A pragmatic review of cost-effectiveness evaluations of reimbursed medical devices conducted for Japan.

Abstract

Aims: The aim of this study is to examine the characteristics and quality of economic evaluations for reimbursed medical devices in Japan.

Materials and methods: A pragmatic review of cost-effectiveness evaluations (CEA) and other economic evaluations for medical devices reimbursed in Japan published between January 2010 and December 2023 was conducted using the PubMed (Medline), Japan Medical Abstracts Society (ICHUSHI Web), and the Cost-Effectiveness Analysis Registry of the Tufts Medical Center databases-as well as Google Scholar. Evaluations for devices assessed under the health technology assessment system in Japan were also reviewed.

Results: Thirty-nine published studies were included with 20 studies (51%) for devices used to treat cardiovascular conditions, 7 studies (18%) for devices used to treat neurological/neurovascular conditions and orthopedic conditions, respectively, and 5 studies (13%) for devices used to treat other types of conditions. The number of published studies for reimbursed medical devices increased from 2017. Nearly 60% of the studies were cost-utility analyses and many were cost-consequence analyses (26%). Although the quality of the studies conducted were good, lack of data was mentioned as a key limitation of nearly all studies-with limited data in general (33%), lack of long-term outcomes data (33%), and lack data for Japan (21%) being key issues. Moreover, lack of cost data was mentioned as a limitation for nearly half (49%) of studies.

Limitations: As this was not a systematic literature review, some relevant studies may have been excluded. Moreover, some databases that are known to cover other journals were not used.

Conclusions: Despite concerns about lack of sufficient outcomes data, good quality CEAs have been published for reimbursed devices in Japan. However, lack of data may still be an issue and the impact of the learning curve effect on cost-effectiveness may need to be considered more.