Literature DB >> 15853432

Future challenges for the economic evaluation of healthcare: patient preferences, risk attitudes and beyond.

John F P Bridges1.   

Abstract

The continued growth in the economic evaluation of healthcare over the past 25 years has led to a shortage of trained health economists globally, leading to a number of universities and/or national governments developing specialised health economics programmes to train more health economists. One of the common problems with many of these training programmes is that they only educate new health economists to the Masters level, and as such they are unable to cover the many skills needed by a successful health economist. Furthermore, government and industry interests have ensured that economic evaluation is a heavily regulated environment that gives little incentive to seek further education. These two related factors (under-education and over-regulation) have lead to a situation where economic evaluation methods may adversely limit innovation of therapeutics and devices in clinical areas that perform badly when evaluated on the cost per QALY scale. The good news, however, is that the tide is turning and theoretically sound adjustments (such as risk adjustments and stated preferences) to the current paradigm are now being considered. This, of cause, is just the tip of the iceberg with other important issues such as time preference and the endogeneity of preference remaining very much under-researched areas in health. This paper concludes that many of these real-world issues, such as patient preferences, can be avoided by using artificial objective functions such as cost per QALY, but this comes at the cost of irrelevance and the misallocation of resources. If we are to meet all of the future challenges in economic evaluation in healthcare then we must focus more on advanced education and far less on the regulation of health economists.

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Year:  2005        PMID: 15853432     DOI: 10.2165/00019053-200523040-00002

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


  15 in total

1.  Addressing uncertainty in medical cost-effectiveness analysis implications of expected utility maximization for methods to perform sensitivity analysis and the use of cost-effectiveness analysis to set priorities for medical research.

Authors:  D Meltzer
Journal:  J Health Econ       Date:  2001-01       Impact factor: 3.883

2.  Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation.

Authors:  M Ryan
Journal:  Soc Sci Med       Date:  1999-02       Impact factor: 4.634

3.  Opportunity costs and uncertainty in the economic evaluation of health care interventions.

Authors:  P Sendi; A Gafni; S Birch
Journal:  Health Econ       Date:  2002-01       Impact factor: 3.046

4.  Cost-effectiveness analysis with risk aversion.

Authors:  J G Zivin
Journal:  Health Econ       Date:  2001-09       Impact factor: 3.046

5.  Valuing the benefits and costs of health care programmes: where's the 'extra' in extra-welfarism?

Authors:  Stephen Birch; Cam Donaldson
Journal:  Soc Sci Med       Date:  2003-03       Impact factor: 4.634

6.  Patient-centered communication.

Authors:  Debra Roter
Journal:  BMJ       Date:  2004-06-12

Review 7.  Cost-effectiveness ratios: in a league of their own.

Authors:  S Birch; A Gafni
Journal:  Health Policy       Date:  1994-05       Impact factor: 2.980

Review 8.  Cost effectiveness/utility analyses. Do current decision rules lead us to where we want to be?

Authors:  S Birch; A Gafni
Journal:  J Health Econ       Date:  1992-10       Impact factor: 3.883

9.  Does "process utility" exist? A case study of willingness to pay for laparoscopic cholecystectomy.

Authors:  C Donaldson; P Shackley
Journal:  Soc Sci Med       Date:  1997-03       Impact factor: 4.634

Review 10.  Pulling cost-effectiveness analysis up by its bootstraps: a non-parametric approach to confidence interval estimation.

Authors:  A H Briggs; D E Wonderling; C Z Mooney
Journal:  Health Econ       Date:  1997 Jul-Aug       Impact factor: 3.046

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  13 in total

1.  Honoring pioneers in patient-centered outcomes research.

Authors:  John F P Bridges; Christopher I Carswell
Journal:  Patient       Date:  2008-01-01       Impact factor: 3.883

2.  Using conjoint analysis to model the preferences of different patient segments for attributes of patient-centered care.

Authors:  Charles E Cunningham; Ken Deal; Heather Rimas; Heather Campbell; Ann Russell; Jennifer Henderson; Anne Matheson; Blake Melnick
Journal:  Patient       Date:  2008-12-01       Impact factor: 3.883

3.  Patients' Preferences for Generic and Branded Over-the-Counter Medicines: An Adaptive Conjoint Analysis Approach.

Authors:  Merja Halme; Kari Linden; Kimmo Kääriä
Journal:  Patient       Date:  2009-12-01       Impact factor: 3.883

4.  Conjoint analysis of French and German parents' willingness to pay for meningococcal vaccine.

Authors:  David Bishai; Roger Brice; Isabelle Girod; Aneta Saleh; Jenifer Ehreth
Journal:  Pharmacoeconomics       Date:  2007       Impact factor: 4.981

Review 5.  [Patient-reported and patient-weighted outcomes in ophthalmology].

Authors:  F Scheibler; R P Finger; R Grosselfinger; C-M Dintsios
Journal:  Ophthalmologe       Date:  2010-03       Impact factor: 1.059

6.  Accounting for tastes: a German perspective on the inclusion of patient preferences in healthcare.

Authors:  Florian Vogt; David L B Schwappach; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2006       Impact factor: 4.981

7.  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

Review 8.  Patient preferences for the treatment of type 2 diabetes: a scoping review.

Authors:  Susan M Joy; Emily Little; Nisa M Maruthur; Tanjala S Purnell; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2013-10       Impact factor: 4.981

9.  Adaptive choice-based conjoint analysis: a new patient-centered approach to the assessment of health service preferences.

Authors:  Charles E Cunningham; Ken Deal; Yvonne Chen
Journal:  Patient       Date:  2010-12-01       Impact factor: 3.883

10.  User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner.

Authors:  Leandro Pecchia; Jennifer L Martin; Angela Ragozzino; Carmela Vanzanella; Arturo Scognamiglio; Luciano Mirarchi; Stephen P Morgan
Journal:  BMC Med Inform Decis Mak       Date:  2013-01-05       Impact factor: 2.796

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