Understanding Variations in Relative Effectiveness: A Health Production Approach

Abstract

Background: Relative effectiveness has become a key concern of health policy. In Europe, this is because of the need for early information to guide reimbursement and funding decisions about new medical technologies. However, ways that effectiveness (does it work?) and efficacy (can it work?) might differ across health systems are poorly understood.Methods: This study proposes 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. We consider how methods such as stochastic frontier analysis and data envelopment analysis using a Malmquist productivity index could in principle be used to generate evidence on, and improve understanding about, the sources of variation in relative effectiveness between countries and over time.Results: Better evidence on factors driving relative effectiveness could: inform decisions on how to best use a new technology to maximum effectiveness; establish the need if any for follow-up post-launch studies, and provide evidence of the impact of new health technologies on outcomes in different healthcare systems.Conclusions: The health production function approach for assessment of relative effectiveness is complementary to traditional experimental and observational studies, focusing on identifying, collecting, and analyzing data at the national level, enabling comparisons to take place. There is a strong case for exploring the use of this approach to better understand the impact of new medicines and devices for improvements in health outcomes.

Relative Effectiveness in Breast Cancer Treatment: A Health Production Approach

“…In a separate study in this issue ( 3 ), we set out an analytical framework that uses a health production function approach, with health as the output of interest ( 4 ). Inputs (“factors” or “determinants”) are classified according to the level at which they operate: patient level (i.e., individuals’ clinical or socio-demographic characteristics); provider level; and the level of the healthcare environment or system.…”

“…extracted the data from each study into a template, providing details of the study design, countries covered by the study, data sources, health outcomes and findings (see online Supplementary Tables 1 and 2). As shown in Table 2 , the factors identified were then grouped into the framework categories reflecting the level of influence (individual, provider, and national level) using the template from Table 1 in Towse et al 2015 ( 3 ). These data were checked by a second reviewer (A.M.).…”

“…This contrasts with relative efficacy, which is a comparison “under ideal circumstances,” which is usually associated with controlled clinical trials ( 2 ). “Comparative effectiveness” is closely related to relative effectiveness ( 3 ).…”

“…Towse et al ( 3 ) propose an analytical framework, which draws upon production function theory, that describes how certain sets of inputs and processes yield specified outcomes. The aim is to systematically identify and quantify the potential determinants of relative effectiveness.…”

Role of Health Technology Assessment in Pharmaceutical Market Access in Developed Countries

“…Especially payers are more interested in evaluating the relative effectiveness of new healthcare technologies compared to standard care or other technologies, and have documented their preferred comparators [21]. This interest in relative effectiveness information in Europe is due to the early information need for guiding reimbursement and funding decisions about new health technologies [3][4][5]28].…”