Determining future capacity for an Ambulatory Surgical Center with discrete event simulation

Educating for success: ambulatory anesthesia training

PURPOSE OF REVIEW

This article explores the unique intersection of the challenges confronting ambulatory anesthesiology education and charts a trajectory forward. The proportion of ambulatory, nonoperating room (NORA), and office-based surgical cases continues to rise; however, the requirements for trainees in these settings have remained static. The rapid evolution of the field combined with a limited workforce also makes continuing education essential, and we discuss the current and future states of ambulatory anesthesia education.

RECENT FINDINGS

Although numerous resources are available across an array of platforms to foster both trainee education and continuing education for practicing anesthesiologists, there is a paucity of current literature evaluating the impact of new curricula developed specifically for ambulatory, NORA, or office-based anesthesiology (OBA).

SUMMARY

We begin with an appraisal of the current state of ambulatory anesthesiology training and evaluate the gap between current graduate medical education and trends in ambulatory surgery. We then develop a vision for an ideal state of future ambulatory education for residents as well as anesthesiologists in practice and highlight the priorities necessary to reach this vision.

The Nature of Adverse Events in Dentistry

OBJECTIVES

Learning from clinical data on the subject of safety with regards to patient care in dentistry is still largely in its infancy. Current evidence does not provide epidemiological estimates on adverse events (AEs) associated with dental care. The goal of the dental practice study was to quantify and describe the nature and severity of harm experienced in association with dental care, and to assess for disparities in the prevalence of AEs.

METHODS

Through a multistaged sampling procedure, we conducted in-depth retrospective review of patients' dental and medical records.

RESULTS

We discovered an AE proportion of 1.4% (95% CI, 1.1% to 1.8). At least two-thirds of the detected AEs were preventable. Eight percent of patients who experienced harm due to a dental treatment presented only to their physician and not to the dentist where they originally received care.

CONCLUSIONS

Although most studies of AEs have focused on hospital settings, our results show that they also occur in ambulatory care settings. Extrapolating our data, annually, at least 3.3 million Americans experience harm in relation to outpatient dental care, of which over 2 million may be associated with an error.

PRACTICAL IMPLICATIONS

Measurement is foundational in enabling learning and improvement. A critical first step in preventing errors and iatrogenic harm in dentistry is to understand how often these safety incidents occur, what type of incidents occur, and what the consequences are in terms of patient suffering, and cost to the healthcare system.

A discrete-event simulation model for assessing operating room efficiency of thoracic, gastrointestinal, and orthopedic surgeries

BACKGROUND

In hospital management, pinpointing steps that most enhance operating room (OR) throughput is challenging. While prior literature has utilized discrete event simulation (DES) to study specific strategies such as scheduling and resource allocation, our study examines an earlier planning phase, assessing all workflow stages to determine the most impactful steps for subsequent strategy development.

METHODS

DES models real-world systems by simulating sequential events. We constructed a DES model for thoracic, gastrointestinal, and orthopedic surgeries summarized from a tertiary Chinese hospital. The model covers preoperative preparations, OR occupation, and OR preparation. Parameters were sourced from patient data and staff experience. Model outcome is OR throughput. Post-validation, scenario analyses were conducted for each department, including: (1) improving preoperative patient preparation time; (2) increasing PACU beds; (3) improving OR preparation time; (4) use of new equipment to reduce the operative time of a selected surgery type; three levels of improvement (slight, moderate, large) were investigated.

RESULTS

The first three improvement scenarios resulted in a 1%-5% increase in OR throughput across the three departments. Large reductions in operative time of the selected surgery types led to approximately 12%, 33%, and 38% increases in gastrointestinal, thoracic, and orthopedic surgery throughput, respectively. Moderate reductions resulted in 6%-17% increases in throughput and slight reductions of 1%-7%.

CONCLUSIONS

The model could reliably reflect OR workflows of the three departments. Among the options investigated, model simulations suggest that improving OR preparation time and operative time are the most effective.

A discrete event simulation for improving operating theatre efficiency

BACKGROUND

Increasing demand in healthcare services has posed excessive burden on healthcare professionals and hospitals with finite capacity. Operating theatres are critical resources within hospitals that can become bottlenecks in patient flow during high demand conditions. There are substantial costs associated with running operating theatres that include keeping professional staff ready, maintaining operating theatres and equipment, environmental services and cleaning of operating theatres and recovery rooms, and these costs can increase if theatres are not used efficiently. In addition to cost, operating theatre inefficiency can result in surgery cancelations and delays, and eventually, poor patient outcomes, which can be exacerbated under the increase in demand.

METHODS

The allocation of surgeries to operating theatres is explored using a simulation model for patients admitted to inpatient beds and sent for surgery. We proposed a discrete event simulation (DES) to model incoming flow to operating theatres of a major metropolitan hospital. We assessed how changing the configuration of surgery at the target hospital affects Key Performance Indicators relating to theatre efficiency. In particular, the model was used to assess impacts of six different scenarios by defining new/hypothetical theatre case-mix, opening and closing times of theatres, turnaround (changeover) time, and repurposing the theatres. Target performance metrics included theatre utilisation, pre-operative length-of-stay, average reclaimable time, the percentage of total theatre time in a year that could be reclaimed, and patient waiting time. A web-based application was developed that allows testing user-defined scenarios and interactive analysis of the results.

RESULTS

Extending the opening hours of operating theatres by 1 hour almost halved the number of deferred electives as well as over-run cases but at the expense of reduced theatre utilisation. A one-hour reduction in opening hours resulted in 10 times more deferred elective cases and a negligible increase in theatre utilisation. Reducing turnaround time by 50% had positive effects on theatre management: increased utilisation and less deferred and over-run elective cases. Pooling emergency theatres did not affect theatre utilisation but resulted in a considerable reduction in average wait time and the proportion of the delayed emergency cases.

CONCLUSIONS

The developed DES-based simulation model of operating theatres along with the web-based user interface provided a useful interrogation tool for theatre management and hospital executive teams to assess new operational strategies. The next step is to embed simulation as ongoing practices in theatre planning workflow, allowing operational managers to use the model outputs to increase theatre utilisation, and reduce cancellations and schedule changes. This can support hospitals in providing services as efficiently and effectively as possible.

Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review

Discrete-event simulation (DES) is a stochastic modeling approach widely used to address dynamic and complex systems, such as healthcare. In this review, academic databases were systematically searched to identify 231 papers focused on DES modeling in healthcare. These studies were sorted by year, approach, healthcare setting, outcome, provenance, and software use. Among the surveys, conceptual/theoretical studies, reviews, and case studies, it was found that almost two-thirds of the theoretical articles discuss models that include DES along with other analytical techniques, such as optimization and lean/six sigma, and one-third of the applications were carried out in more than one healthcare setting, with emergency departments being the most popular. Moreover, half of the applications seek to improve time- and efficiency-related metrics, and one-third of all papers use hybrid models. Finally, the most popular DES software is Arena and Simul8. Overall, there is an increasing trend towards using DES in healthcare to address issues at an operational level, yet less than 10% of DES applications present actual implementations following the modeling stage. Thus, future research should focus on the implementation of the models to assess their impact on healthcare processes, patients, and, possibly, their clinical value. Other areas are DES studies that emphasize their methodological formulation, as well as the development of frameworks for hybrid models.