Coordination of Appointments for Anesthesia Care Outside of Operating Rooms Using an Enterprise-Wide Scheduling System

Association of surgeons' gender with elective surgical lists in the State of Florida is explained by differences in mean operative caseloads

BACKGROUND

A recent publication reported that at three hospitals within one academic health system, female surgeons received less surgical block time than male surgeons, suggesting potential gender-based bias in operating room scheduling. We examined this observation's generalizability.

METHODS

Our cross-sectional retrospective cohort study of State of Florida administrative data included all 4,176,551 ambulatory procedural encounters and inpatient elective surgical cases performed January 2017 through December 2019 by 8875 surgeons (1830 female) at all 609 non-federal hospitals and ambulatory surgery centers. There were 1,509,190 lists of cases (i.e., combinations of the same surgeon, facility, and date). Logistic regression adjusted for covariables of decile of surgeon's quarterly cases, surgeon's specialty, quarter, and facility.

RESULTS

Selecting randomly a male and a female surgeons' quarter, for 66% of selections, the male surgeon performed more cases (P < .0001). Without adjustment for quarterly caseloads, lists comprised one case for 44.2% of male and 54.6% of female surgeons (difference 10.4%, P < .0001). A similar result held for lists with one or two cases (difference 9.1%, P < .0001). However, incorporating quarterly operative caseloads, the direction of the observed difference between male and female surgeons was reversed both for case lists with one (-2.1%, P = .03) or one or two cases (-1.8%, P = .05).

CONCLUSIONS

Our results confirm the aforementioned single university health system results but show that the differences between male and female surgeons in their lists were not due to systematic bias in operating room scheduling (e.g., completing three brief elective cases in a week on three different workdays) but in their total case numbers. The finding that surgeons performing lists comprising a single case were more often female than male provides a previously unrecognized reason why operating room managers should help facilitate the workload of surgeons performing only one case on operative (anesthesia) workdays.

Briefest Time to Perform a Series of Preoperative Nerve Blocks in Multiple Patients: A Simulation Study

Introduction

To mitigate first-case delays in operating rooms, sufficient additional time must be allotted when anesthesiologists perform preoperative nerve blocks in multiple patients who are scheduled as the initial cases of the day. We used spinal anesthetics performed in dedicated block rooms located just outside the operating room suite to estimate the briefest times needed to complete a series of spinal, epidural, peripheral, or other regional nerve blocks. We followed this approach because even though the studied hospital had a busy regional anesthesia service, sample sizes were insufficient and electronic data were not available to directly study the time to perform the many other nerve blocks they perform.

Methods

We studied a historical cohort of 8,462 adult patients undergoing spinal anesthesia between 2005 and 2017. Preoperative evaluation, consent, and holding area tasks were completed before entering the block room; the times to complete these tasks were not available for study. Upon block room entry, the electronic anesthetic record was started, a timeout conducted with patient participation, vital signs taken, and the spinal performed. The interval from entry until intrathecal injection was the spinal block time. Because fits of these times to probability distributions previously used for anesthesia times were poor (p < 0.001), percentiles of times to perform one or more spinal anesthetics were calculated using Monte-Carlo simulation (100,000 samples with replacement) from the empirical distributions.

Results

The mean spinal block time was 8.8 minutes. The 90% upper prediction limit for one block was 14 minutes, with progressively decreasing times for each subsequent block for a 90% chance of finishing on time. For example, for three first-case regional or neuraxial blocks performed outside the operating room by one anesthesiologist, the first patient needs to arrive at least 38 minutes earlier than non-block patients to mitigate operating room start delays.

Conclusions

These minimum time estimates can help nursing leadership ensure that sufficient time will be available after patients are ready for anesthesia to avoid first-case delays when preoperative regional anesthesia is performed outside the operating room. Given that inadequate sample size and documentation issues likely exist universally for the various non-neuraxial preoperative nerve blocks, we recommend that hospitals use our estimates as a minimum starting point rather than try to calculate times using their own data. Then, as a systems-based metric to assess all steps in the process, track the percentages of days for which all blocks were completed in sufficient time to avoid a first-case delay for those patients. Adjustments to the arrival times would then be implemented, if needed, to meet hospital objectives for on-time starts.

Strategies for daily operating room management of ambulatory surgery centers following resolution of the acute phase of the COVID-19 pandemic

We performed a narrative review to explore the economics of daily operating room management decisions for ambulatory surgery centers following resolution of the acute phase of the Coronavirus Disease 2019 (COVID-19) pandemic. It is anticipated that there will be a substantive fraction of patients who will be contagious, but asymptomatic at the time of surgery. Use multimodal perioperative infection control practices (e.g., including patient decontamination) and monitor performance (e.g., S. aureus transmission from patient to the environment). The consequence of COVID-19 is that such processes are more important than ever to follow because infection affects not only patients but the surgery center staff and surgeons. Dedicate most operating rooms to procedures that are not airway aerosol producing and can be performed without general anesthesia. Increase throughput by performing nerve blocks before patients enter the operating rooms. Bypass the phase I post-anesthesia care unit whenever possible by appropriate choices of anesthetic approach and drugs. Plan long-duration workdays (e.g., 12-h). For cases where the surgical procedure does not cause aerosol production, but general anesthesia will be used, have initial (phase I) post-anesthesia recovery in the operating room where the surgery was done. Use anesthetic practices that achieve fast initial recovery of the brief ambulatory cases. When the surgical procedure causes aerosol production (e.g., bronchoscopy), conduct phase I recovery in the operating room and use multimodal environmental decontamination after each case. Use statistical methods to plan for the resulting long turnover times. Whenever possible, have the anesthesia and nursing teams stagger cases in more than one room so that they are doing one surgical case while the other room is being cleaned. In conclusion, this review shows that while COVID-19 is prevalent, it will markedly affect daily ambulatory workflow for patients undergoing general anesthesia, with potentially substantial economic impact for some surgical specialties.

Obtaining and Modeling Variability in Travel Times From Off-Site Satellite Clinics to Hospitals and Surgery Centers for Surgeons and Proceduralists Seeing Office Patients in the Morning and Performing a To-Follow List of Cases in the Afternoon

BACKGROUND

Hospitals achieve growth in surgical caseload primarily from the additive contribution of many surgeons with low caseloads. Such surgeons often see clinic patients in the morning then travel to a facility to do 1 or 2 scheduled afternoon cases. Uncertainty in travel time is a factor that might need to be considered when scheduling the cases of to-follow surgeons. However, this has not been studied. We evaluated variability in travel times within a city with high traffic density.

METHODS

We used the Google Distance Matrix application programming interface to prospectively determine driving times incorporating current traffic conditions at 5-minute intervals between 9:00 AM and 4:55 PM during the first 4 months of 2018 between 4 pairs of clinics and hospitals in the University of Miami health system. Travel time distributions were modeled using lognormal and Burr distributions and compared using the absolute and signed differences for the median and the 0.9 quantile. Differences were evaluated using 2-sided, 1-group t tests and Wilcoxon signed-rank tests. We considered 5-minute signed differences between the distributions as managerially relevant.

RESULTS

For the 80 studied combinations of origin-to-destination pairs (N = 4), day of week (N = 5), and the hour of departure between 10:00 AM and 1:55 PM (N = 4), the maximum difference between the median and 0.9 quantile travel time was 8.1 minutes. This contrasts with the previously published corresponding difference between the median and the 0.9 quantile of 74 minutes for case duration. Travel times were well fit by Burr and lognormal distributions (all 160 differences of medians and of 0.9 quantiles <5 minutes; P < .001). For each of the 4 origin-destination pairs, travel times at 12:00 PM were a reasonable approximation to travel times between the hours of 10:00 AM and 1:55 PM during all weekdays.

CONCLUSIONS

During mid-day, when surgeons likely would travel between a clinic and an operating room facility, travel time variability is small compared to case duration prediction variability. Thus, afternoon operating room scheduling should not be restricted because of concern related to unpredictable travel times by surgeons. Providing operating room managers and surgeons with estimated travel times sufficient to allow for a timely arrival on 90% of days may facilitate the scheduling of additional afternoon cases especially at ambulatory facilities with substantial underutilized time.

Appropriate operating room time allocations and half-day block time for low caseload proceduralists, including anesthesiologist pain medicine physicians in the State of Florida

STUDY OBJECTIVE

We analyzed University of Iowa operating room data to estimate whether it would be economically rational to allocate, every two weeks, an operating room to anesthesiology pain medicine physicians or a half-day session to individual proceduralists. We investigated the generalizability of the results by studying anesthesiologist pain medicine physicians working at all hospitals and ambulatory surgery centers in the State of Florida.

DESIGN

Observational, cohort study of spinal neuromodulation procedures.

MEASUREMENTS

Hours of daily operating room time and cases by anesthesiologist pain medicine physicians at the University of Iowa, and in Florida in 2018. For each two-week period, we calculated the difference in hours between (1) the under-utilized time from allocating 8 h and (2) time-and-a-half times the over-utilized time from no allocated time.

MAIN RESULTS

The mean greater cost from allocating 8 h vs 0 h equaled 3.89 h, significantly >0 (P = 0.0001, N = 77 periods). Sample mean activities were 0.79 cases and 1.64 h, <2.00 cases and 4.00 h, respectively (both P < 0.0001). Thus, no allocated time or block time should be planned. At least 76.6% (95% lower confidence limit) of Florida surgical facilities performing ≥1 neuromodulation procedures averaged <1.08 cases per two weeks. At least 89.6% of the facilities averaged <2 cases per two weeks. At least 88.8% of combinations of anesthesiologist and facility in Florida averaged fewer cases per two weeks than anesthesiologist proceduralists at the University of Iowa. At least 96.5% of the proceduralists averaged <2 cases per two weeks at each facility where they operated.

CONCLUSIONS

Among anesthesiologist proceduralists in Florida using operating room time for neurostimulator procedures, most perform too few cases weekly for the economically appropriate planning of block time. Few Florida facilities would have enough cases, even potentially, to warrant allocating operating room time.

The challenges of implementing electronic health records for anesthesia use outside the operating room

PURPOSE OF REVIEW

The nonoperating room environment presents a number of distinct challenges for anesthesiologists in the implementation of electronic health records (EHRs). These include documentation compliance, billing, and room design.

RECENT FINDINGS

EHRs offer multiple opportunities for improved continuity of care, expedited preoperative evaluation, and seamless transitions between anesthesia and nonanesthesia providers. Additionally, data gathered through adoption of EHRs provide the promise of future analysis and research, allowing for data-driven improvements in quality of care and value optimization. Institutions adopting a new EHR in areas where anesthesia is provided outside of the operating room should plan wisely to address these matters.

SUMMARY

The needs of anesthesiology practice should be carefully incorporated into future EHR builds as demands for anesthesia care outside of the operating room expand.

A Narrative Review of Meaningful Use and Anesthesia Information Management Systems

The US federal government has enacted legislation for a federal incentive program for health care providers and hospitals to implement electronic health records. The primary goal of the Meaningful Use (MU) program is to drive adoption of electronic health records nationwide and set the stage to monitor and guide efforts to improve population health and outcomes. The MU program provides incentives for the adoption and use of electronic health record technology and, in some cases, penalties for hospitals or providers not using the technology. The MU program is administrated by the Department of Health and Human Services and is divided into 3 stages that include specific reporting and compliance metrics. The rationale is that increased use of electronic health records will improve the process of delivering care at the individual level by improving the communication and allow for tracking population health and quality improvement metrics at a national level in the long run. The goal of this narrative review is to describe the MU program as it applies to anesthesiologists in the United States. This narrative review will discuss how anesthesiologists can meet the eligible provider reporting criteria of MU by applying anesthesia information management systems (AIMS) in various contexts in the United States. Subsequently, AIMS will be described in the context of MU criteria. This narrative literature review also will evaluate the evidence supporting the electronic health record technology in the operating room, including AIMS, independent of certification requirements for the electronic health record technology under MU in the United States.

Overutilization and underutilization of operating rooms - insights from behavioral health care operations management

The planning of surgery durations is crucial for efficient usage of operating theaters. Both planning too long and too short durations for surgeries lead to undesirable consequences, e.g. idle time, overtime, or rescheduling of surgeries. We define these consequences as operating room inefficiency. The overall objective of planning surgery durations is to minimize expected operating room inefficiency, since surgery durations are stochastic. While most health care studies assume economically rational behavior of decision makers, experimental studies have shown that decision makers often do not act according to economic incentives. Based on insights from health care operations management, medical decision making, behavioral operations management, as well as empirical observations, we derive hypotheses that surgeons' behavior deviates from economically rational behavior. To investigate this, we undertake an experimental study where experienced surgeons are asked to plan surgeries with uncertain durations. We discover systematic deviations from optimal decision making and offer behavioral explanations for the observed biases. Our research provides new insights to tackle a major problem in hospitals, i.e. low operating room utilization going along with staff overtime.

National incidence of use of monitored anesthesia care

BACKGROUND

Sedation or monitored anesthesia care (MAC), alone or after peripheral regional nerve block, is currently administered by anesthesiologists and/or certified registered nurse anesthetists. Some of this care may be at risk for substitution by other providers or by reductions in reimbursement.

METHODS

Data from the 2006 United States of America National Survey of Ambulatory Surgery were analyzed to determine national rates for the percentage of total ambulatory anesthesia operating room (OR) time that was either (1) sedation and/or MAC, or (2) peripheral regional nerve block with/without sedation or MAC.

RESULTS

MAC cases alone comprised 29%± 2% of OR time with an anesthesiologist and/or certified registered nurse anesthetist. MAC and/or peripheral block comprised 34% ± 2% of OR time. Percentages by cases were larger than by OR time (P < 0.0001). Among cases with anesthesia, 42% ± 3% were MAC and 47% ± 2% were MAC with/without peripheral block. Percentages of American Society of Anesthesiologists' Relative Value Guide units for MAC would be intermediate between the 29% and 42%, and for MAC and/or peripheral block between the 34% and 47%.

CONCLUSIONS

MAC alone or after peripheral nerve block accounts for a relatively high percentage of ambulatory anesthetics nationwide.

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

Background

No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach.

Methods

A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered.

Results

Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments.

Conclusions

Our technical advance is the development and use of automated event-based knowledge elicitation to identify suboptimal OR management decisions that decrease the efficiency of use of OR time. The adapted scenarios can be used in future decision-making.

Out-of-operating room procedures: preprocedure assessment

Performing an anesthetic in a procedure suite instead of in the operating room can be extremely challenging for the anesthetist. Not only are the procedures performed outside of the operating room becoming increasingly more complex but also patient acuity is increasing. In some cases, the out-of-operating room procedure may be selected as a less risky alternative to an operating room procedure in an extremely high-risk patient. Effective preprocedure evaluation and preparation are critical to achieve optimal clinical outcomes and maximal operational efficiency in these areas.

Automatic updating of times remaining in surgical cases using bayesian analysis of historical case duration data and "instant messaging" updates from anesthesia providers

BACKGROUND

Operating room (OR) whiteboards (status displays) communicate times remaining for ongoing cases to perioperative stakeholders (e.g., postanesthesia care unit, anesthesiologists, holding area, and control desks). Usually, scheduled end times are shown for each OR. However, these displays are inaccurate for predicting the time that remains in a case. Once a case scheduled for 2 h has been on-going for 1.5 h, the median time remaining is not 0.5 h but longer, and the amount longer differs among procedures.

METHODS

We derived the conditional Bayesian lower prediction bound of a case's duration, conditional on the minutes of elapsed OR time. Our derivations make use of the posterior predictive distribution of OR times following an exponential of a scaled Student t distribution that depends on the scheduled OR time and several parameters calculated from historical case duration data. The statistical method was implemented using Structured Query Language (SQL) running on the anesthesia information management system (AIMS) database server. In addition, AIMS workstations were sent instant messages displaying a pop-up dialog box asking for anesthesia providers' estimates for remaining times. The dialogs caused negotiated interruptions (i.e., the anesthesia provider could reply immediately, keep the dialog displayed, or defer response). There were no announcements, education, or efforts to promote buy-in.

RESULTS

After a case had been in the OR longer than scheduled, the median remaining OR time for the case changes little over time (e.g., 35 min left at 2:30 pm and also at 3:00 pm while the case was still on-going). However, the remaining time differs substantially among surgeons and scheduled procedure(s) (16 min longer [10th percentile], 35 min [50th], and 86 min [90th]). We therefore implemented an automatic method to estimate the times remaining in cases. The system was operational for >119 of each day's 120 5-min intervals. When instant message dialogs appearing on AIMS workstations were used to elicit estimates of times remaining from anesthesia providers, acknowledgment was on average within 1.2 min (95% confidence interval [CI] 1.1-1.3 min). The 90th percentile of latencies was 6.5 min (CI: 4.4-7.0 min).

CONCLUSIONS

For cases taking nearly as long as or longer than scheduled, each 1 min progression of OR time reduces the median time remaining in a case by <1 min. We implemented automated calculation of times remaining for every case at a 29 OR hospital.

Novel, Web-Based, Information-Exploration Approach for Improving Operating Room Logistics and System Processes

Routine clinical information systems now have the ability to gather large amounts of data that surgical managers can access to create a seamless and proactive approach to streamlining operations and minimizing delays. The challenge lies in aggregating and displaying these data in an easily accessible format that provides useful, timely information on current operations. A Web-based, graphical dashboard is described in this study, which can be used to interpret clinical operational data, allow managers to see trends in data, and help identify inefficiencies that were not apparent with more traditional, paper-based approaches. The dashboard provides a visual decision support tool that assists managers in pinpointing areas for continuous quality improvement. The limitations of paper-based techniques, the development of the automated display system, and key performance indicators in analyzing aggregate delays, time, specialties, and teamwork are reviewed. Strengths, weaknesses, opportunities, and threats associated with implementing such a program in the perioperative environment are summarized.