PharmacoEconomics

, Volume 31, Issue 2, pp 163–171 | Cite as

Valuing Benefits to Inform a Clinical Trial in Pharmacy

Do Differences in Utility Measures at Baseline Affect the Effectiveness of the Intervention?
  • Michela Tinelli
  • Mandy Ryan
  • Christine Bond
  • Anthony Scott
Original Research Article

Abstract

Background

The generic health-related quality-of-life (HR-QOL) utility measures the EQ-5D and SF-6D are both commonly used to inform healthcare policy developments. However, their application to pharmacy practice is limited and the optimal method to inform policy developments is unknown.

Objectives

Our objective was to test the sensitivity of the EQ-5D and SF-6D within pharmacy when measuring whether changes in health status or other co-variates at baseline affect the effectiveness of the intervention at follow-up. A further objective was to consider the implications of the findings for pharmacy research and policy.

Methods

The EQ-5D and SF-6D utility measures were employed within a randomized controlled trial (RCT) of community pharmacy-led medicines management for patients with coronary heart disease. The intervention covered a baseline visit with the potential for follow-up. Simultaneous quantile regression assessed the impact of the intervention on both EQ-5D and SF-6D measures at follow-up, controlling for baseline health, appropriateness of treatment, personal characteristics and self-reported satisfaction.

Results

No statistically significant difference in HR-QOL across the intervention and control groups at follow-up was reported for either measure. Increased health gain was however associated with the baseline utility score (with the EQ-5D more sensitive for those in worse health) and the appropriateness of treatment, but not patient characteristics or self-reported satisfaction.

Conclusion

Neither generic measure detected a gain in HR-QOL as a result of the introduction of an innovative pharmacy-based service. This finding supports other work in the area of pharmacy, where health gains have not changed following interventions. Disease-specific utility measures should be investigated as an alternative to generic approaches such as the EQ-5D and SF-6D. Given that the RCT found an increase in self-reported satisfaction, broader measures of benefit that value patient experiences, such as contingent valuation and discrete-choice experiments, should also be considered in pharmacy.

Notes

Acknowledgements

The authors would like to thank the medical statistician and senior lecturer Dr Lorna Aucott, University of Aberdeen, for her helpful comments and suggestions. The MEDMAN trial was funded by the Department of Health for England and Wales and managed by a collaboration of the National Pharmaceutical Association, the Royal Pharmaceutical Society of Great Britain, the Company Chemist Association and the Co-operative Pharmacy Technical Panel, led by the Pharmaceutical Services Negotiating Committee. The research in this paper was undertaken while the author M. Tinelli was undertaking a research fellowship jointly funded by the Economic and Social Research Council (ESRC) and the Medical Research Council (MRC). The Health Economics Research Unit (HERU), University of Aberdeen is funded by the Chief Scientist Office of the Scottish Government Health Directorate. The authors’ work was independent of the funders.

Conflicts of interest

The authors declare no conflicts of interest.

Author contributions

M. Tinelli contributed to data collection, analysis, and drafting and revision of this paper. M. Ryan contributed to planning of the analysis, interpretation of the results, and contributed to drafting and revision of this paper. C. Bond was the principal investigator and guarantor for the MEDMAN trial report. She contributed to the conception and design of the study, to the establishment of the team, to all aspects of study management, to planning of the analysis, interpretation of the results, and drafting and revision of this paper. A. Scott contributed to study design, some aspects of study management, some aspects of data analysis, and interpretation of the results. He also contributed to drafting and revision of this paper. C. Bond is the guarantor for the overall content of this paper.

Supplementary material

40273_2012_12_MOESM1_ESM.pdf (23 kb)
Supplementary material 1 (PDF 22 kb)

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Copyright information

© Springer International Publishing Switzerland 2012

Authors and Affiliations

  • Michela Tinelli
    • 1
    • 2
    • 4
  • Mandy Ryan
    • 1
  • Christine Bond
    • 2
  • Anthony Scott
    • 3
  1. 1.Health Economics Research Unit (HERU)University of AberdeenAberdeenUK
  2. 2.Centre of Academic Primary CareUniversity of AberdeenAberdeenUK
  3. 3.Melbourne Institute of Applied Economic and Social ResearchUniversity of MelbourneMelbourneAustralia
  4. 4.LSE Health and Social CareLondon School of Economics and Political ScienceLondonUK

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