Machine learning-based models for prediction of innovative medicine reimbursement decisions in Scotland.

Journal: Journal of epidemiology and population health

PMID: 39826204

Abstract

OBJECTIVE: This study aimed to investigate the critical factors for reimbursement decisions of innovative medicines in Scotland and to explore the feasibility of machine learning models for predicting decisions.

Authors

Yitong Wang

Department of Pharmacy, Peking University People's Hospital, 11 Xizhimen South Street, Xicheng District, Beijing 100044, China; Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.
Keith Tolley

Tolley Health Economics Ltd, Unit 5 11-13 Eagle Parade Buxton Derbyshire SK17 6E, United Kingdom.
Clément Francois

Aix-Marseille University, CEReSS-Health Service Research and Quality of Life Center: UR3279, Marseille, France; Putnam, 75012 Paris, France.
Mondher Toumi

Aix-Marseille University, CEReSS-Health Service Research and Quality of Life Center: UR3279, Marseille, France.

Keywords

Decision Making Decision Trees Humans Machine Learning Reimbursement Mechanisms Scotland

External Resources

View on PubMed Access via DOI PubMed (39826204)

Machine learning-based models for prediction of innovative medicine reimbursement decisions in Scotland.

Abstract

Authors

Keywords

External Resources

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