Advancing the Health Economic evidence available to inform economic models and decisions about appropriate Cystic Fibrosis care

Mohindru, Bishal (2021) Advancing the Health Economic evidence available to inform economic models and decisions about appropriate Cystic Fibrosis care. Doctoral thesis, University of East Anglia.

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Abstract

Cystic Fibrosis (CF) is a genetic disease which impacts multiple organs in the body. As a result, CF individuals require lifelong care. Over the years, there has been an increase in the availability of treatments for CF leading to improvements in health. However, these improvements can place significant burden on the NHS. Economic evaluations capture both the costs and the benefits of treatment, which can be further extended through health economic modelling. This framework allows decision makers to make recommendations on the use of such treatments in the NHS. This thesis focuses on improving evidence availability for the health economic modelling of CF treatments and decision about appropriate care.

A review of health economic modelling studies was carried out. Studies were evaluated for model structure, data inputs and modelling methods for areas requiring improvement. The evidence from the review and discussion with clinical experts was used to develop a De Novo health economic model. Regression modelling was used to generate novel health state transition and cost data from the U.K. CF Data Registry (2005-2016). An exemplar cost-utility analysis on Orkambi® was conducted to validate the De Novo model and input data. Statistical tests, between model consistency, clinical expert opinion and the observed data was used for validation.

The results of the study show that the input data were comparable to data found in the literature and used in existing health economic models. The De Novo model produced comparable ICER and cost estimates to those found in the literature. The methods of the work conducted in this thesis can be applied to other Data Registries. They prove to be a strong supportive tool with great potential to improve the cost effectiveness evaluation of existing and novel treatments in the future.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: Chris White
Date Deposited: 23 Mar 2022 09:33
Last Modified: 23 Mar 2022 09:33
URI: https://ueaeprints.uea.ac.uk/id/eprint/84234
DOI:

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