What Drives Variations in Relative Effectiveness Across Countries?
This study provides an analytical framework, drawing on production function theory, to identify and quantify the determinants of relative effectiveness and sources of variation in the relative effectiveness of treatments between populations and healthcare systems. Relative effectiveness is a key…
This study provides an analytical framework, drawing on production function theory, to identify and quantify the determinants of relative effectiveness and sources of variation in the relative effectiveness of treatments between populations and healthcare systems.
Relative effectiveness is a key topic within health policy. In Europe, this is due to the need for early information to guide reimbursement and funding decisions about new medical technologies. However, the reasons why evidence on effectiveness (does it work?) and efficacy (can it work?) might differ across health systems are poorly understood.
Provide an analytical framework, drawing on production function theory, to systematically identify and quantify the determinants of relative effectiveness and sources of variation between populations and healthcare systems; and
Test this framework using evidence on breast cancer from England, Spain, and Sweden as a case study, and investigate the reasons why the relative effectiveness of a new drug might vary across healthcare systems.
The first paper finds that better evidence on factors driving relative effectiveness could:
inform decisions on how best to use a new technology to maximise its effectiveness
establish whether there is a need for follow-up post-launch studies, and
provide evidence of the impact of new health technologies on outcomes in different healthcare systems.
The authors conclude there is a strong case for exploring the use of a health production function approach to better understand the impact of new medicines and devices for improvements in health outcomes. Moreover, the health production function approach is complementary to traditional experimental and observational studies, focusing on identifying, collecting, and analysing data at the national level, enabling comparisons to take place.
The second paper focuses on breast cancer. In order to highlight potential cross-country differences in the relative effectiveness of a new drug we reviewed studies investigating reasons for differences in health outcomes in breast cancer. We also reviewed relevant national clinical guidelines and health technology assessment (HTA) reports to understand similarities and differences in the management of breast cancer between countries. We show how our analytical framework can help to understand the factors that might drive differences in relative effectiveness across different settings.
The review included thirteen international studies and thirty country-specific studies. Cross-country differences in population age structure, deprivation, and educational attainment were consistently associated with variation in outcomes. Screening intensity appeared to drive differences in survival, although the impact on mortality was unclear.
Studies that show differences in relative effectiveness between countries, or that identify factors suggesting these exist, provide one way to identify how health system performance can be improved.
Finally, we consider the implications for data sharing across health care systems. For example,
In some cases, it will be reasonable to expect evidence on relative effectiveness to be transferable
In other cases, it may be possible to anticipate and adjust for expected differences in relative effectiveness between countries, and so use evidence from one country in another
In other cases, however, an understanding of relative effectiveness in a country may generate questions that cannot be answered by existing evidence and that require a bespoke study.
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