A Literature Review on Validated Simulations of the Surgical Services

Modelling vaccination capacity at mass vaccination hubs and general practice clinics: a simulation study

Background

COVID-19 mass vaccination programs place an additional burden on healthcare services. We aim to model the queueing process at vaccination sites to inform service delivery.

Methods

We use stochastic queue network models to simulate queue dynamics in larger mass vaccination hubs and smaller general practice (GP) clinics. We estimate waiting times and daily capacity based on a range of assumptions about appointment schedules, service times and staffing and stress-test these models to assess the impact of increased demand and staff shortages. We also provide an interactive applet, allowing users to explore vaccine administration under their own assumptions.

Results

Based on our assumed service times, the daily throughput for an eight-hour clinic at a mass vaccination hub ranged from 500 doses for a small hub to 1400 doses for a large hub. For GP clinics, the estimated daily throughput ranged from about 100 doses for a small practice to almost 300 doses for a large practice. What-if scenario analysis showed that sites with higher staff numbers were more robust to system pressures and mass vaccination sites were more robust than GP clinics.

Conclusions

With the requirement for ongoing COVID-19 booster shots, mass vaccination is likely to be a continuing feature of healthcare delivery. Different vaccine sites are useful for reaching different populations and maximising coverage. Stochastic queue networks offer a flexible and computationally efficient approach to simulate vaccination queues and estimate waiting times and daily throughput to inform service delivery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08447-8.

Simulation Modelling in Healthcare: An Umbrella Review of Systematic Literature Reviews

BACKGROUND

Numerous studies examine simulation modelling in healthcare. These studies present a bewildering array of simulation techniques and applications, making it challenging to characterise the literature.

OBJECTIVE

The aim of this paper is to provide an overview of the level of activity of simulation modelling in healthcare and the key themes.

METHODS

We performed an umbrella review of systematic literature reviews of simulation modelling in healthcare. Searches were conducted of academic databases (JSTOR, Scopus, PubMed, IEEE, SAGE, ACM, Wiley Online Library, ScienceDirect) and grey literature sources, enhanced by citation searches. The articles were included if they performed a systematic review of simulation modelling techniques in healthcare. After quality assessment of all included articles, data were extracted on numbers of studies included in each review, types of applications, techniques used for simulation modelling, data sources and simulation software.

RESULTS

The search strategy yielded a total of 117 potential articles. Following sifting, 37 heterogeneous reviews were included. Most reviews achieved moderate quality rating on a modified AMSTAR (A Measurement Tool used to Assess systematic Reviews) checklist. All the review articles described the types of applications used for simulation modelling; 15 reviews described techniques used for simulation modelling; three reviews described data sources used for simulation modelling; and six reviews described software used for simulation modelling. The remaining reviews either did not report or did not provide enough detail for the data to be extracted.

CONCLUSION

Simulation modelling techniques have been used for a wide range of applications in healthcare, with a variety of software tools and data sources. The number of reviews published in recent years suggest an increased interest in simulation modelling in healthcare.