Control Chart Monitoring of the Numbers of Cases Waiting When Anesthesiologists Do Not Bring in Members of Call Team

Larger anesthesia practitioner per operating room ratios are needed to prevent unnecessary non-operative time than to mitigate patient risk: A narrative review

When choosing the anesthesia practitioner to operating room (OR) ratio for a hospital, objectives are applied to mitigate patient risk: 1) ensuring sufficient anesthesiologists to meet requirements for presence during critical intraoperative events (e.g., anesthesia induction) and 2) ensuring sufficient numbers to cover emergencies outside the ORs (e.g., emergent reintubation in the post-anesthesia care unit). At a 24-OR suite with each anesthesiologist supervising residents in 2 ORs, because critical events overlapped among ORs, ≥14 anesthesiologists were needed to be present for all critical events on >90% of days. The suitable anesthesia practitioner to OR ratio would be 1.58, where 1.58 = (24 + 14)/24. Our narrative review of 22 studies from 17 distinct hospitals shows that the practitioner to OR ratio needed to reduce non-operative time is reliably even larger. Activities to reduce non-operative times include performing preoperative evaluations, making prompt evidence-based decisions at the OR control desk, giving breaks during cases (e.g., lunch or lactation sessions), and using induction and block rooms in parallel to OR cases. The reviewed articles counted the frequency of these activities, finding them much more common than urgent patient-care events. Our review shows, also, that 1 anesthesiologist per OR, working without assistants, is often more expensive, from a societal perspective, than having a few more anesthesia practitioners (i.e., ratio > 1.00). These results are generalizable among hundreds of hospitals, based on managerial epidemiology studies. The implication of our narrative review is that existing studies have already shown, functionally, that artificial intelligence and monitoring technologies based on increasing the safety of intraoperative care have little to no potential to influence anesthesia or OR productivity. There are, in contrast, opportunities to use sensor data and decision-support to facilitate communication among anesthesiologists outside of ORs to choose optimal task sequences that reduce non-operative times, thereby increasing production and OR efficiency.

Bibliometric Analysis of Contributions of Anesthesiology Journals and Anesthesiologists to Operating Room Management Science

BACKGROUND

Anesthesiology journals appear to have been progressively publishing a smaller percentage of operating room (OR) management studies. Similarly, non-anesthesiologists have increasingly been authors of these publications. Five hypotheses were formulated to evaluate these impressions based on 2 of the authors' curation of an online, comprehensive bibliography of OR management articles and corresponding referenced course materials.

METHODS

We studied all 2938 publications having Scopus' SciVal topic T.6319 (OR management) more than 28 years from 1996 through May 2023, including 8608 distinct authors.

RESULTS

Half (50%) of the publications were absent from PubMed, and the percentage absent has been increasing progressively (Kendall's τ = 0.71; P < .0001). Fewer than half were published in journals including anesthesiology as the sole classification (20%) or as one of the classifications (27%). The anesthesiology journals have been publishing a progressively decreasing fraction (τ = -0.61; P < .0001). Among the 11 authors each contributing at least 1% of the OR management science publications, 9 were anesthesiologists and the other 2 had anesthesiologists as coauthors on all these publications. Only 3% of authors had at least 10 OR management publications from earlier years. There were 75% of authors with no such earlier publications and 85% with 0 or 1. There was a progressive increase in the number of authors publishing OR management annually and with at most 1 such earlier publication (τ = 0.90; P < .0001). Only 20% of publications had any author with at least 10 earlier OR management publications, 48% had every author with no such earlier publications, and 60% had all authors with 0 or 1.

CONCLUSIONS

Although most of the authors with the greatest production of OR management science were anesthesiologists, the percentage of publications in anesthesiology journals has been decreasing progressively. Anesthesiologists cannot rely solely on anesthesiology journals to keep up with the field. For most publications, every author had few or no earlier publications on the topic. Clinicians and managers relying on OR management science will continue to need to apply more information when judging whether published results can reliably be applied to their facilities.

The problem with dichotomizing quality improvement measures

The Anesthesia Quality Institute (AQI) promotes improvements in clinical care outcomes by managing data entered in the National Anesthesia Clinical Outcomes Registry (NACOR). Each case included in NACOR is classified as “performance met” or “performance not met” and expressed as a percentage for a length of time. The clarity associated with this binary classification is associated with limitations on data analysis and presentations that may not be optimal guides to evaluate the quality of care. High compliance benchmarks present another obstacle for evaluating quality. Traditional approaches for interpreting statistical process control (SPC) charts depend on data points above and below a center line, which may not provide adequate characterizations of a QI process with a low failure rate, or few possible data points below the center line. This article demonstrates the limitations associated with the use of binary datasets to evaluate the quality of care at an individual organization with QI measures, describes a method for characterizing binary data with continuous variables and presents a solution to analyze rare QI events using g charts.

Managing capacity for urgent surgery: staffing, staff scheduling in-house or on-call from home, and work assignments

Parmar and colleagues developed and validated a graphical method for choosing the number of operating theatres to set aside for urgent surgical cases. We address appropriate usage of their new method for calculating anaesthesia staffing, including comparison with previously published techniques. Parmar and colleagues' method is based on all staff scheduled in-house, rather than some on-call from home. We review that this is not nearly as large a limitation as it may seem because of behavioural factors of staff assignment.

The anesthetizing sites supervised to anesthesiologist ratio is an invalid surrogate for group productivity in academic anesthesia departments when used without consideration of the corresponding managerial decisions

When the anesthesiologist does not individually perform the anesthesia care, then to make valid comparisons among US anesthesia departments, one must consider the staffing ratio (i.e., how many cases each anesthesiologist supervises when working with Certified Registered Nurse Anesthetists [CRNAs] or Certified Anesthesiologist Assistants [CAA]). The staffing ratio also must be considered when accurately measuring group productivity. In this narrative review, we consider anesthesia departments with non-physician anesthesia providers and anesthesiology residents. We investigate the validity of such departments assessing the overall ratio of anesthetizing sites supervised per anesthesiologist as a surrogate for group clinical productivity. The sites/anesthesiologist ratio can be estimated accurately using the arithmetic mean calculated by anesthesiologist, the harmonic mean calculated by case, or the harmonic mean calculated by CRNA or CAA, but not by the arithmetic mean ratio by case. However, there is lack of validity to benchmarking the percentage time that anesthesiologists are supervising the maximum possible number of CRNAs or CAAs when some of the anesthesiologists also are supervising resident physicians. Assignments can differ in the total number anesthesiologists needed while every anesthesiologist is supervising as many sites as possible. Similarly, there is lack of validity to limiting assessment to the anesthesiologists supervising only CRNAs or CAAs. There also is lack of validity to limiting assessment only to cases performed by supervised CRNAs or CAAs. When cases can be assigned to anesthesiology residents or CRNAs or CAAs, increasing sites/anesthesiologist while limiting consideration to the CRNAs or CAAs creates incentive for the CRNAs or CAAs to be assigned cases, even when lesser productivity is the outcome. Decisions also can increase sites/anesthesiologist without increasing productivity (e.g., when one anesthesiologist relieves another before the end of the regular workday). A suitable alternative approach to fallaciously treating the sites/anesthesiologist ratio as a surrogate for productivity is that, when a teaching hospital supplies financial support, a responsibility of the anesthesia department is to explain annually the principal factors affecting productivity at each facility it manages and to show annually that decisions were made that maximized productivity, subject to the facilities' constraints.

US National Anesthesia Workload on Saturday and Sunday Mornings

BACKGROUND

In order to provide guidance to organizations considering elective weekend surgical case scheduling, we analyzed data from the American Society of Anesthesiologist's Anesthesia Quality Institute. We determined the US anesthesia workload on Saturdays and Sundays.

METHODS

The American Society of Anesthesiologist's Anesthesia Quality Institute data were from all US anesthesia groups that submitted cases to the National Anesthesia Clinical Outcomes Registry for 2013. For each of the N = 2,075,188 cases, we identified the local date and time of the start of anesthesia care and the duration of anesthesia care. Anesthesia workload was measured as the time from the start to the end of continuous anesthesia care. Because elective cases are rarely scheduled on Sundays, we considered the difference in workload between Saturday and Sunday to estimate elective case scheduling. This difference would be an overestimate if some patients' scheduled cases were postponed from Friday to Saturday. Data are reported as mean ± standard error; N = 13 four-week periods.

RESULTS

The difference in the anesthesia minutes between Saturdays versus Sundays 7:00 AM to 2:59 PM (ie, elective caseload) represented just 0.38% ± 0.02% of the total minutes nationwide; Saturday 1.57% ± 0.03% versus Sunday 1.19% ± 0.02%. The P < .00001 comparing the 0.38% with 1.0% and, also, with 0.5% (upper 99% confidence interval = 0.42%).

CONCLUSIONS

The imputed Saturday elective schedule represents a tiny percentage of overall anesthetic workload nationwide. Saturday elective surgery is currently an uncommon practice in the United States. Based on this prior knowledge, organizations considering changes to their current scheduling strategies should perform a thorough statistical analysis of their local workload prior to implementation and apply evidence-based criteria to guide their decision-making process.

Decision support system for the operating room rescheduling problem

Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

Shaping the operating room and perioperative systems of the future: innovating for improved competitiveness

PURPOSE OF REVIEW

To review the current state of anesthesiology for operative and invasive procedures, with an eye toward possible future states.

RECENT FINDINGS

Anesthesiology is at once a mature specialty and in a crisis--requiring breakthrough to move forward. The cost of care now approaches reimbursement, and outcomes as commonly measured approach perfection. Thus, the cost of further improvements seems ready to topple the field, just as the specialty is realizing that seemingly innocuous anesthetic choices have long-term consequences, and better practice is required.

SUMMARY

Anesthesiologists must create more headroom between costs and revenues in order to sustain the academic vigor and creativity required to create better clinical practice. We outline three areas in which technological and organizational innovation in anesthesiology can improve competitiveness and become a driving force in collaborative efforts to develop the operating rooms and perioperative systems of the future: increasing the profitability of operating rooms; increasing the efficiency of anesthesia; and technological and organizational innovation to foster improved patient flow, communication, coordination, and organizational learning.