Imperial College London

Hilary Watt CStat FHEA MSc MA(Oxon) BA

Faculty of MedicineSchool of Public Health

Senior Teaching Fellow in Statistics
 
 
 
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Contact

 

+44 (0)20 7594 7451h.watt Website

 
 
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Location

 

322Reynolds BuildingCharing Cross Campus

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Summary

 

Publications

Citation

BibTex format

@article{Watt:2015:10.1186/s13063-015-0625-1,
author = {Watt, H and Harris, M and Noyes, J and Whitaker, R and Hoare, Z and Edwards, RT and Haines, A},
doi = {10.1186/s13063-015-0625-1},
journal = {Trials},
title = {Development of a composite outcome score for a complex intervention - measuring the impact of Community Health Workers},
url = {http://dx.doi.org/10.1186/s13063-015-0625-1},
volume = {16},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - 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 proce
AU - Watt,H
AU - Harris,M
AU - Noyes,J
AU - Whitaker,R
AU - Hoare,Z
AU - Edwards,RT
AU - Haines,A
DO - 10.1186/s13063-015-0625-1
PY - 2015///
SN - 1745-6215
TI - Development of a composite outcome score for a complex intervention - measuring the impact of Community Health Workers
T2 - Trials
UR - http://dx.doi.org/10.1186/s13063-015-0625-1
UR - http://hdl.handle.net/10044/1/23393
VL - 16
ER -