Improta, Giovanni (2017) Dynamic Analytic Hierarchy Process: a new approach to technology assessment to support healthcare processes. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: Dynamic Analytic Hierarchy Process: a new approach to technology assessment to support healthcare processes
Date: 8 April 2017
Number of Pages: 219
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Chimica, dei Materiali e della Produzione Industriale
Dottorato: Ingegneria dei prodotti e dei processi industriali
Ciclo di dottorato: 29
Coordinatore del Corso di dottorato:
Santillo, Liberatina CarmelaUNSPECIFIED
Date: 8 April 2017
Number of Pages: 219
Uncontrolled Keywords: AHP; Analytic Hierarchy Process; HTA; Health Technology Assessment; Decision Making; Healthcare
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/17 - Impianti industriali meccanici
Date Deposited: 25 Apr 2017 17:10
Last Modified: 08 Mar 2018 13:48


The Analytic Hierarchy Process (AHP) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. In particular, AHP is used around the world in a wide variety of decision situations decomposing the relative decision problem into a hierarchy of more easily-comprehended sub-problems, each of which can be analyzed independently. Our thesis work aims to provide a dynamic view of the AHP to overcome the static nature of the methodology, taking into account the evaluations associated with criteria and alternatives as a function of time and considering internal dependence loop. First, we have defined the decision problem and decomposed hierarchically criteria and sub-criteria, and later, we have developed several System Dynamics models. Our case study concerned with evaluating a new health technology for the assay of thyroglobulin in patients with differentiated thyroid cancer. Indeed, the dynamic AHP provides a dynamic image of the system where the best decision can be different compared to all decisions obtained at different times.


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