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Understanding Variations in Relative Effectiveness: A Health Production Approach

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Author(s)

  • Adrian Towse
  • Bengt Jonsson
  • Clare McGrath
  • Anne Mason
  • Ruth Puig-Peiro
  • Jorge Mestre-Ferrandiz
  • Michele Pistollato
  • Nancy Devlin

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Publication details

JournalInternational Journal of Technology Assessment in Health Care
DateE-pub ahead of print - 3 Feb 2016
DatePublished (current) - 2016
Issue number6
Volume31
Number of pages8
Pages (from-to)363-370
Early online date3/02/16
Original languageEnglish

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.

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© Cambridge University Press 2016. This content is made available by the publisher under a Creative Commons Attribution Licence. This means that a user may copy, distribute and display the resource providing that they give credit. Users must adhere to the terms of the licence.

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