Discrete event simulation (DES) is a form of computer-based modeling that provides an intuitive and flexible approach to representing complex systems. It has been used in a wide range of health care applications. Most early applications involved analyses of systems with constrained resources, where the general aim was to improve the organization of delivered services. More recently, DES has increasingly been applied to evaluate specific technologies in the context of health technology assessment. The aim of this article was to provide consensus-based guidelines on the application of DES in a health care setting, covering the range of issues to which DES can be applied. The article works through the different stages of the modeling process: structural development, parameter estimation, model implementation, model analysis, and representation and reporting. For each stage, a brief description is provided, followed by consideration of issues that are of particular relevance to the application of DES in a health care setting. Each section contains a number of best practice recommendations that were iterated among the authors, as well as among the wider modeling task force.

The economic evaluation of health technologies has become a major tool in health policy in Europe for prioritizing the allocation of health resources and the approval of new technologies. The objective of this proposal was to develop guidelines for the economic evaluation of health technologies in Spain. A group of researchers specialized in economic evaluation of health technologies developed the document reported here, following the initiative of other countries in this framework, to provide recommendations for the standardization of methodology applicable to economic evaluation of health technologies in Spain. Recommendations appear under 17 headings or sections. In each case, the recommended requirements to be satisfied by economic evaluation of health technologies are provided. Each recommendation is followed by a commentary providing justification and compares and contrasts the proposals with other available alternatives. The economic evaluation of health technologies should have a role in assessing health technologies, providing useful information for decision making regarding their adoption, and they should be transparent and based on scientific evidence.

Over the last few years, economic evaluation of health technologies has become a major tool used by European health policy decision-makers to create strategies for prioritizing the allocation of health resources and the approval of new technologies. Spain was a pioneer in proposing the standardization of methodology applicable to economic evaluation studies. However, because health policy decision-makers refused to support the initiative, the methodology was never put into practice. In the medium term, evidence of the economic value of new health technologies financed by the national health system will probably be increasingly required. At that time, stakeholders and decision-makers will have to agree upon a clear and concise set of rules on the technical and methodological issues that must be followed by economic evaluations of health technologies. Consequently, we have provided guidelines and recommendations for producing first-rate economic evaluations. The recommendations appear under seventeen headings or sections. In each case, the recommended requirements to be satisfied by an economic evaluation of health technologies are provided and each recommendation is followed by a commentary, providing a justification and comparing and contrasting the proposal with other available alternatives.

The demand for diagnostic and therapeutic services for obstructive sleep apnoea syndrome (OSAS) showed marked growth during the 1990s. This paper analyses the long-term cost-effectiveness of nasal continuous positive airway pressure (nCPAP) treatment in comparison to conventional null treatment.A Markov model was used to represent the natural history of OSAS based upon published evidence. Utility values came from a survey of OSAS patients. Data on health costs were collected from hospitals in the Basque Country, Spain.The incremental cost-effectiveness ratio of nCPAP treatment is v6,000 Euros per quality-adjusted life year. On disaggregated analysis, nCPAP treatment accounts for 86% of incremental costs; 84% of incremental effectiveness is attributable to improved quality of life.Treatment of obstructive sleep apnoea syndrome with nasal continuous positive airway pressure has a cost-effectiveness that is in line with that of other commonly funded treatments such as antihypertensive drugs. The key clinical benefit of nasal continuous positive airway pressure treatment is improvement in the quality of life of patients with obstructive sleep apnoea syndrome. This benefit is also precisely the one for which the evidence base is strongest. The remaining uncertainties concerning the impact of nasal continuous positive airway pressure on long-term mortality have only a relatively small impact on the economics of treatment. Eur Respir J 2003; 21: 515-522.

In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque health managers and Government during the COVID-19 responses. BMTF is a modelling team, working on different approaches, including stochastic processes, statistical methods and artificial intelligence. Here we describe the efforts and challenges to develop a flexible modeling framework able to describe the dynamics observed for the tested positive cases, including the modelling development steps. The results obtained by a new stochastic SHARUCD model framework are presented. Our models differentiate mild and asymptomatic from severe infections prone to be hospitalized and were able to predict the course of the epidemic, providing important projections on the national health system’s necessities during the increased population demand on hospital admissions. Short and longer-term predictions were tested with good results adjusted to the available epidemiological data. We have shown that the partial lockdown measures were effective and enough to slow down disease transmission in the Basque Country. The growth rate $$ \lambda $$ λ was calculated from the model and from the data and the implications for the reproduction ratio r are shown. The analysis of the growth rates from the data led to improved model versions describing after the exponential phase also the new information obtained during the phase of response to the control measures. This framework is now being used to monitor disease transmission while the country lockdown was gradually lifted, with insights to specific programs for a general policy of “social distancing” and home quarantining.