Literature DB >> 11700787

Using health outcomes data to inform decision-making: government agency perspective.

R Taylor1.   

Abstract

In the developed world, the demand for healthcare is rising faster than supply, so that governments are faced with the need to allocate limited resources for maximum benefit. Many governments are responding to these pressures by developing health technology assessment agencies, which evaluate the cost effectiveness of new pharmaceutical and medical products relative to existing interventions. In England and Wales, the agency concerned with health technology assessment is the National Institute for Clinical Excellence (NICE). NICE brings together evidence of clinical and cost effectiveness to judge the value of the treatment relative to alternative uses of National Health Service (NHS) resources and makes recommendations on use of the treatment by the NHS in England and Wales. NICE evaluates technologies where they may result in significant impact on NHS resources or key healthcare policy. The health technology assessment includes a review of the clinical effectiveness, cost effectiveness and service impact of the technology under consideration. This health technology assessment report, together with submissions from the technology manufacturer, and patient and healthcare professionals groups, is then considered by an appraisal committee that formulates guidance to the NHS and is ultimately published by NICE. A number of countries have formal guidelines on the use of outcome measures and economic evaluations in the submissions required for health technology assessment prior to market access. These guidelines vary in both the detail and level of mandatory requirement to be followed by technology manufacturers. NICE has recently updated its guidance to technology manufacturers on their submissions. These guidelines, developed in consultation with the healthcare industry, provide detailed specification of the requirements of NICE for health outcomes data and economic evaluation. These details are described in more detail in this paper.

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Year:  2001        PMID: 11700787     DOI: 10.2165/00019053-200119002-00006

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  3 in total

1.  Problems with the interpretation of pharmacoeconomic analyses: a review of submissions to the Australian Pharmaceutical Benefits Scheme.

Authors:  S R Hill; A S Mitchell; D A Henry
Journal:  JAMA       Date:  2000-04-26       Impact factor: 56.272

2.  How well do doctors and nurses work together?

Authors:  C Davies
Journal:  Nurs Times       Date:  1999 Aug 18-24

3.  Early warning of new health care technologies in the United Kingdom.

Authors:  A Stevens; C Packer; G Robert
Journal:  Int J Technol Assess Health Care       Date:  1998       Impact factor: 2.188

  3 in total
  5 in total

1.  Lean systems approaches to health technology assessment: a patient-focused alternative to cost-effectiveness analysis.

Authors:  John F P Bridges
Journal:  Pharmacoeconomics       Date:  2006-12       Impact factor: 4.981

2.  Questionnaire survey for the development and publication of cancer clinical practice guidelines in Japan.

Authors:  Tomohisa Furuhata; Koichi Hirata; Fumihiko Wakao; Kenji Okita; Masafumi Imamura; Yoshihiko Maehara; Masahiko Nishiyama
Journal:  Int J Clin Oncol       Date:  2014-06-26       Impact factor: 3.402

Review 3.  A review of health utilities across conditions common in paediatric and adult populations.

Authors:  Jean-Eric Tarride; Natasha Burke; Matthias Bischof; Robert B Hopkins; Linda Goeree; Kaitryn Campbell; Feng Xie; Daria O'Reilly; Ron Goeree
Journal:  Health Qual Life Outcomes       Date:  2010-01-27       Impact factor: 3.186

4.  Cost-utility of Protocols of BFM-ALL and UK-ALL for Treatment of Children with Acute Lymphoblastic Leukemia in Iran.

Authors:  Hadi Hayati; Abbas Kebriaeezadeh; Mohammad Ali Ehsani; Shekoufeh Nikfar; Ali Akbari Sari; Azim Mehrvar; Elham Shahgholi
Journal:  Iran J Public Health       Date:  2018-03       Impact factor: 1.429

5.  Mapping the FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D.

Authors:  Paulos Teckle; Helen McTaggart-Cowan; Kim Van der Hoek; Stephen Chia; Barb Melosky; Karen Gelmon; Stuart Peacock
Journal:  Health Qual Life Outcomes       Date:  2013-12-01       Impact factor: 3.186

  5 in total

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