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PRECISE: A health economic approach to evaluate uncertain evidence in personalised medicine

Reference number
Coordinator Linköpings universitet
Funding from Vinnova SEK 4 732 029
Project duration May 2019 - August 2023
Status Completed

Purpose and goal

The main aim of the project was to develop simulation models to evaluate diagnostic strategies in fatty liver disease, as well as developing methods to handle uncertainty in such evaluations. Two models, based on a comprehensive review of the scientific literature, were constructed for the evaluation of fatty liver disease. The project also developed several tutorial models used for methods development; these were presented in additional reports. The project interacted with relevant authorities and stakeholders via workshops and collaborations.

Expected effects and result

The case study in fatty liver disease reveals the complexity of evaluating advanced management strategies with diagnostics and tailored treatments. The results show that current clinical practice is not cost-effective. Applying the methodological framework developed by the project in the evaluation of precision medicine can ensure that new technologies that generate health at an acceptable cost are identified. The case study of the project illustrates the importance of rigorous assessment prior to implementation.

Planned approach and implementation

The case study has been executed according to the project plan. A systematic review of existing models formed the basis of the simulation model that was constructed and programmed into the software R. Data from registers as well as available literature was used to populate the model. In addition to the evaluation results, comprehensive analyses of uncertainty and validity were undertaken. The latter appears particularly important for future studies; examples are provided in the report. Certain methods aspects were analyzed by the developed tutorial models.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 20 October 2023

Reference number 2019-01189

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