title: Development of a composite outcome score for a complex intervention - measuring the impact of Community Health Workers.
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.
authors: Department of Primary Care and Public Health, Imperial College London, Reynolds Building, St Dunstans Road, London, W6 8RP, , England, UK. h.watt@imperial.ac.uk.
authors: Hilary
authors: H
authors: Watt
authors: Department of Primary Care and Public Health, Imperial College London, Reynolds Building, St Dunstans Road, London, W6 8RP, , England, UK. m.harris@imperial.ac.uk.
authors: Matthew
authors: M
authors: Harris
authors: School of Social Sciences, Bangor University, Bangor, Wales, UK. jane.noyes@bangor.ac.uk.
authors: Jane
authors: J
authors: Noyes
authors: Whitaker Research Ltd., London, UK. Rhiannon@whitres.co.uk.
authors: Rhiannon
authors: R
authors: Whitaker
authors: NWORTH Clinical Trials Unit, Bangor University, Bangor, Wales, UK. z.hoare@bangor.ac.uk.
authors: Zoe
authors: Z
authors: Hoare
authors: Centre for Health Economics and Medicine Evaluation, Bangor University, Bangor, Wales, UK. r.t.edwards@bangor.ac.uk.
authors: Rhiannon Tudor
authors: RT
authors: Edwards
authors: London School of Hygiene and Tropical Medicine, London, England, UK. andy.haines@lshtm.ac.uk.
authors: Andy
authors: A
authors: Haines
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003153:Community Health Services / Q000706:statistics & numerical data*; D003150:Community Health Workers / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003695:Delivery of Health Care; D004739:England; D005191:Family Characteristics; D005260:Female; D006295:Health Resources / Q000706:statistics & numerical data*; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010342:Patient Acceptance of Health Care; D011247:Pregnancy; D011320:Primary Health Care / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018401:Sample Size; D012737:Sex Factors; D014852:Wales; D000078329:Workforce; D055815:Young Adult