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 provides an overview of the level of activity of simulation modelling in healthcare and the key themes. METHODS: 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, Science Direct) and grey literature sources, enhanced by citation searches. The articles were included if they performed a systematic review of simulation modelling techniques in health care. After quality assessment of all included articles, data was 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 checklist. All the review articles described the types of applications used for simulation modelling; 15 reviews described techniques used for simulation modelling; 3 reviews described data sources used for simulation modelling; and 6 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 the recent years suggest an increased interest for simulation modelling in healthcare. (263 words)

OBJECTIVE:To conduct a systematic review of published research on the use of discrete event simulation (DES) for resource modelling in health technology assessment (HTA). Resource modelling (RM) is broadly defined as incorporating and measuring effects of constraints on physical resources (e.g. beds, doctors, nurses) in HTA models. METHODS: Systematic literature searches were conducted in academic databases (JSTOR, SAGE, SPRINGER, SCOPUS, IEEE, Science Direct, PUBMED, EMBASE) and grey literature (Google Scholar, NHS journal library), enhanced by manual searchers (i.e. reference list checking, citation searching and hand searching techniques). RESULTS:The search strategy yielded 4,117 potentially relevant citations. Following the screening and manual searches, 10 articles were included. Reviewing these articles provided insights into the applications of RM: firstly, different types of economic analyses, model settings, RM and costeffectiveness analysis (CEA) outcomes were identified. Secondly, variation in the characteristics of the constraints such as types and nature of constraints, sources of data for the constraints were identified. Thirdly, it was found that including the effects of constraints caused the CEA results to change in these articles. CONCLUSION:The review found that DES proved to be an effective technique for RM but there were only a small number of studies applied in HTA. However, these studies showed the important consequences of modelling physical constraints and point to the need for a framework to be developed to guide future applications of this approach. (230 words) Keywords Discrete event simulation, resource modelling, health technology assessment, simulation modelling 2 Key Points for Decision Makers  Economic evaluation studies in health care typically ignore the short-term constraints on physical resources (e.g. doctors, nurses) which can lead to incorrect results.  Discrete Event Simulation is an effective tool for modelling the effects of constraints but there were only a small number of studies applied in health technology assessment (HTA).  Further research is required to examine the possible developments for detailed modelling of the resource constraints in HTA.