| Literature DB >> 31179038 |
Thomas Butt1,2, Gordon G Liu1, David D Kim3, Peter J Neumann3.
Abstract
INTRODUCTION: Cost-effectiveness analysis (CEA) is playing an increasingly important role in informing healthcare decision-making in China. This study aims to review the published literature on CEA in mainland China and describe its characteristics and evolution. We provide recommendations on the future direction of CEA as a methodology and as a tool to support healthcare decision-making in China.Entities:
Keywords: China; DALY; QALY; cost-effectiveness analysis; health technology assessment
Year: 2019 PMID: 31179038 PMCID: PMC6528776 DOI: 10.1136/bmjgh-2019-001418
Source DB: PubMed Journal: BMJ Glob Health ISSN: 2059-7908
Study characteristics
| Variable | QALY | DALY | ||
| All | Primary geography=China | All | Primary geography=China | |
| Studies, n | 125 | 121 | 45 | 23 |
| Top three disease areas, name (%) | ||||
| 1 | Oncology (34.7) | Oncology (35.7) | Infectious and parasitic diseases (62.2) | Infectious and parasitic diseases (60.9) |
| 2 | Infectious and parasitic diseases (25.7) | Infectious and parasitic diseases (25.5) | Endocrine, nutritional and metabolic diseases (11.1) | Endocrine, nutritional and metabolic diseases (13.0) |
| 3 | Endocrine, nutritional and metabolic diseases (14.9) | Endocrine, nutritional and metabolic diseases (15.3) | Oncology (6.7) | Oncology (8.7) |
| First author affiliation=China, % | 80.8 | 82.6 | 35.6 | 65.2 |
| Academic author, % | 79.2 | 79.3 | 82.2 | 58.3 |
| Government sponsorship, % | 42.4 | 42.1 | 51.1 | 41.7 |
| Healthcare payer perspective, % | 57.1 | 58.4 | 35.6 | 26.1 |
| Quality score, mean | 5.04 | 5.05 | 4.70 | 4.41 |
Disease area categories are based on International Classification of Diseases 10th Revision (ICD-10) chapters.
DALY, disability-adjusted life-year; QALY, quality-adjusted life-year.
Figure 1Cost-effectiveness analysis (CEA) studies by year of publication. DALY, disability-adjusted life-year; QALY, quality-adjusted life-year.
Changes over time in study characteristics
| 1998–2010 (n=26) | 2011–2013 (n=31) | 2014–2015 (n=43) | 2016–2017 (n=71) | Test for trend, P value | |
| QALY as unit of health benefit, % | 42.3 | 64.5 | 81.4 | 83.1 | <0.0001 |
| First author at Chinese institution, % | 38.5 | 73.3 | 67.4 | 78.9 | 0.0002 |
| Quality score (cost-per-QALY studies), mean | 4.59 | 4.95 | 4.95 | 5.27 | – |
| Quality score (cost-per-DALY studies), mean | 4.43 | 4.60 | 4.81 | 5.04 | – |
DALY, disability-adjusted life-year; QALY, quality-adjusted life-year.
Figure 2Characteristics of cost-effectiveness analysis (CEA) studies. (A) Author affiliations. (B) Source of sponsorship. *Includes academic. **Includes intergovernmental organisations. DALY, disability-adjusted life-year; QALY, quality-adjusted life-year.
Logistic regression to identify factors that influence the probability that the ICER is greater than the weighted median for ratios in the north-east quadrant for cost-per-QALY studies
| Model 1: disease area | Model 2: full | |||||
|
|
|
|
|
|
|
|
| Disease area=oncology | 3.03*** | 1.12 | 0.003 | 3.22*** | 1.27 | 0.003 |
| Sponsor=industry | – | – | – | 0.66 | 0.38 | 0.466 |
| Author=industry | – | – | – | 0.43 | 0.39 | 0.352 |
| Study quality (subjective score) | – | – | – | 1.27* | 0.17 | 0.069 |
| Constant | 0.70* | 0.15 | 0.086 | 0.21** | 0.15 | 0.026 |
| Observations | 208 | 208 | ||||
Variables were coded as follows: disease area oncology=1, disease area not oncology=0; study sponsor included industry=1, sponsor did not include industry=0; author list included industry=1, author list did not include industry=0; study quality=1–7 interval scale (half-points were possible).
***p<0.01; **p<0.05; *p<0.10.
ICER, incremental cost-effectiveness ratio; OR, odds ratio; QALY, quality-adjusted life-year; SE, standard error.