Quality assessment of pharmacoeconomic evaluation literature in China from 2018 to 2022 / 中国药房

ABSTRACT

OBJECTIVE To analyze existing problems of pharmacoeconomic evaluation research in China and to improve the standardization and scientificity of research， so as to provide more high-quality evidence for government decision-making. METHODS Retrieved from CNKI， Wanfang database， VIP， PubMed， Web of Science from 2018 to 2022， the literature related to pharmacoeconomic evaluation in China was collected； Excel 2016 software was used to extract the key information of the included literature which met inclusion criteria. The Quality of Health Economic Studies （QHES） scale was used to evaluate the quality of the included literature. RESULTS A total of 113 pieces of literature were included in this study， involving 85 pieces of Chinese literature and 28 pieces of English literature. The overall score of QHES included literature was 65.7， of which the average score of Chinese literature was 62.0 and English literature was 76.9. The median quality scores for the literature in 2018， 2019， 2020， 2021 and 2022 were 62.0， 70.5， 59.3， 71.0， and 73.0， respectively. Of these， 65 pieces of literature reported the research perspective； 36 reported the discount rate indistinctly； 25 provided unclear definitions of thresholds； and 53 used two sensitivity analysis methods. Among different items of the QHES scale， item 2 （research perspective）， item 8 （time range and discount rate）， item 14 （potential bias） and item 16 （sources of funding） had low percentage of scores. CONCLUSIONS From 2018 to 2022， pharmacoeconomic evaluation literature published by Chinese academics has generally shown a fluctuating upward trend in terms of quality， but there is still some room for improvement. The main problems in current pharmacoeconomics research in China include unclear understanding of the research perspective， single measurement of cost and health outcomes， unreasonable design of time horizon， indistinct description of the threshold or discount rate， and lack of sensitivity analysis.