 2 surgeons, both of whom have mean patient waiting times of 2 weeks (ie, maximum waiting times of approximately 4 weeks). Both surgeons schedule elective outpatient cases into 1 eight-hour “block” per week (eg, additional time in their OR workday would be for surgery on patients already admitted to the hospital preoperatively).39,40 The mean case duration equals 3 hours, with realistic standard deviation representing multiple procedures. Then, sharing patients between (simulated) surgeons results in a reduction in underutilized OR time for these patients from 26.2% to 14.3% (ie, difference of 11.9%).7 The simulated 11.9% reduction in underutilized OR time could also be considered a corresponding reduction in overutilized OR time, among surgeons who also typically have patients who are inpatient preoperatively, since such cases would be performed promptly and thus often in overutilized OR time. Regardless, if the mean waiting time were 1 week, consistent with the surveyed patients’ preferences, the reduction in underutilized time from sharing would be even larger, or 26.3%.7 If the mean case duration equaled 2 hours, the reductions in underutilized OR time are still large, 10.1% and 20.1%, respectively.7 These reductions of >10% literally are expected decrease in labor costs of running hospitals’ ORs; as noted previously, they reliably exceed the costs of all anesthesia drugs and supplies combined.7
The benefit of the results would be accrued principally among the anesthesia and OR departments’ productivity and/or patient waiting; the group productivity of the surgeons would remain unchanged. Conceptually, briefer patient waiting time may lead to less patient dissatisfaction (ie, leaving the queue and going to another hospital and surgical group for care). However, we stipulated in the study questions that all patients have surgery at Mayo Clinic. Furthermore, patients surveyed were only those who had surgery at Mayo Clinic. Consequently, our study design can reasonably be considered applicable for reducing patient waiting times and/or increasing anesthesia (OR) productivity.
Although our results are limited in being from Mayo Clinic and only addressing 2 categories of procedures, the results are similar to 2 previous findings. First, 60.9% of 235 patients in Australia waiting for cholecystectomy, inguinal herniorrhaphy, etc, chose to have their procedure sooner with another surgeon.41 The 60.9% was not different from our observed percentage of 58.5%; P = .33 by Fisher exact test. Second, we previously investigated patient-centered decision making by mail survey of Mayo Clinic patients undergoing the same procedures, but regarding postponing surgery for anesthesia drug shortage.18 Even for “very slight” differences between drugs, described as being analogous to the difference between acetaminophen and aspirin for treating a headache, 73.2% wanted to be told about the anesthesia drug shortage (P = .0001 testing for more than ½).18 In our opinion, if most patients want to discuss a change in anesthesia plan as small as that equivalent to choosing medication for the treatment of a mild headache, then it should be expected that patients would want to know of their option of having surgery sooner with another surgeon. That seems particularly reasonable considering that 60% of the patients met the surgeon who performed their procedure just 0 or 1 time(s) preoperatively (Table 1); similar to the median of 2 times among all procedures at the University of Iowa.21
Although our results were insensitive to patient age, we included many patients of age <65 years (Table 1). Since patients (and parents) who are retired want to have surgery sooner,7 our results probably underestimate the percentages of patients in other practices who would choose to switch surgeons to have their procedure sooner.
The average patient wants to discuss with the surgical team (eg, the scheduler or surgeon) the option of having another surgeon perform their procedure even if the wait with their currently assigned surgeon would be 4 days or less. However, because of the potentials for response bias, our response categories, and sample size, that maximum wait could be as long as 2 weeks.
Name: Ilana I. Logvinov, RN, MSN, CCRP.
Contribution: This author helped perform the study.
Name: Franklin Dexter, MD, PhD.
Contribution: This author helped design the study, analyze the data, and write the manuscript.
Name: Elisabeth U. Dexter, MD, FACS, FCCP.
Contribution: This author helped design the study.
Name: Sorin J. Brull, MD, FCARCSI (Hon).
Contribution: This author helped perform the study.
This manuscript was handled by: Nancy Borkowski, DBA, CPA, FACHE, FHFMA.
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. Accessed January 16, 2017.
17. Healthcare Cost and Utilization Project. Available at: https://hcupnet.ahrq.gov
. Accessed January 16, 2017.
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19. Clinical Classifications Software for Services and Procedures Available at: http://FDshort.com/CCS_CPT
. Accessed January 16, 2017; CCS 36 includes 2013 CPT includes 32440–32501, 32505, 32506, 32657, 32657, 32663, and 32666–32672; CCS 84 includes 47400–47460, 47550, 47562–47564, and 47600–47630.
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28. Dexter F, Traub RD. How to schedule elective surgical cases into specific operating rooms to maximize the efficiency of use of operating room time. Anesth Analg. 2002;94:933–942.
29. Dexter F, Macario A, O’Neill L. Scheduling surgical cases into overflow block time- computer simulation of the effects of scheduling strategies on operating room labor costs. Anesth Analg. 2000;90:980–988.
30. Van Houdenhoven M, van Oostrum JM, Hans EW, Wullink G, Kazemier G. Improving operating room efficiency by applying bin-packing and portfolio techniques to surgical case scheduling. Anesth Analg. 2007;105:707–714.
31. Shi P, Dexter F, Epstein RH. Comparing policies for case scheduling within 1 day of surgery by Markov chain models. Anesth Analg. 2016;122:526–538.
32. Dexter F, Epstein RH, Campos J, Dutton RP. US National Anesthesia Workload on Saturday and Sunday Mornings. Anesth Analg. 2016;123:1297–1301.
33. Sessler DI, Kurz A, Saager L, Dalton JE. Operation timing and 30-day mortality after elective general surgery. Anesth Analg. 2011;113:1423–1428.
34. Singla AA, Guy GS, Field JB, Ma N, Babidge WJ, Maddern GJ. No weak days? Impact of day in the week on surgical mortality. ANZ J Surg. 2016;86:15–20.
35. Aylin P, Alexandrescu R, Jen MH, Mayer EK, Bottle A. Day of week of procedure and 30 day mortality for elective surgery: retrospective analysis of hospital episode statistics. BMJ. 2013;346:f2424.
36. Whitlock EL, Feiner JR, Chen LL. Perioperative mortality, 2010 to 2014: a retrospective cohort study using the National Anesthesia Clinical Outcomes Registry. Anesthesiology. 2015;123:1312–1321.
37. Glance LG, Osler T, Li Y, et al. Outcomes are worse in US patients undergoing surgery on weekends compared with weekdays. Med Care. 2016;54:608–615.
38. Dexter F, Epstein RH, Dutton RP, et al. Diversity and similarity of anesthesia procedures in the United States during and among regular work hours, evenings, and weekends. Anesth Analg. 2016;123:1567–1573.
39. Dexter F, Maxbauer T, Stout C, Archbold L, Epstein RH. Relative influence on total cancelled operating room time from patients who are inpatients or outpatients preoperatively. Anesth Analg. 2014;118:1072–1080.
40. Epstein RH, Dexter F. Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery. Anesth Analg. 2015;121:206–218.
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