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Decision support for cost-effectiveness of healthcare interventions

Goeree, B.N. (2014) Decision support for cost-effectiveness of healthcare interventions. Master's Thesis / Essay, Industrial Engineering and Management.

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The innovation of the pharmaceutical market has greatly improved health outcomes, but also has led to an increased usage of resources (such as money, time, and personnel). As a result, health care systems are putting an increasing strain on the economies of countries. In order to combat these increased costs, regulators take decisions concerning the amount of money to be spend on health care. One of the most important decisions with regards to monetary value, is whether to reimburse a new intervention, or not. To inform such decisions, a new product is thoroughly analyzed and tested. However all these analyses and tests are published on their own discretion. This leaves the decision maker with a myriad of unstructured, high quality, evidence. Ideally a decision maker is informed by all this high quality evidence. To achieve this, it is common practice for a decision maker to request a cost-effectiveness analysis to be carried out by a specialist. The aim of this analysis is to provide the decision maker with an integrated view of all the available evidence. However, conducting such analyses proves to be a very time consuming task. This is largely caused by the fact that (1) a repository containing structured data concerning all the available evidence does not exist, (2) after manual collection the accompanying analysis model is also created manually, and finally (3) computation and outcome presentation are, again, manually coded on a model-by-model basis. In this thesis a decision support system, which aims to alleviate the manual workload concerned with the creation (step 2) and presentation (step 3) of a cost-effectiveness model, is presented.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Industrial Engineering and Management
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 07:59
Last Modified: 15 Feb 2018 07:59

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