Analysis of Operating Room Allocations to Optimize Scheduling of Specialty Rotations for Anesthesia Trainees

Operational strategies to manage non-elective orthopaedic surgical flows: a simulation modelling study

OBJECTIVES

To explore the value of simulation modelling in evaluating the effects of strategies to plan and schedule operating room (OR) resources aimed at reducing time to surgery for non-elective orthopaedic inpatients at a Swedish hospital.

METHODS

We applied discrete-event simulation modelling. The model was populated with real world data from a university hospital with a strong focus on reducing waiting time to surgery for patients with hip fracture. The system modelled concerned two patient groups that share the same OR resources: hip-fracture and other non-elective orthopaedic patients in need of surgical treatment. We simulated three scenarios based on the literature and interaction with staff and managers: (1) baseline; (2) reduced turnover time between surgeries by 20 min and (3) one extra OR during the day, Monday to Friday. The outcome variables were waiting time to surgery and the percentage of patients who waited longer than 24 hours for surgery.

RESULTS

The mean waiting time in hours was significantly reduced from 16.2 hours in scenario 1 (baseline) to 13.3 hours in scenario 2 and 13.6 hours in scenario 3 for hip-fracture surgery and from 26.0 hours in baseline to 18.9 hours in scenario 2 and 18.5 hours in scenario 3 for other non-elective patients. The percentage of patients who were treated within 24 hours significantly increased from 86.4% (baseline) to 96.1% (scenario 2) and 95.1% (scenario 3) for hip-fracture patients and from 60.2% (baseline) to 79.8% (scenario 2) and 79.8% (scenario 3) for patients with other non-elective patients.

CONCLUSIONS

Healthcare managers who strive to improve the timelines of non-elective orthopaedic surgeries may benefit from using simulation modelling to analyse different strategies to support their decisions. In this specific case, the simulation results showed that the reduction of surgery turnover times could yield the same results as an extra OR.

Diversity and Similarity of Anesthesia Procedures in the United States During and Among Regular Work Hours, Evenings, and Weekends

BACKGROUND

Anesthesiologists providing care during off hours (ie, weekends or holidays, or cases started during the evening or late afternoon) are more likely to care for patients at greater risk of sustaining major adverse events than when they work during regular hours (eg, Monday through Friday, from 7:00 AM to 2:59 PM). We consider the logical inconsistency of using subspecialty teams during regular hours but not during weekends or evenings.

METHODS

We analyzed data from the Anesthesia Quality Institute's National Anesthesia Clinical Outcomes Registry (NACOR). Among the hospitals in the United States, we estimated the average number of common types of anesthesia procedures (ie, diversity measured as inverse of Herfindahl index), and the average difference in the number of common procedures between 2 off-hours periods (regular hours versus weekends, and regular hours versus evenings). We also used NACOR data to estimate the average similarity in the distributions of procedures between regular hours and weekends and between regular hours and evenings in US facilities. Results are reported as mean ± standard error of the mean among 399 facilities nationwide with weekend cases.

RESULTS

The distributions of common procedures were moderately similar (ie, not large, <.8) between regular hours and evenings (similarity index .59 ± .01) and between regular hours and weekends (similarity index, .55 ± .02). For most facilities, the number of common procedures differed by <5 procedures between regular hours and evenings (74.4% of facilities, P < .0001) and between regular hours and weekends (64.7% of facilities, P < .0001). The average number of common procedures was 13.59 ± .12 for regular hours, 13.12 ± .13 for evenings, and 9.43 ± .13 for weekends. The pairwise differences by facility were .13 ± .07 procedures (P = .090) between regular hours and evenings and 3.37 ± .12 procedures (P < .0001) between regular hours and weekends. In contrast, the differences were -5.18 ± .12 and 7.59 ± .13, respectively, when calculated using nationally pooled data. This was because the numbers of common procedures were 32.23 ± .05, 37.41 ± .11, and 24.64 ± .12 for regular hours, evenings, and weekends, respectively (ie, >2x the number of common procedures calculated by facility).

CONCLUSIONS

The numbers of procedures commonly performed at most facilities are fewer in number than those that are commonly performed nationally. Thus, decisions on anesthesia specialization should be based on quantitative analysis of local data rather than national recommendations using pooled data. By facility, the number of different procedures that take place during regular hours and off hours (diversity) is essentially the same, but there is only moderate similarity in the procedures performed. Thus, at many facilities, anesthesiologists who work principally within a single specialty during regular work hours will likely not have substantial contemporary experience with many procedures performed during off hours.

A MIP Model for Rolling Horizon Surgery Scheduling

Most surgery scheduling is done 1 day in advance. Caused by lack of overall planning, this scheduling scheme often results in unbalanced occupancy time of the operating rooms. So we put forward a rolling horizon mixed integer programming model for the scheduling. Rolling horizon scheduling refers to a scheduling scheme in which cyclic surgical requests are taken into account. Surgical requests are updated daily. The completed surgeries are eliminated, and new surgeries are added to the scheduling list. Considering day-to-day demand for surgery, we develop a non-rolling scheduling model (NRSM) and a rolling horizon scheduling model (RSM). By comparing the two, we find that the quality of surgery scheduling is significantly influenced by the variation in demand from day to day. A rolling horizon scheduling will enable a more flexible planning of the pool of surgeries that have not been scheduled into this main blocks, and hence minimize the idle time of operating rooms. The strategy of the RSM helps balance the occupancy time among operating rooms. Using surgical data from five departments of the West China Hospital (WCH), we generate surgical demands randomly to compare the NRSM and the RSM. The results show the operating rooms' average utilization rate using RSM is significantly higher than when applying NRSM.

Influencing Anesthesia Provider Behavior Using Anesthesia Information Management System Data for Near Real-Time Alerts and Post Hoc Reports

In this review article, we address issues related to using data from anesthesia information management systems (AIMS) to deliver near real-time alerts via AIMS workstation popups and/or alphanumeric pagers and post hoc reports via e-mail. We focus on reports and alerts for influencing the behavior of anesthesia providers (i.e., anesthesiologists, anesthesia residents, and nurse anesthetists). Multiple studies have shown that anesthesia clinical decision support (CDS) improves adherence to protocols and increases financial performance through facilitation of billing, regulatory, and compliance documentation; however, improved clinical outcomes have not been demonstrated. We inform developers and users of feedback systems about the multitude of concerns to consider during development and implementation of CDS to increase its effectiveness and to mitigate its potentially disruptive aspects. We discuss the timing and modalities used to deliver messages, implications of outlier-only versus individualized feedback, the need to consider possible unintended consequences of such feedback, regulations, sustainability, and portability among systems. We discuss statistical issues related to the appropriate evaluation of CDS efficacy. We provide a systematic review of the published literature (indexed in PubMed) of anesthesia CDS and offer 2 case studies of CDS interventions using AIMS data from our own institution illustrating the salient points. Because of the considerable expense and complexity of maintaining near real-time CDS systems, as compared with providing individual reports via e-mail after the fact, we suggest that if the same goal can be accomplished via delayed reporting versus immediate feedback, the former approach is preferable. Nevertheless, some processes require near real-time alerts to produce the desired improvement. Post hoc e-mail reporting from enterprise-wide electronic health record systems is straightforward and can be accomplished using system-independent pathways (e.g., via built-in e-mail support provided by the relational database management system). However, for some of these enterprise-wide systems, near real-time data access, necessary for CDS that generates concurrent alerts, has been challenging to implement.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints

OBJECTIVES

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems.

METHOD

A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China.

RESULTS

The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in individual maximum overtime (OT); and (4) an 42% reduction in the total OT of nurses. Comparison results with the real 10-workday hospital scheduling further show the advantage of the ACO in several measurements. Instead of assigning all surgeries by a surgeon to only one OR and the same nurses by traditional manual approach in hospital, ACO realizes a more balanced surgery arrangement by assigning the surgeries to different ORs and nurses. It eventually leads to shortening the end time within the confidential interval of [7.4%, 24.6%] with 95% confidence level.

CONCLUSION

The ACO approach proposed in this paper efficiently solves the surgery scheduling problem with daily nurse roster while providing a shortened end time and relatively balanced resource allocations. It also supports the advantage of integrating the surgery scheduling with the nurse scheduling and the efficiency of systematic optimization considering a complete three-stage surgery flow and resources involved.

Continuity of Care in the Training Environment: Anesthesiology Residency in the Ambulatory Surgery Setting

BACKGROUND

Anesthesiology residents acquire clinical skills and acumen primarily from experience providing anesthesia for procedural cases, with prior preparation maximizing learning. Ambulatory surgery and associated management styles create fluid anesthesiology staffing-reducing predictability for learners and disrupting continuity of care.

OBJECTIVE

This prospective, observational study aimed to quantify anesthesia personnel changes in the operating rooms of a single teaching hospital.

METHODS

For a 5-week period, Monday through Friday, we recorded the surgical schedule on the prior evening. After the day of surgery, tracking software provided a list of cases performed. We completed electronic health record review for each case, recorded the actual anesthesiology personnel involved, and compared that to the personnel originally scheduled. We also recorded the occurrence of any permanent transitions of care within a case, the type of operation, and the anesthesia start and end times.

RESULTS

Anesthesia providers included 47 residents and 32 attending physicians. The study period included 1285 scheduled cases, 55% (n  =  711) of which were started and finished by the originally scheduled resident and attending physician. Including canceled cases (126 of 1285, 10%) and added cases (207 of 1366, 15%), residents started anesthetics on patients and with attending physicians assigned to them from the day before 54% of the time. Transitions of care occurred in 19% (260 of 1366) of the cases.

CONCLUSIONS

Anesthesiology residents prepare for many procedures that do not eventuate and frequently start other cases without prior opportunity for preparation and study. Transitions of care further reduce continuity of care and fragment supervision.