Meta-analysis of data on costs from trials of counselling in primary care: using individual patient data to overcome sample size limitations in economic analyses

P Bower, S Byford, J Barber, J Beecham, S Simpson, K Friedli, R Corney, M King, I Harvey

    Research output: Contribution to journalArticlepeer-review

    39 Citations (Scopus)
    47 Downloads (Pure)

    Abstract

    Objective: To assess the feasibility of overcoming sample size limitations in economic analyses of clinical trials through meta-analysis of data on individual patients from multiple trials.
    Design: Meta-analysis of individual patient data from trials of counselling in primary care compared with usual care by a general practitioner.
    Setting: Primary care.
    Patients: People with mental health problems.
    Main outcome measures: Direct treatment costs, depressive symptoms, and cost effectiveness.
    Results: Meta-analysis of individual patient data proved feasible. The results showed that the previous analyses of individual trials were underpowered to provide useful conclusions about the cost comparisons. The results are sensitive to assumptions made about the costs of sessions with a counsellor and the management of patients by a general practitioner.
    Conclusions: Meta-analysis of individual patient data may assist in overcoming sample size limitations in economic analyses. Although feasible, such analysis has shortcomings that may limit the validity of the results. The relative costs and benefits of this method, as opposed to further collection of primary data, are as yet unclear.

    Original languageEnglish
    Pages (from-to)1247-1250
    Number of pages4
    Journal British Medical Journal (BMJ)
    Volume326
    Issue number7401
    DOIs
    Publication statusPublished - 7 Jun 2003

    Keywords

    • RANDOMIZED CONTROLLED-TRIAL
    • NEED

    Fingerprint

    Dive into the research topics of 'Meta-analysis of data on costs from trials of counselling in primary care: using individual patient data to overcome sample size limitations in economic analyses'. Together they form a unique fingerprint.

    Cite this