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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-03-21

AUTHORS

Hilary Watt, Matthew Harris, Jane Noyes, Rhiannon Whitaker, Zoe Hoare, Rhiannon Tudor Edwards, Andy Haines

ABSTRACT

BackgroundIn 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.MethodsWe 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.ResultsAssuming 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.ConclusionsThis 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. More... »

PAGES

107

References to SciGraph publications

  • 2009-01-16. The SAIL databank: linking multiple health and social care datasets in BMC MEDICAL INFORMATICS AND DECISION MAKING
  • 2013-06-11. Learning from the Brazilian Community Health Worker Model in North Wales in GLOBALIZATION AND HEALTH
  • 2012-06-21. Horizontal equity in health care utilization in Brazil, 1998–2008 in INTERNATIONAL JOURNAL FOR EQUITY IN HEALTH
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13063-015-0625-1

    DOI

    http://dx.doi.org/10.1186/s13063-015-0625-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1047888918

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25872945


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