23
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Development of a composite outcome score for a complex intervention - measuring the impact of Community Health Workers

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          In health services research, composite scores to measure changes in health-seeking behaviour and uptake of services do not exist. We describe the rationale and analytical considerations for a composite primary outcome for primary care research. We simulate its use in a large hypothetical population and use it to calculate sample sizes. We apply it within the context of a proposed cluster randomised controlled trial (RCT) of a Community Health Worker (CHW) intervention.

          Methods

          We define the outcome as the proportion of the services (immunizations, screening tests, stop-smoking clinics) received by household members, of those that they were eligible to receive. First, we simulated a population household structure (by age and sex), based on household composition data from the 2011 England and Wales census. The ratio of eligible to received services was calculated for each simulated household based on published eligibility criteria and service uptake rates, and was used to calculate sample size scenarios for a cluster RCT of a CHW intervention. We assume varying intervention percentage effects and varying levels of clustering.

          Results

          Assuming no disease risk factor clustering at the household level, 11.7% of households in the hypothetical population of 20,000 households were eligible for no services, 26.4% for 1, 20.7% for 2, 15.3% for 3 and 25.8% for 4 or more. To demonstrate a small CHW intervention percentage effect (10% improvement in uptake of services out of those who would not otherwise have taken them up, and additionally assuming intra-class correlation of 0.01 between households served by different CHWs), around 4,000 households would be needed in each of the intervention and control arms. This equates to 40 CHWs (each servicing 100 households) needed in the intervention arm. If the CHWs were more effective (20%), then only 170 households would be needed in each of the intervention and control arms.

          Conclusions

          This is a useful first step towards a process-centred composite score of practical value in complex community-based interventions. Firstly, it is likely to result in increased statistical power compared with multiple outcomes. Second, it avoids over-emphasis of any single outcome from a complex intervention.

          Related collections

          Most cited references17

          • Record: found
          • Abstract: found
          • Book: not found

          Essential Medical Statistics

          <b>Blackwell Publishing is delighted to announce that this book has been Highly Commended in the 2004 BMA Medical Book Competition. Here is the judges' summary of this book:</b><p>"This is a technical book on a technical subject but presented in a delightful way. There are many books on statistics for doctors but there are few that are excellent and this is certainly one of them. Statistics is not an easy subject to teach or write about. The authors have succeeded in producing a book that is as good as it can get. For the keen student who does not want a book for mathematicians, this is an excellent first book on medical statistics."<p><i>Essential Medical Statistics</i> is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods.<p>The second edition of <i>Essential Medical Statistics</i> has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data.<p>Aimed at students of medical statistics, medical researchers, public health practitioners and practising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact.<p><i>Essential Medical Statistics</i> is supported by a web site at <b>www.blackwellpublishing.com/essentialmedstats</b>. This useful online resource provides statistical datasets to download, as well as sample chapters and future updates.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Composite outcomes in randomized trials: greater precision but with greater uncertainty?

            Composite outcomes, in which multiple end points are combined, are frequently used as primary outcome measures in randomized trials and are often associated with increased statistical efficiency. However, such measures may prove challenging for the interpretation of results. In this article, we examine the use of composite outcomes in major clinical trials, assess the arguments for and against them, and provide guidance on their application and reporting. To assess incidence and quality of reporting, we systematically reviewed the use of composite end points in clinical trials in Annals of Internal Medicine, BMJ, Circulation, Clinical Infectious Diseases, Journal of the American College of Cardiology, JAMA, Lancet, New England Journal of Medicine, and Stroke from 1997 through 2001 using a sensitive search strategy. We selected for review 167 original reports of randomized trials (with a total of 300 276 patients) that included a composite primary outcome that incorporated all-cause mortality. Sixty-three trials (38%) were neutral both for the primary end point and the mortality component. Sixty trials (36%) reported significant results for the primary outcome measure but not for the mortality component. Only 6 trials (4%) were significant for the mortality component but not for the primary composite outcome, whereas 19 trials (11%) were significant for both. Twenty-two trials (13%) were inadequately reported. Our review suggests that reporting of composite outcomes is generally inadequate, implying that the results apply to the individual components of the composite outcome rather than only to the overall composite. Current guidelines for the undertaking and reporting of clinical trials could be revised to reflect the common use of composite outcomes in clinical trials.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Definition, reporting, and interpretation of composite outcomes in clinical trials: systematic review

              Objective To study how composite outcomes, which have combined several components into a single measure, are defined, reported, and interpreted. Design Systematic review of parallel group randomised clinical trials published in 2008 reporting a binary composite outcome. Two independent observers extracted the data using a standardised data sheet, and two other observers, blinded to the results, selected the most important component. Results Of 40 included trials, 29 (73%) were about cardiovascular topics and 24 (60%) were entirely or partly industry funded. Composite outcomes had a median of three components (range 2–9). Death or cardiovascular death was the most important component in 33 trials (83%). Only one trial provided a good rationale for the choice of components. We judged that the components were not of similar importance in 28 trials (70%); in 20 of these, death was combined with hospital admission. Other major problems were change in the definition of the composite outcome between the abstract, methods, and results sections (13 trials); missing, ambiguous, or uninterpretable data (9 trials); and post hoc construction of composite outcomes (4 trials). Only 24 trials (60%) provided reliable estimates for both the composite and its components, and only six trials (15%) had components of similar, or possibly similar, clinical importance and provided reliable estimates. In 11 of 16 trials with a statistically significant composite, the abstract conclusion falsely implied that the effect applied also to the most important component. Conclusions The use of composite outcomes in trials is problematic. Components are often unreasonably combined, inconsistently defined, and inadequately reported. These problems will leave many readers confused, often with an exaggerated perception of how well interventions work.
                Bookmark

                Author and article information

                Contributors
                h.watt@imperial.ac.uk
                m.harris@imperial.ac.uk
                jane.noyes@bangor.ac.uk
                Rhiannon@whitres.co.uk
                z.hoare@bangor.ac.uk
                r.t.edwards@bangor.ac.uk
                andy.haines@lshtm.ac.uk
                Journal
                Trials
                Trials
                Trials
                BioMed Central (London )
                1745-6215
                21 March 2015
                21 March 2015
                2015
                : 16
                : 107
                Affiliations
                [ ]Department of Primary Care and Public Health, Imperial College London, Reynolds Building, St Dunstans Road, London, W6 8RP, England UK
                [ ]School of Social Sciences, Bangor University, Bangor, Wales UK
                [ ]London School of Hygiene and Tropical Medicine, London, England UK
                [ ]NWORTH Clinical Trials Unit, Bangor University, Bangor, Wales UK
                [ ]Centre for Health Economics and Medicine Evaluation, Bangor University, Bangor, Wales UK
                [ ]Whitaker Research Ltd., London, UK
                Article
                625
                10.1186/s13063-015-0625-1
                4417521
                25872945
                3a88a753-ecdd-44cc-849b-618093cff07a
                © Watt et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 9 May 2014
                : 2 March 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Medicine
                health services research,health impact assessment,delivery of health care,research outcomes

                Comments

                Comment on this article