[Understanding complex processes better-A case study on increasing patient safety and efficiency in a central operating room]. / Komplexe Prozesse besser verstehen ­ eine alltagsbezogene Fallstudie zur Erhöhung der Patientensicherheit und Effektivität in einem Zentral-OP.

BACKGROUND: Various professional groups are involved in the daily work of the central operating room with the aim of providing the best possible treatment for each individual using modern medical technology (sociotechnical system) in a cost-effective manner. Ensuring perioperative patient safety is of particular importance. At the same time, the efficient use of the central operating room is essential for the economic success of a hospital. Preoperative preparation is a complex process with many substeps that are often difficult to manage. Historically, the focus has been on retrospective learning from errors and incidents. More recent approaches take a systemic view. A central idea is to consider the mostly positive course of treatment and the adjustments to daily work that are currently required by the people involved (Safety-II). By taking greater account of how the many components of the system interact, processes can be better understood and specific measures derived. This strengthens the system's ability to adapt to changes and disturbances, thus ensuring that goals are achieved. The functional resonance analysis method (FRAM) is an internationally recognized method for modelling work as done compared to work as imagined. This paper presents the application of FRAM to preoperative preparation in a major regional hospital. OBJECTIVE: Is FRAM suitable for improving process understanding in preoperative preparation? MATERIAL AND METHODS: An interdisciplinary project team identified relevant functions of preoperative preparation through document analysis and walkthroughs. Based on this, more than 30 guided interviews were conducted with functionaries. The results were presented graphically and specific information, such as safety-related statements or reasons for the variability of functions, were also presented textually. In the next phase, statements were evaluated and compared with the target model and the job descriptions. RESULTS: The FRAM revealed the process as a complex network of relationships. During the modelling process, a varying degree of centrality and variability of certain functions became apparent. From the observations, the project team selected those with high relevance for patient safety and for the efficiency of the overall process in order to prioritize starting points for deriving measures to increase resilience. These starting points relate either to single functions, such as surgical site marking or to multiple functions that are variable in their execution, such as delays due to nonsynchronized duty times. CONCLUSION: The FRAM conducted provides valuable new insights into the functioning of complex sociotechnical systems that go far beyond classical linear methods. The awareness of operational processes gained and the resulting dynamic view of interactions within the system enable specific measures to be derived that promote resilient behavior and reduce critical variability, thus contributing to increased patient safety and efficiency.

Modeling daily veterinary anesthetist patient care hours and probabilities of exceeding critical thresholds.

OBJECTIVE: Use a referral dental clinic model to study how to calculate accurate 95% upper confidence limits for probabilities of workloads (total case duration, including turnover time) exceeding allocated times. ANIMALS: Dogs and cats undergoing dental treatments. METHODS: Managerial data (procedure date and duration) collected over 44 consecutive operative workdays were used to calculate the daily anesthetist workload. Workloads were compared with a normal distribution using the Shapiro-Wilk test, serial correlation was examined by runs test, and comparisons among weekdays were made using the Kruskal-Wallis test. The 95% confidence limits for normally distributed workloads exceeding allocated times were estimated with a generalized pivotal quantity. The impact of a number of procedures was assessed with scatterplots, Pearson linear correlation coefficients, and multivariable linear regression. RESULTS: Mean anesthetist's workload was normally distributed (Shapiro-Wilk P = .25), without serial correlation (P = .45), and without significant differences among weekdays (P = .52). Daily workload, mean 9.39 hours and SD 3.06 hours, had 95% upper confidence limit of 4.47% for the probability that exceeding 16 hours (ie, 8 hours per each of 2 tables). There was a strong positive correlation between daily workload and the end of the workday (r = .85), significantly larger than the correlation between the end of the workday and the number of procedures (r = .64, P < .0001). CLINICAL RELEVANCE: There are multiple managerial applications in veterinary anesthesia wherein the problem is to estimate risks of exceeding thresholds of workload, including the costs of hiring a locum, scheduling unplanned add-on cases, planning for late discharge of surgical patients to owners, and coordinating anesthetist breaks.

A comparison between a maximum care university hospital and an outpatient clinic - potential for optimization in arthroscopic workflows?

BACKGROUND: Due to the growing economic pressure, there is an increasing interest in the optimization of operational processes within surgical operating rooms (ORs). Surgical departments are frequently dealing with limited resources, complex processes with unexpected events as well as constantly changing conditions. In order to use available resources efficiently, existing workflows and processes have to be analyzed and optimized continuously. Structural and procedural changes without prior data-driven analyses may impair the performance of the OR team and the overall efficiency of the department. The aim of this study is to develop an adaptable software toolset for surgical workflow analysis and perioperative process optimization in arthroscopic surgery. METHODS: In this study, the perioperative processes of arthroscopic interventions have been recorded and analyzed subsequently. A total of 53 arthroscopic operations were recorded at a maximum care university hospital (UH) and 66 arthroscopic operations were acquired at a special outpatient clinic (OC). The recording includes regular perioperative processes (i.a. patient positioning, skin incision, application of wound dressing) and disruptive influences on these processes (e.g. telephone calls, missing or defective instruments, etc.). For this purpose, a software tool was developed ('s.w.an Suite Arthroscopic toolset'). Based on the data obtained, the processes of the maximum care provider and the special outpatient clinic have been analyzed in terms of performance measures (e.g. Closure-To-Incision-Time), efficiency (e.g. activity duration, OR resource utilization) as well as intra-process disturbances and then compared to one another. RESULTS: Despite many similar processes, the results revealed considerable differences in performance indices. The OC required significantly less time than UH for surgical preoperative (UH: 30:47 min, OC: 26:01 min) and postoperative phase (UH: 15:04 min, OC: 9:56 min) as well as changeover time (UH: 32:33 min, OC: 6:02 min). In addition, these phases result in the Closure-to-Incision-Time, which lasted longer at the UH (UH: 80:01 min, OC: 41:12 min). CONCLUSION: The perioperative process organization, team collaboration, and the avoidance of disruptive factors had a considerable influence on the progress of the surgeries. Furthermore, differences in terms of staffing and spatial capacities could be identified. Based on the acquired process data (such as the duration for different surgical steps or the number of interfering events) and the comparison of different arthroscopic departments, approaches for perioperative process optimization to decrease the time of work steps and reduce disruptive influences were identified.

The new timing in acute care surgery (new TACS) classification: a WSES Delphi consensus study.

BACKGROUND: Timely access to the operating room for emergency general surgery (EGS) indications remains a challenge across the globe, largely driven by operating room availability and staffing constraints. The "timing in acute care surgery" (TACS) classification was previously published to introduce a new tool to triage the timely and appropriate access of EGS patients to the operating room. However, the clinical and operational effectiveness of the TACS classification has not been investigated in subsequent validation studies. This study aimed to improve the TACS classification and provide further consensus around the appropriate use of the new TACS classification through a standardized Delphi approach with international experts. METHODS: This is a validation study of the new TACS by a selected international panel of experts using the Delphi method. The TACS questionnaire was designed as a web-based survey. The consensus agreement level was established to be ≥ 75%. The collective consensus agreement was defined as the sum of the percentage of the highest Likert scale levels (4-5) out of all participants. Surgical emergency diseases and correlated clinical scenarios were defined for each of the proposed classes. Subsequent rounds were carried out until a definitive level of consensus was reached. Frequencies and percentages were calculated to determine the degree of agreement for each surgical disease. RESULTS: Four polling rounds were carried out. The new TACS classification provides 6 colour-code classes correlated to a precise timing to surgery, defined scenarios and surgical condition. The WHITE colour-code class was introduced to rapidly (within a week) reschedule cancelled or postponed surgical procedures. Haemodynamic stability is the main tool to stratify patients for immediate surgery or not in the presence of sepsis/septic shock. Fifty-one surgical diseases were included in the different colour-code classes of priority. CONCLUSION: The new TACS classification is a comprehensive, simple, clear and reproducible triage system which can be used to assess the severity of the patient and the surgical disease, to reduce the time to access to the operating room, and to manage the emergency surgical patients within a "safe" timeframe. By including well-defined surgical diseases in the different colour-code classes of priority, validated through a Delphi consensus, the new TACS improves communication among surgeons, between surgeons and anaesthesiologists and decreases conflicts and waste and waiting time in accessing the operating room for emergency surgical patients.

Estimación de la eficiencia del uso de pabellones electivos en el sistema de salud público chileno entre 2018 y 2021. / Efficiency estimation on the use of elective surgical theaters in the Chilean public health system from 2018 to 2021.

Objective: The efficient use of wards intended for elective surgeries is essential to resolve cases on the surgical waiting list. This study aims to estimate the efficiency of ward use in the Chilean public health system between 2018 and 2021. Methods: The design was an ecological study. Section A.21 of the database constructed by the monthly statistical summaries that each public health network facility reported to the Ministry of Health between 2018 and 2021 was analyzed. Data from subsections A, E and F were extracted: ward staffing, total elective surgeries by specialty, number and causes of suspension of elective surgeries. Then, the surgical performance during working hours and the percentage of hourly occupancy for a working day was estimated. Additionally, an analysis was made by region with data from 2021. Results: The percentage of elective wards in use ranged from 81.1% to 94.1%, while those enabled for those staffing ranged from 70.5% to 90.4% during 2018 and 2021. The total number of surgeries was highest in 2019 (n = 416 339), but for 2018, 2020, and 2021 it ranged from 259 000 to 297 000. Suspensions varied between 10.8% (2019) and 6.9% (2021), with the leading cause being patient-related. When analyzing the number of cases canceled monthly by facility, we saw that the leading cause was trade union-related. The maximum throughput of a ward intended for elective surgery was reached in 2019 and was 2.5 surgeries; in 2018, 2020 and 2021, the throughput borders on two surgeries per ward enabled for elective surgery. The percentage of ward time occupied during working hours by contract day varies between 80.7% (2018) and 56.8% (2020). Conclusions: All the parameters found and estimated in this study show that there is an inefficient utilization of operating rooms in Chilean public healthcare facilities.

Objetivo: El uso eficiente de pabellones destinados a cirugías electivas es fundamental para resolver patologías en lista de espera quirúrgica. El objetivo general de este estudio es estimar la eficiencia del uso de pabellones en el sistema de salud público de Chile entre los años 2018 y 2021. Métodos: El diseño fue un estudio ecológico. Se analizó la Sección A.21 de la base de datos construida por los resúmenes estadísticos mensuales que cada establecimiento de la red de salud pública reportó al Ministerio de Salud de Chile entre 2018 y 2021. Se extrajeron los datos de la subsección A, E y F: dotación de pabellones, total de cirugías electivas por especialidad, número y causas de suspensión de cirugías electivas. Luego se estimó el rendimiento quirúrgico en horario hábil y el porcentaje de ocupación horaria respecto de una jornada laboral. Adicionalmente, se hizo un análisis por región con datos de 2021. Resultados: El porcentaje de pabellones electivos respecto de los en dotación varió entre 81,1 y 94,1%; mientras que los habilitados respecto de los en dotación varió entre 70,5 y 90,4% durante 2018 y 2021. El número total de cirugías fue más alto en 2019 (n = 416 339), pero en 2018, 2020 y 2021 variaron entre 259 y 297 mil cirugías. Las suspensiones varían entre 10,8 (2019) y 6,9%w(2021), siendo la principal causa de suspensión atribuida al "paciente". Al analizar la cantidad de pacientes suspendidos mensualmente por institución, se observa que la principal causa es "gremial". El rendimiento máximo de un pabellón destinado a cirugía electiva se alcanzó en 2019 y fue de 2,5 cirugías; mientras que en 2018, 2020 y 2021 el rendimiento bordea las dos cirugías por pabellón habilitado para cirugía electiva. El porcentaje de tiempo de pabellón ocupado en horario hábil respecto a una jornada de contrato varía entre 80,7 (2018) y 56,8% (2020). Conclusiones: Todos los parámetros encontrados y estimados en este estudio muestran que el uso de pabellones en el sistema público de Chile es ineficiente.

Estimación de la eficiencia del uso de pabellones electivos en el sistema de salud público chileno entre 2018 y 2021 / Efficiency estimation on the use of elective surgical theaters in the Chilean public health system from 2018 to 2021

Objective The efficient use of wards intended for elective surgeries is essential to resolve cases on the surgical waiting list. This study aims to estimate the efficiency of ward use in the Chilean public health system between 2018 and 2021. Methods The design was an ecological study. Section A.21 of the database constructed by the monthly statistical summaries that each public health network facility reported to the Ministry of Health between 2018 and 2021 was analyzed. Data from subsections A, E and F were extracted: ward staffing, total elective surgeries by specialty, number and causes of suspension of elective surgeries. Then, the surgical performance during working hours and the percentage of hourly occupancy for a working day was estimated. Additionally, an analysis was made by region with data from 2021. Results The percentage of elective wards in use ranged from 81.1% to 94.1%, while those enabled for those staffing ranged from 70.5% to 90.4% during 2018 and 2021. The total number of surgeries was highest in 2019 (n = 416 339), but for 2018, 2020, and 2021 it ranged from 259 000 to 297 000. Suspensions varied between 10.8% (2019) and 6.9% (2021), with the leading cause being patient-related. When analyzing the number of cases canceled monthly by facility, we saw that the leading cause was trade union-related. The maximum throughput of a ward intended for elective surgery was reached in 2019 and was 2.5 surgeries; in 2018, 2020 and 2021, the throughput borders on two surgeries per ward enabled for elective surgery. The percentage of ward time occupied during working hours by contract day varies between 80.7% (2018) and 56.8% (2020). Conclusions All the parameters found and estimated in this study show that there is an inefficient utilization of operating rooms in Chilean public healthcare facilities.

Objetivo El uso eficiente de pabellones destinados a cirugías electivas es fundamental para resolver patologías en lista de espera quirúrgica. El objetivo general de este estudio es estimar la eficiencia del uso de pabellones en el sistema de salud público de Chile entre los años 2018 y 2021. Métodos El diseño fue un estudio ecológico. Se analizó la Sección A.21 de la base de datos construida por los resúmenes estadísticos mensuales que cada establecimiento de la red de salud pública reportó al Ministerio de Salud de Chile entre 2018 y 2021. Se extrajeron los datos de la subsección A, E y F: dotación de pabellones, total de cirugías electivas por especialidad, número y causas de suspensión de cirugías electivas. Luego se estimó el rendimiento quirúrgico en horario hábil y el porcentaje de ocupación horaria respecto de una jornada laboral. Adicionalmente, se hizo un análisis por región con datos de 2021. Resultados El porcentaje de pabellones electivos respecto de los en dotación varió entre 81,1 y 94,1%; mientras que los habilitados respecto de los en dotación varió entre 70,5 y 90,4% durante 2018 y 2021. El número total de cirugías fue más alto en 2019 (n = 416 339), pero en 2018, 2020 y 2021 variaron entre 259 y 297 mil cirugías. Las suspensiones varían entre 10,8 (2019) y 6,9%w(2021), siendo la principal causa de suspensión atribuida al "paciente". Al analizar la cantidad de pacientes suspendidos mensualmente por institución, se observa que la principal causa es "gremial". El rendimiento máximo de un pabellón destinado a cirugía electiva se alcanzó en 2019 y fue de 2,5 cirugías; mientras que en 2018, 2020 y 2021 el rendimiento bordea las dos cirugías por pabellón habilitado para cirugía electiva. El porcentaje de tiempo de pabellón ocupado en horario hábil respecto a una jornada de contrato varía entre 80,7 (2018) y 56,8% (2020). Conclusiones Todos los parámetros encontrados y estimados en este estudio muestran que el uso de pabellones en el sistema público de Chile es ineficiente.

Pattern of Perioperative Surgical Patient Care, Equipment Handling and Operating Room Management During COVID-19 Pandemic at Jimma Medical Center.

Background: The nature of COVID-19 transmission creates significant risks in surgical departments owing to the close contact of medical staff with patients, the limited physical environment of the operating room and recovery room, the possibility of shared surgical equipment and challenges in the delivery of surgical care in all surgical departments. Globally, studies have reported that the effects of the pandemic on surgical departments are profound, potentially long-lasting and extensive. To manage these effects, different local guidelines and recommendations have been developed, with potential differences in their effectiveness and implementation. Therefore, harmonized and effective national/international guidelines for specific surgical departments during perioperative periods are pertinent to curtail the infection, and will inevitably need to be adapted for consistent and sustainable implementation by all medical staff. The pattern of surgical patient care during the COVID-19 pandemic at Jimma Medical Center (JMC), Ethiopia, has not been explored yet. The present study aimed to describe the pattern of perioperative surgical patient care, equipment handling and operating room management during the COVID-19 pandemic at JMC. Methods: A cross-sectional study was conducted to describe the pattern of perioperative surgical patient care, equipment handling and operating room management during the COVID-19 pandemic at JMC, using five-point Likert scales (0, not at all; 1, rarely; 2, sometimes; 3, most of the time; 4, frequently). A total of 90 respondents [35 patients (five patients from each of seven surgical departments) and 55 healthcare providers (six professionals from each of nine units, including the center of sterility room and anesthesia)] who were available during the study period, selected by a convenience sampling technique with multistage clustering, participated in the study. Data were collected using a structured questionnaire via direct observation and face-to-face interviews with patients undergoing surgery, healthcare providers and hospital administrators, against the standard surgical patient care guidelines. The collected data were manually checked for missing values and outliers, cleared, entered into EpiData (v4.3.1) and exported to SPSS (v22) for analysis. The mean score of practice was compared among different disciplines by applying the unpaired t-test. The findings of the study were reported using tables and narration. A p-value of less than 0.05 was declared as statistically significant. Results: Despite the surgical care practice having changed during the COVID-19 pandemic in all service domains, it is not implemented consistently among different surgical departments owing to different barriers (lack of training on the updated guidelines and financial constraints). The majority of surgical staff were implementing the use of preventive measures against COVID-19, while they were practiced less among patients. The guidelines for surgical practice during the preoperative phase were well applied, especially screening patients by different methods and the application of telemedicine to reduce physical contacts. But, against guidelines, elective patients were planned and underwent surgery, especially in the general surgery department. The implementation of recommended guidelines in the center of sterility room in handling surgical equipment was not very different before and during the pandemic. The extent of practice for anesthesia care, operating room management and postoperative care in the recovery room also changed, and the guidelines were sometimes applied. Conclusion and Recommendations: Although perioperative surgical care practice differed before and during the pandemic, the standard guidelines were inconsistently implemented among surgical departments. The implementation of recommended guidelines in the center of sterility room in handling surgical equipment was not very different before and during the pandemic. Thus, the authors developed safe surgical care guidelines throughout the different domains (infection prevention and PPE use; preoperative care, intraoperative care, operating room management, anesthesia care, equipment handling process and postoperative care) for all disciplines and shared them with all staff. We recommend that all surgical staff should access these guidelines and strictly adhere to them for surgical service during the pandemic.

Building a well-balanced culture in the perioperative setting.

Healthcare institutions are currently under enormous financial, political and social pressure. Especially in the perioperative setting, various professional groups with differing agendas, dynamic teams, high-stress levels and diverging stakeholder interests are contributing to tension on a variety of levels. These players ask for guidance that goes beyond defined goals, clear structures or rules for process optimization. The impact of culture, which is influenced by core values, unspoken behaviours and practices, a shared purpose and implicit norms, has been often neglected. However, culture is a key factor in the search for optimal patient outcomes, quality of care, protection and long-time retention of staff, as well as economic success. In this review, we discuss important aspects to consider in building a great perioperative workplace, discuss indispensable adaptations in times of crisis and touch on urgently needed further investigations to optimize the art of developing, protecting, and cultivating a well-balanced culture.

Administrative structures: Options for achieving success in perioperative medicine.

Without the appropriate administrative structure, even well-thought-out strategic plans or detailed process improvement initiatives will fail. Developing a strong foundation for governance and leadership is a critical element of any high-functioning organization, and it applies just as well in the perioperative setting. Yet, perioperative patient care teams and operating room (OR) management structures can be very complex, due to relationships both within the OR and between the OR and other departments. Frequently, reliable management of the perioperative process is lacking. We aim to provide an overview of the structural and elemental components and roles of perioperative management teams, as well as the administrative structure that guides them, since effective perioperative care teams and OR leaders are of paramount importance for any successful hospital.

Operational and strategic decision making in the perioperative setting: Meeting budgetary challenges and quality of care goals.

Efficient operating room (OR) management is a constant balancing act between optimal OR capacity, allocation of ORs to surgeons, assignment of staff, ordering of materials, and reliable scheduling, while according the highest priority to patient safety. We provide an overview of common concepts in OR management, specifically addressing the areas of strategic, tactical, and operational decision making (DM), and parameters to measure OR efficiency. For optimal OR productivity, a surgical suite needs to define its main stakeholders, identify and create strategies to meet their needs, and ensure staff and patient satisfaction. OR planning should be based on real-life data at every stage and should apply newly developed algorithms.

Managing bottlenecks in the perioperative setting: Optimizing patient care and reducing costs.

Bottlenecks limit the maximum output of a system and indicate operational congestion points in process management. Bottlenecks also affect perioperative care and include dimensions such as infrastructure, architectural design and limitations, inefficient equipment and material supply chains, communication-related limitations on the flow of information, and patient- or staff-related factors. Improvement of workflow is, therefore, becoming a priority in most healthcare settings. We provide an overview of bottleneck management in the perioperative setting and introduce dimensions, including aligned strategic decision-making, tactical planning, and operational adjustments.

Benchmarking Surgeons' Gender and Year of Medical School Graduation Associated With Monthly Operative Workdays for Multispecialty Groups.

Background Female surgeons reportedly receive less surgical block time and fewer procedural referrals than male surgeons. In this study, we compared operative days between female and male surgeons throughout Florida. Our objective was to facilitate benchmarking by multispecialty groups, both the endpoint to use for statistically reliable results and expected differences. Methodology The historical cohort study included all 4,060,070 ambulatory procedural encounters and inpatient elective surgical states performed between January 2017 and December 2019 by 8,472 surgeons at 609 facilities. Surgeons' gender, year of medical school graduation, and surgical specialty were obtained from their National Provider Identifiers. Results Female surgeons operated an average of 1.0 fewer days per month than matched male surgeons (99% confidence interval 0.8 to 1.2 fewer days, P < 0.0001). The mean differences were 0.8 to 1.4 fewer days per month among each of the five quintiles of years of graduation from medical school (all P ≤ 0.0050). Results were comparable when repeated using the number of monthly cases the surgeons performed. Conclusions An average difference of ≤1.4 days per month is a conservative estimate for the current status quo of the workload difference in Florida. Suppose that a group's female surgeons average more than two fewer operative days per month than the group's male surgeons of the same specialty. Such a large average difference would call for investigation of what might reflect systematic bias. While such a difference may reflect good flexibility of the organization, it may show a lack of responsiveness (e.g., fewer referrals of procedural patients to female surgeons or bias when apportioning allocated operating room time).

Feasibility of Anesthesiologists Giving Nurse Anesthetists 30-Minute Lunch Breaks and 15-Minute Morning Breaks at a University's Facilities.

Background Managers of an anesthesia department sought an estimation of how often each anesthesiologist can give lunch breaks and morning breaks to nurse anesthetists to plan staff scheduling. When an anesthesiologist supervising the nurse anesthetists can give a break, it would be preferred because fewer extra nurse anesthetists would be scheduled to facilitate breaks. Methodology Our methodological development used retrospective cohort data from the three surgical suites of a single anesthesia department. Surgical times were estimated using three years of data from October 2016 through September 2019, with 95,146 cases. Comparison was made with the next year from October 2019 through September 2020, with 30,987 cases. The 5% lower prediction bounds for surgical time were estimated based on two-parameter, log-normal distributions. The times when two and three sequential rooms had overlapping lower prediction limits were calculated. Sequential rooms were used because that was how anesthesiologists' assignments were made at the studied department, when feasible given constraints. Percentages of cases were reported with 15 minutes available starting sometime between 9:00 and 10:30 and 30 minutes starting sometime between 11:15 and 12:45, times characteristic for the studied department. At the studied university's facilities, the nurse anesthetists were independent practitioners (e.g., an anesthesiologist supervising two nurse anesthetists each with a long case could give a break to one of the two rooms). Results The percentage of days for which an anesthesiologist could give a lunch break (11:15-12:45) was close to the percentage of cases when an anesthesiologist could give the same-length break anytime throughout the workday. In other words, the length of the break was important, not the time of the day of the break. The absolute percentages also depended on how many rooms the anesthesiologist supervised, the duration of cases, and facility. For example, among anesthesiologists at the adult surgical suite supervising three nurse anesthetists, a lunch break could be given by the anesthesiologist on at most one-third of the days without affecting workflow. Conclusions Our results show that the feasibility of an anesthesiologist clinically supervising one, two, or three rooms to give lunch breaks to the nurse anesthetists in the rooms depends principally on how many rooms are supervised, the duration of the break, and the facility's percentage of cases with surgical times longer than that duration. The specific numerical results will differ among departments. Our methodology would be useful to other departments where anesthesiologists are clinically supervising independent practitioners, sometimes during cases long enough for a break, and there is anesthesiologist backup help. Such departments can use our methodology to plan their staff scheduling for additional nurse anesthetists to give the remaining breaks.

More surgery in December among US patients with commercial insurance is offset by unrelated but lesser surgery among patients with Medicare insurance.

STUDY OBJECTIVE: Evaluate whether there is more surgery (in the US State of Florida) at the end of the year, specifically among patients with commercial insurance. DESIGN: Observational cohort study. SETTING: The 712 facilities in Florida that performed inpatient or outpatient elective surgery from January 2010 through December 2019. RESULTS: Among patients with commercial insurance, December had more cases than November (1.108 [1.092-1.125]) or January (1.257 [1.229-1.286]). In contrast, among patients with Medicare insurance (traditional or managed care), December had fewer cases than November (ratio 0.917 [99% confidence interval 0.904-0.930]) or January (0.823 [0.807-0.839]) of the same year. Summing among all cases, December did not have more cases than November (ratio 1.003 [0.992-1.014]) or January (0.998 [0.984-1.013]). Comparing December versus November (January) ratios for cases among patients with commercial insurance to the corresponding ratios for cases among patients with Medicare, years with more commercial insurance cases had more Medicare cases (Spearman rank correlation +0.36 [+0.25], both p < 0.0001). CONCLUSIONS: In the US State of Florida, although some surgeons' procedural workloads may have seasonal variation if they care mostly for patients with one category of insurance, surgical facilities with patients undergoing many procedures will have less variability. Importantly, more commercial insurance cases were not causing Medicare cases to be postponed or vice-versa, providing mechanistic explanation for why forecasts of surgical demand can reasonably be treated as the sum of the independent workloads among many surgeons.

Case duration prediction and estimating time remaining in ongoing cases.

In this issue of the British Journal of Anaesthesia, Jiao and colleagues applied a neural network model for surgical case durations to predict the operating room times remaining for ongoing anaesthetics. We review estimation of case durations before each case starts, showing why their scientific focus is useful. We also describe managerial epidemiology studies of historical data by the scheduled procedure or distinct combinations of scheduled procedures included in each surgical case. Most cases have few or no historical data for the scheduled procedures. Generalizability of observational results such as theirs, and automatic computer assisted clinical and managerial decision-making, are both facilitated by using structured vocabularies when analysing surgical procedures.

Similarities Between Pediatric and General Hospitals Based on Fundamental Attributes of Surgery Including Cases Per Surgeon Per Workday.

Introduction Operating room (OR) management decision-making at both pediatric and adult hospitals is determined, in large part, by the same fundamental attributes of surgery and other considerations related to case duration prediction. These include the non-preemptive nature of surgeries, wide prediction limits for case duration, and constraints to moving or resequencing cases on the day of surgery. Another attribute fundamentally affecting OR management is the median number of cases a surgeon performs on their OR days. Most adult surgeons have short lists of cases (i.e., one or two cases per day). Similarly, at adult hospitals, growth in caseloads is mostly due to the subset of those surgeons who also operate just once or twice per week. It is unknown if these characteristics of surgery apply to pediatric surgeons and pediatric hospitals as well. Methods Our retrospective cohort study included all elective surgical cases performed at the six pediatric hospitals in Florida during 2018 and 2019 (n = 71,340 cases). We calculated the percentages of combinations of surgeon, date, and hospital (lists) comprising one or two cases, or just one case, and determined if the values were statistically >50% (i.e., indicative of "most"). We determined if most of the growth in caseload and intraoperative work relative value units (wRVUs) at the pediatric hospitals between 2018 and 2019 accrued from low-caseload surgeons. Results are reported as mean ± standard error of the mean. Results Averaging among the six pediatric hospitals, the non-holiday weekday lists of most surgeons at each facility had just one or two elective cases, inpatient and/or ambulatory (68.1%; p = 0.016 vs. 50%, n = 27,557 lists). Growth in surgical caseloads from 2018 to 2019 was mostly attributable to surgeons who in 2018 averaged ≤2.0 cases per week (76.3% ± 5.4%, p = 0.0085 vs. 50%). Similarly, growth in wRVUs was mostly attributable to these low-caseload surgeons (73.8% ± 5.4%, p = 0.017 vs. 50%). Conclusions Like adult hospitals, most pediatric surgeons' lists of cases consist of only one or two cases per day, with many lists containing a single case. Similarly, growth at pediatric hospitals accrued from low-caseload surgeons who performed one or two cases per week in the preceding year. These findings indicate that hospitals desiring to increase their surgical caseload should ensure that low-caseload surgeons are provided access to the OR schedule. Additionally, since percent-adjusted utilization and raw utilization cannot be accurately measured for low-caseload surgeons, neither metric should be used to allocate OR time to individual surgeons. Since most adult and pediatric surgeons have low caseloads, this is a fundamental attribute of surgery.

[Frequency distribution and coordination of emergency operations in German hospitals (FACE) : Analysis in 26 hospitals depending on the level of care]. / Häufigkeitsverteilung und koordinative Umsetzung von Notfalloperationen in deutschen Krankenhäusern : Analyse in 26 Krankenhäusern in Abhängigkeit von der Versorgungsstufe.

BACKGROUND: Timely emergency surgery is vital as this often has a direct impact on morbidity and mortality. The joint recommendations of the German Associations of Anesthesiologists (BDA), Surgeons (BDC), and Operating Room Management (VOp.M) for coordinative implementation have been available since 2016: N0 (surgery immediately), N1 (surgery start in the next free operating room), N2 (surgery start ≤ 6 h), N3 (surgery at the end of the elective schedule), N4/Urgent (surgery within 12-24 h). The aim of this study was to describe the situation of care in German hospitals of different sizes for the first time using routine data. METHODS: The data were collected in 26 hospitals with different levels of care over a period of 10 days. The frequency distribution of the individual emergency categories and the duration from the notification of the operation to the start of anesthesia or surgery were examined for the hospital as a whole and for the four operating departments with a typically high ratio of emergencies: general surgery, trauma surgery, gynecology/obstetrics and urology. RESULTS: A total of 1603 emergency surgical interventions were analyzed. The number of N0 cases was very low due to the specific entity of these emergencies, N1 made up approximately 13-15% of emergencies and categories N2-N4/Urgent comprised approximately 25-32% of emergencies each. The average duration between the notification of the operation and the start of anesthesia or surgery was (min): N0 20.7 ± 14.3 and 43.6 ± 31.8, N1 61.5 ± 48.7 and 90.1 ± 56.1, N2 187.9 ± 152.0 and 220.5 ± 153.4, N3 394.5 ± 392.3 and 428.3 ± 397.9 and N4/Urgent 494.8 ± 484.4 and 519.6 ± 486.6, respectively. The distribution of the emergency categories did not differ significantly between community hospitals compared to tertiary care hospitals, including university hospitals (p = 0.731) and also the duration between notification and start of anesthesia and operation was similar. Significant differences depending on the service level were only found for N1 until the start of anesthesia and for N3 until the start of anesthesia and of surgery. General surgery classified as N3 has a significantly shorter implementation time in community hospitals compared to tertiary care hospitals, including university hospitals, both at the start of anesthesia (mean 287.8 min versus 417.1 min; p = 0.045) and at the start of surgery (mean 316.3 min versus 459.0 min; p = 0.032). The implementation of trauma surgery emergencies classified as N1 took place, based on the start of surgery in community hospitals with an average duration of 91.2 min, statistically significantly faster than in hospitals with a maximum care of 133.0 min (p = 0.036). In urology, there were notable variations between smaller and larger hospitals in emergency interventions with the classification N4/Urgent for both periods of time, both up to the start of anesthesia (p = 0.012) and up to the start of surgery (p = 0.007). At an average of 291.8 min (start of anesthesia) or 294.4 min (start of surgery), the implementation time in hospitals with maximum care, including university hospitals, was shorter than in urological clinics of community providers (626.5 min and 645.6 min, respectively). In gynecology/obstetrics, there was no statistically significant difference between the two groups. CONCLUSION: Cases with high urgency were surgically treated within a short time period. Overall, differences in time management of emergencies were only small between hospital types. The gradations in the temporal implementation of the individual emergency categories were due particularly to distinctions in the resources available, such as the number of operating theaters, including the run times.

Average and longest expected treatment times for ultraviolet light disinfection of rooms.

BACKGROUND: Planning Ultraviolet-C (UV-C) disinfection of operating rooms (ORs) is equivalent to scheduling brief OR cases. The study purpose was evaluation of methods for predicting surgical case duration applied to treatment times for ORs and hospital rooms. METHODS: Data used were disinfection times with a 3-tower UV-C disinfection system in N=700 rooms each with ≥100 completed treatments. RESULTS: The coefficient of variation of mean treatment duration among rooms was 19.6% (99% confidence interval [CI] 18.2%-21.0%); pooled mean 18.3 minutes among the 133,927 treatments. The 50th percentile of coefficients of variation among treatments of the same room was 27.3% (CI 26.3%-28.4%), comparable to variabilities in durations of surgical procedures. The ratios of the 90th percentile to mean differed among rooms. Log-normal distributions had poor fits for 33% of rooms. Combining results, we calculated 90% upper prediction limits for treatment times by room using a distribution-free method (e.g., third longest of preceding 29 durations). This approach was suitable because, once UV-C disinfection started, the median difference between the duration estimated by the system and actual time was 1 second. CONCLUSIONS: Times for disinfection should be listed as treatment of a specific room (e.g., "UV-C main OR16"), not generically (e.g., "UV-C"). For estimating disinfection time after single surgical cases, use distribution-free upper prediction limits, because of considerable proportional variabilities in duration.

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.