Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model.
Healthcare is one of the most complex systems to manage. In recent years, the control of processes and the modelling of public administrations have been considered some of the main areas of interest in management. In particular, one of the most problematic issues is the management of waiting lists and the consequent absenteeism of patients. Patient no-shows imply a loss of time and resources, and in this paper, the strategy of overbooking is analysed as a solution. Here, a real waiting list process is simulated with discrete event simulation (DES) software, and the activities performed by hospital staff are reproduced. The methodology employed combines agile manufacturing and Six Sigma, focusing on a paediatric public hospital pavilion. Different scenarios show that the overbooking strategy is effective in ensuring fairness of access to services. Indeed, all patients respect the times dictated by the waiting list, without “favouritism”, which is guaranteed by the logic of replacement. In a comparison between a real sample of bookings and a simulated sample designed to improve no-shows, no statistically significant difference is found. This model will allow health managers to provide patients with faster service and to better manage their resources.
The Analytic Hierarchy Process (AHP) is a methodology, based on both mathematical and psychological approaches, exploited to analyze and solve complex problems, in order to make the best decision. AHP is also widely employed for the evaluation of healthcare systems. It works by splitting the decision problem into a hierarchy of more easily-comprehended sub-problems, each of which can be independently analyzed. Starting from these assumptions, our work aims to implement a dynamic framework for the AHP methodology, able to overcome the static nature of the technique, taking into account the evaluations associated with criteria and sub-criteria as a function of time. In the context of this paper, the Dynamic AHP is implemented as a tool for Health Technology Assessment (HTA). Indeed, the proposed case study concerns the evaluation of a new health technology for the thyroglobulin assay in patients with differentiated thyroid cancer. To this aim, we have defined the decision problem and formalized criteria and sub-criteria hierarchically; then, in order to deal with the problem from a dynamical point of view, i.e., to take into account the time dependence of criteria and sub-criteria, we developed several System Dynamics models, one for each criterion. In this context, it is shown that the Dynamic AHP approach provides a dynamic evaluation of the system, which allows to identify the best decision by exploiting the information on the possible evolution of the problem due to its time behavior, rather than taking the decision at a fixed time point, as the Static AHP does.
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