Anesthesia providers and operating room (OR) nurses make managerial decisions throughout each day of surgery. For example, they decide when to call for the next patient coming to their OR. They decide whether to start a case in one OR or another.
The statistical basis for operational decision-making on the day of surgery is understood (1,2). Economically rational decisions arise from the use of the following ordered priorities (1): i) performing all scheduled cases unless there is a patient safety concern, ii) reducing over-utilized OR time, iii) reducing patient and surgeon waiting times, and iv) satisfying personal priorities, etc. The decision-making is summarized in Table 1, the Methods, and two review articles (1,2). Profitable facilities that are focused on satisfaction of surgeons can have sufficient excess capacity to prevent almost all over-utilized OR time (3). Decisions on the day of surgery are then based on reducing surgeon waiting.
Commercial products to communicate OR management information on the day of surgery include both passive status displays (e.g., big screens or whiteboards) and active status displays (e.g., text pagers). These displays show data about where the patient is (their status) as they advance through the perioperative period. It is unknown how best to use these passive and active displays to present clinicians with information derived from statistical methods (1,2) to achieve optimal decision-making. Previous papers that have reported the use of status displays in ORs for managerial decision-making have been limited to decisions involving individual ORs (Table 2).
OR staff likely use displays to increase the speed of work in each OR (i.e., increase the work per unit time in each OR). Surgeons can perceive that the most important attributes of a high-performing anesthesia group include those related to working quickly in individual ORs: timely starts and brief times for patient awakening, turnover, and patient entrance to positioning (11). Time is a consistent catalyst for tension and interpersonal conflict among physicians and OR nurses (12,13). When time is the subject of communication during cases, 46% of interactions can involve high tension and blame (14). OR staff can perceive that the desire to perform as many surgical cases in a day as possible is so pervasive as to be the most dominant organizational factor underlying unsafe practices at work (15). Staff working in outpatient surgery centers can perceive time pressures to be so strong as to commonly affect quality of care and patient safety (16). Some anesthesia departments publish each anesthesiologist's time of entrance of the first patient of the day into each OR, anesthesia induction time, wakeup time, and turnover time (17). Financial incentives have been provided for anesthesiologists meeting measures of “productivity … on the day of surgery,” defined as timely entrance of the first patient of the day into his or her OR, brief time to positioning, and lack of waiting for the anesthesiologist (18).
Nevertheless, increasing each clinician's clinical work per unit time is not the same as following the ordered priorities, described above, when decisions involve more than one OR. As summarized below, decisions that increase clinical work per unit time can result in decisions that are suboptimal economically for the surgical suite as a whole (1,2). We used an experimental simulation study to assess the degree to which passive status displays (i.e., information upon request) or active command displays (i.e., recommendations) can result in decision-making that matches the ordered-priorities of Table 1.
This section is a summary of definitions and results needed to develop and interpret our study. Terms defined are shown in italic. References, details, justifications, explanations of economic rationality, and dozens of examples are in two recent review articles of OR management operational decision-making based on OR efficiency (1,2). A summary is in Table 1.
Allocated OR time is an interval of OR time, with a specified start and end time on a specified day of the week, assigned by the facility to a service for scheduling cases (e.g., otolaryngology in OR #23 from 7:15 am to 3:30 pm).
A few months before the day of surgery, based on the OR allocations, the process of staff scheduling determines the individuals who will work each shift on each day. The allocated OR time affects not just appropriate staff scheduling in anesthesia departments, but also in OR nursing, postanesthesia care unit, surgical pathology, surgical wards, and so forth.
If the allocated time for an OR was planned from 7:15 am to 3:30 pm, and the last case of the day in the OR exited the OR at 1:30 pm, there were 2 h of under-utilized OR time. If the last case of the day exited at 4:30 pm, there was 1 h of over-utilized OR time. Depending on staff scheduling and compensation, each hour of over-utilized OR time may be an hour of overtime.
On the day of surgery, the cost of an hour of under-utilized OR time is negligible relative to the cost of an hour of over-utilized OR time (2,19). Therefore, decisions can be made to complete the existing cases with as little over-utilized OR time as possible, and without regard for the under-utilized OR time (1).
In the ordered priorities above (Table 1), increasing OR efficiency is a lower priority than completing the cases each day. The reason is that, overall, virtually every surgeon's cases contribute positively to hospital and professional margin when there is prospective payment (e.g., diagnosis related groups) (3). Even without any incremental revenue, canceling cases on the day of surgery increases costs, whether analyzed from the perspective of the hospital, patient, physicians, or society (20). Therefore, completing all scheduled cases each day is economically rational. The consequence is that minimizing over-utilized OR time serves to maximize the ratio of the output (clinical care) to input (staffing costs), which is efficiency. Thus, on the day of surgery, minimizing over-utilized OR time maximizes OR efficiency (1,19,21).
When decision-making involves multiple ORs, decisions to reduce over-utilized OR time can conflict with decisions to increase clinical work per unit time in each OR.
Example 1: A six OR ambulatory surgery center had five ORs allocated (staffed) for short hours (7:15 am to 3:30 pm) and one OR allocated for long hours (7:15 am to 6:00 pm). One day, the last case of the day in the 6:00 pm OR was to be performed by a different surgeon than the preceding cases. Based on progress in that OR, that 1.5 h case was expected to start at 4:00 pm, and thus result in no expected over-utilized OR time. Nonetheless, at 2:30 pm the case was moved to the same anesthesiologist's 3:30 pm OR. Starting the case earlier increased the anesthesiologist's clinical work per unit time. The anesthesiologist may be rewarded intangibly or tangibly for doing more of the work. Nevertheless, the consequence was over-utilized OR time. The OR nurses were scheduled so that there was no staff available to relieve the OR team in the 3:30 pm OR other than the staff in the 6:00 pm OR once they finished their cases. Thus, the over-utilized OR time meant, in practice, not only unpredictable work hours and increased staffing cost, but also mandatory, unexpected, and unnecessary overtime to finish the case, albeit briefly.
When a decision does not affect over-utilized OR time, the next ordered priority is to reduce patient and surgeon waiting time (Table 1) (1). For elective cases, this refers to reducing waiting from the scheduled start time (Table 1) (1) (i.e., tardiness as defined in the following Example).
Example 2: Three cases of the same procedure were performed in an OR. Each case took 2 h. The turnover times were 30 min. Scheduled start times were 8 am, 10:30 am, and 1 pm. The first case entered the OR at 8:20 am. For purposes of a decision made at 9 am, the tardiness of the start of the OR's remaining cases from their scheduled start times could be considered to be 40 min, where 40 min = 20 min late for the second case plus 20 min late for the third case. The minimum value of tardiness was 0 min.
In practice, most decisions should be made based on reducing tardiness (i.e., surgeon and patient waiting). The reason is that when OR allocations are made appropriately or additional capacity is provided to ease case scheduling (2,3), most ORs have no over-utilized OR (1,2). Yet, often an OR without any expected over-utilized OR time has cases with expected tardiness of start (e.g., an OR with four cases totaling 6.0 h starts its first case of the day 15 min late).
Although personal priorities may intuitively seem to often be a higher priority than reducing waiting, they cannot because bizarre behaviors would then be appropriate. For example, consider Example 2 with three cases totaling 6 h. An OR nurse could then reasonably take a 1.5 h lunch break in the middle of this day, as it would not cause over-utilized OR time, just further increase tardiness from scheduled start times.
The displays that we studied not only showed tardiness, but also earliness. Suppose that a 2 h case enters an OR at 11:30 am. The turnover times are 15 min. The scheduled start time of the next and final case is 2:30 pm. The earliness of start of the OR's case is 45 min, where 45 min = 2:30 pm to 1:45 pm. The minimum value of earliness is 0 min.
Nine scenarios were created from actual cases (Table 3). The scenarios involved anesthesiologists, OR charge nurses, and/or turnover personnel. Each scenario described a decision that involved two ORs and had a correct answer based on expected over-utilized OR time, under-utilized OR time, earliness, and/or tardiness (Table 1).
The nine scenarios were created so that one updated paper OR schedule for 1 day [i.e., status display with raw data (24)] was sufficient for all scenarios (Table 4).
Room assignments, scheduled start times, scheduled OR times, historical average OR times, ages, times of patient entrance and exit from ORs, and procedures were realistic and internally consistent. The paper OR schedule matched the ones printed at the participants' hospital other than by not listing the patient name or medical record number. In addition, under the column with the surgeon's name, the specialty was listed with sequential numbers for each surgeon (e.g., Gynecology 1 and Gynecology 2), instead of the surgeon's name.
Which ORs were allocated to 3:30 pm or 6:00 pm were evident from the paper schedule based on the time at which the last case of the day was scheduled to end in the OR. For example, Table 4 shows scenario #1 in which both ASC2 and ASC4 were allocated to 3:30 pm.
Paper-based graphical depictions were created of passive status displays (24) showing hours of over/under-utilized OR time and minutes of tardiness/earliness (Fig. 1). When the last case of the day in an OR was ongoing or had finished, the words “Last case” were displayed instead of the tardiness or earliness. The displays offered data about each of the ORs in a scenario. The displays were depicted by pictures of LED displays positioned over OR doors like those at airline gates (Fig. 1). These passive displays were chosen for the experiment since they provided all data required for the decision, no redundant information (e.g., other ORs), and focused participants on the fact that they were being asked to address the deliberately over-simplified problem of just two ORs. In the “real world,” the spatial distance between such passive displays would reduce their effectiveness. Thus, the study was, by design, biased to show a benefit of status displays.
Participants could try to use the data from the scenarios and the status displays to estimate uncertainties in OR times (25) and incorporate the uncertainty in their decision-making. Therefore, we designed the status displays to provide not just the expected over-utilized OR time and tardiness, but also the expected under-utilized OR time and earliness (1).
Graphical depictions of active command displays were pictures of the hospital's alphanumeric text pagers with recommendations (Fig. 1). The text recommendations pertained either to which OR to focus on (e.g., start first or clean first), to which OR to assign an add-on case, to which OR to assign staff, or whether or not to move a case to a different OR.
Although the use of command displays may serve to mitigate the influence of the heuristic of working fast on decision-making, the displays may also inappropriately lull participants into relying on recommendations in lieu of clinical judgment. Previous studies in other subject areas found participants complied with poor recommendations from command displays (Table 5). In three of the scenarios (#5, #8, and #9), incorrect recommendations were made by the active command display and would be suggested by the passive status display or use of the paper OR schedule.
Following institutional review board approval, eight certified registered nurse anesthetists (CRNAs) from the facility where the research was completed piloted the study in November 2005. Minor modifications were made to scenario presentation, depictions of displays, and to presentation of the paper OR schedule. Starting December 2005, enrollment began. Enrollment continued through the end of January.
The subject pool for the study included anesthesiologists, OR charge nurses, and turnover personnel whose responsibilities included cleaning and assisting in the preparation of ORs and equipment for each case. Examples of decisions by nurses and housekeepers are in Table 3. Participants included 12 anesthesiologists, 15 registered nurses, and 18 housekeepers and anesthesia assistants. Employment at the hospital had been 5 yr or less for 44% and greater than 10 yr for 40%.
The nine scenarios were presented to each of four groups, all with an updated paper OR schedule: with/without command display and with/without passive status display. After each participant agreed to participate in the study, he or she was randomized to one of the four groups based on a card in an opaque envelope. No limit was placed on the time that each participant chose to take to complete the study. All participants responded to every scenario.
Preceding the presentation of the scenarios, each participant was shown a 10-min slide presentation (www.FranklinDexter.net/education.htm, first half of the training materials, accessed Sept. 15, 2006). He or she was also given a one page summary of principles as posted at the OR control desk (Table 1).
Each scenario was printed in color in landscape view on one piece of paper. The command display or status display, when applicable, was printed on that one piece of paper (Fig. 1).
To evaluate whether displays would mitigate what we expected to be clinicians' tendency to make decisions that increased the clinical work per unit time in each OR, we compared the accuracy of responses to the four scenarios involving reducing expected hours of over-utilized OR time (#1, #3, #6, and #7) to random chance by the binomial test. Correct answers could be determined from the paper OR schedule (Table 4) using either the listed mean historical average OR times (1) or the scheduled OR time. Statistical significance of worse than random chance for the status displays would be particularly convincing, because the study was, by design, biased to show benefit to the status displays (see above Displays section).
When anesthesia providers were provided prompts in real-time for quality assurance documentation, they complied with the recommendations, even though doing so reduced their clinical work per unit time (31). Therefore, we expected that command displays would increase the percentage of managerial decisions that match the ordered priorities of Table 1, particularly when increasing clinical work per unit time in each OR results in additional over-utilized OR time. Analysis of variance with interaction was used to study the number of scenarios answered correctly by each participant. This was a 2 × 2 design with one factor being command display Yes/No and the other factor being status display with processed data Yes/No. All four groups received the status display with updated raw data (i.e., the OR schedule) (Table 4). Significant differences were checked by the nonparametric Mann–Whitney test. The χ2 test was used to assess the impact of command displays on the accuracy of responses to the four scenarios involving reducing expected hours of over-utilized OR time.
Although in other subject areas poor recommendations from command displays can result in unsafe decisions (Table 5), we expected such situations to be recognized by participants. We assessed the accuracy of responses to the three scenarios with incomplete information (#5, #8, and #9). In addition, relevant unsolicited verbal comments were transcribed and analyzed qualitatively.
Additional tests evaluated validity of our experimental design. As all tests supported validity, these findings are reported in the legend of Table 6.
Although five scenarios involved reducing expected hours of over-utilized OR time (#1, #3, #5, #6, and #7), one of the scenarios (#5) focused on incomplete information. That scenario (#5) was put in between the first pair of scenarios (#1 and #3) and the second pair of scenarios (#6 and #7) so that the accuracy of responses to the first pair of scenarios (#1 and #3) could be compared with that of the second pair of scenarios (#6 and #7). The impact of the scenario with incomplete information (#5) on the accuracy of responses to the other four scenarios was tested by the test for the homogeneity of the odds that the command displays increased the accuracy of responses.
All scenarios crossed job categories. Four scenarios had a decision made by anesthesiologists, three had decisions made by OR charge nurses, and two had decisions made by turnover personnel. Every participant responded to every scenario by specifying how the decision should be made. In addition, when the job category of the scenario matched that of the participant, the participant was also asked what he or she would do. For example, the text of scenario #1 (Tables 3 and 4) seen by anesthesiologists was as in Figure 1, with the last two sentences: “… which of the two ORs should you start first, ASC2 or ASC4? Which one would you start?” The OR nurses and turnover technicians did not have the last sentence. Concordance between participants' responses and reports of actions was tested by Fisher's exact test.
An additional post hoc test examined whether there was an effect of job category on the impact of command displays on decisions involving over-utilized OR time. Recommendation from a command display may have a larger incremental benefit on getting an answer correct for scenarios that consider decisions for which the job category of the scenario does not match the job category of the participant. The opposite could also be argued. Statistical analysis was performed by testing for the homogeneity of the odds ratio.
Participants without command displays answered the scenarios involving over-utilized OR time less accurately than random chance (P = 0.011, 31 of 84 responses) (Table 6). This result was consistent with the staff using the status displays to increase the clinical work per unit time in each OR (i.e., keeping the ORs busy). Command displays significantly increased the correct response rate (P < 0.001).
Among all scenarios, simulated status displays with processed information (e.g., expected over-utilized OR time) had no effect on the accuracy of decision-making versus displays with raw data (i.e., updated paper schedule) (P = 0.40) (Table 7). Command displays increased the accuracy of decision-making (P = 0.010; Mann–Whitney P < 0.001). The combination did not increase the accuracy further (P = 0.40).
Previous studies in other subject areas found participants comply with poor recommendations from command displays (Table 5). In our scenario for which the command displays provided a poor recommendation and safety was unaffected, participants complied with the incorrect recommendation more often than did the other participants (Table 6). In the two scenarios for which the command displays provided recommendations that adversely affected safety, participants appropriately ignored advice (Table 6). Unsolicited verbal comments showed a resulting lack of trust (23) in the command displays (Table 8), matching results of studies in other subject areas (23).
When decision-making on the day of surgery involves multiple ORs, decisions to increase clinical work per unit time in each OR often conflict with decisions to reduce over-utilized OR time. Command displays (recommendations) increased consideration of over-utilized OR time, but status displays did not.
Reducing over-utilized OR time has advantages for OR nurses, housekeepers, and anesthesia providers: consistent decision-making on the day of surgery, more predictable work hours, fewer handoffs during cases, and reduced staffing costs (1,2). Depending on staff scheduling, reducing over-utilized OR time can also reduce scheduled overtime (e.g., late call list) and unscheduled (mandatory) overtime. The premise of making decisions to reduce the hours that ORs finish late is so simple that in our experience people often find the concept to be so obvious that they are annoyed by being taught it. Even though we removed organizational or time pressure by using simulation, the participants made decisions that increased the clinical work per unit time in each OR.
Nurses and physicians receive clinical training while completing lists of cases in single ORs, not while working at OR control desks or while medically directing multiple ORs. Thus, socialization of OR culture occurs in situations for which making decisions to increase clinical work per unit time is advantageous. Our results suggest that the tendency is then applied inappropriately to managerial decisions involving multiple ORs. This socialization likely is reinforced by the presence of intangible and tangible rewards for working fast (see Introduction). This tendency is explored further in our companion paper (32).
Although many communication episodes at the OR control desk involve decisions that affect multiple ORs (1,33,34), previous studies of status displays have not considered such decisions (Table 2). Status displays (Tables 6 and 7) were insufficient to change decision-making, even though the situations studied were deliberately simple. In contrast, command displays were efficacious (Table 7), particularly for the economically most important decisions (1) (i.e., those to reduce over-utilized OR time) (Table 6). Thus, we recommend that research in computer–human interaction for decision-making on the day of surgery focuses on decision aids that make recommendations. Such displays are not Gantt charts displaying information about multiple ORs, whether as large displays in hallways or on web pages, and whether the information provided is raw [i.e., like an updated OR schedule (24)] or processed [e.g., expected over-utilized OR times (24)].
Command displays have disadvantages when there are errors in recommendations due to the decision aids having incomplete knowledge (Table 5). Such situations should be expected when coordinating ORs, because much of the information is not obtained from information systems, but from direct observation (e.g., a patient being wheeled down the hall) and social networks (e.g., asking a surgeon in passing) (35). One disadvantage is that decision-makers often comply with the erroneous recommendations (Tables 5 and 6). Preliminary findings are that when safety is adversely affected, erroneous recommendations are recognized (Table 8) and ignored (Table 6), unlike in other subject areas (domains). The resulting disadvantage is that there is a reduction in trust in all of the command display's recommendations, good or bad (23). Findings from other domains are that, when some recommendations are erroneous, appropriate recommendations are followed more often when from a human than from a computer (Table 5) (30). Therefore, we expect continuation of the current managerial model whereby most decisions involving multiple ORs are made at an OR control desk and then communicated verbally to other clinicians (33). We also recommend strongly against using a reduction in communication episodes (e.g., phone calls) at OR control desks (34) as an end-point of success of information systems, in lieu of end-points of decisions made. Our results show that the successful distribution of information on the day of surgery cannot be taken as sole evidence of value of communication tools (e.g., displays).
Our finding of a benefit for accurate real-time OR information system data is novel, even though it may seem intuitive. The economic importance of decision-making on the day of surgery is very small (1) compared to having the distribution of services among ORs (blocks) planned (3) right several months before the day of surgery, OR allocations (staffing) planned (1,21,36) right a few months before the day of surgery, and scheduling (1,19) the cases right a few weeks to days before the day of surgery. In contrast to the findings in the current paper, decisions for allocating blocks, planning staffing, and scheduling cases are robust to even large errors in OR data (1,3,19,25,36).
Usefulness Varies Among Facilities
Because OR allocations are driven by the relative cost of an hour of over-utilized OR time to an hour of under-utilized OR time, if a facility sets this ratio to a high value, there can be sufficient excess capacity (i.e., under-utilized OR time) that rarely would one surgeon need to wait for another (2,3,21). On the day of surgery, decision-making by the ordered priorities would then usually simplify to reducing patient and surgeon waiting (Table 1). For example, if at a reader's facility there are <8 h of cases in most ORs every workday, then the results of our study are unlikely to be useful.
The studied recommendations on the day of surgery are likely to be useful only for facilities that also follow the ordered priorities (Table 1) when making OR allocation (2,21,36) and case scheduling (1,2,19) decisions before the day of surgery, as is economically rational (1–3).
Reducing over-utilized OR time can provide direct benefits to OR staff, but less likely to customers of the surgical suite, the surgeons. The argument could be made that anesthesiologists acted to reduce surgeon waiting in lieu of over-utilized OR time to reduce surgeon and patient waiting (i.e., to increase surgeon satisfaction). Alternatively, they could have made decisions to finish the available clinical work as early in the day as possible. Additional observational studies in our companion paper show that neither hypothesis can explain our results (32). Rather, the behavior was consistent with the heuristic of keeping each clinician busy when present.
Our study has the weakness that it was a simulation (i.e., not naturalistic decision-making). This weakness is mitigated in our companion paper (32) in which we show that our results (Tables 6 and 7) are matched by two observational studies.
The studies were performed at one academic hospital. We suspect that confounding effects of organizational culture had a small influence on results based on the results explaining previous findings from other facilities [Table 2, Ref. (31)] and matching findings from other subject areas (Table 5). Nevertheless, we studied decision-making at just one hospital, and that one hospital was an academic hospital.
Finally, we did not detect heterogeneity of decision-making among clinicians with different backgrounds and jobs (Table 6). However, our statistical power was likely weak to detect such differences if present.
Clinicians at a hospital made managerial decisions that were consistent with a tendency to increase the clinical work per unit time in each OR. This work ethic likely is supported by intangible and tangible rewards, and seems to be a reasonable basis for decisions involving individual cases. However, it can be disadvantageous for decisions involving multiple ORs. Command displays with recommendations may be more effective at changing decisions than education and distributed status displays. Future research can focus on how to create better recommendations and how to increase the accuracy of the information used to make the recommendations to prevent a reduction in trust.
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