Skip to main content
Top
Published in: Trials 1/2015

Open Access 01-12-2015 | Research

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

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

Published in: Trials | Issue 1/2015

Login to get access

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.
Literature
3.
go back to reference Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655.CrossRefPubMedPubMedCentral Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655.CrossRefPubMedPubMedCentral
4.
go back to reference Betty R, Kirkwood JAS. Essential medical statistics. 2nd ed. Oxford, UK: Blackwell Published Ltd; 2003. Betty R, Kirkwood JAS. Essential medical statistics. 2nd ed. Oxford, UK: Blackwell Published Ltd; 2003.
5.
go back to reference Huang P, Goetz CG, Woolson RF, Tilley B, Kerr D, Palesch Y, et al. Using global statistical tests in long-term Parkinson’s disease clinical trials. Mov Disord. 2009;24(12):1732–9.CrossRefPubMedPubMedCentral Huang P, Goetz CG, Woolson RF, Tilley B, Kerr D, Palesch Y, et al. Using global statistical tests in long-term Parkinson’s disease clinical trials. Mov Disord. 2009;24(12):1732–9.CrossRefPubMedPubMedCentral
6.
go back to reference Tilley BC, Marler J, Geller NL, Lu M, Legler J, Brott T, et al. Use of a global test for multiple outcomes in stroke trials with application to the national institute of neurological disorders and stroke t-PA stroke trial. Stroke. 1996;27(11):2136–42.CrossRefPubMed Tilley BC, Marler J, Geller NL, Lu M, Legler J, Brott T, et al. Use of a global test for multiple outcomes in stroke trials with application to the national institute of neurological disorders and stroke t-PA stroke trial. Stroke. 1996;27(11):2136–42.CrossRefPubMed
7.
go back to reference Mayo NE, Scott S. Evaluating a complex intervention with a single outcome may not be a good idea: an example from a randomized trial of stroke case management. Age Aging. 2011;40:718–24.CrossRef Mayo NE, Scott S. Evaluating a complex intervention with a single outcome may not be a good idea: an example from a randomized trial of stroke case management. Age Aging. 2011;40:718–24.CrossRef
8.
go back to reference Cordoba G, Schwartz L, Woloshin S, Bae H, Gøtzsche PC. Definition, reporting, and interpretation of composite outcomes in clinical trials: systematic review. BMJ. 2010;341:c3920.CrossRefPubMedPubMedCentral Cordoba G, Schwartz L, Woloshin S, Bae H, Gøtzsche PC. Definition, reporting, and interpretation of composite outcomes in clinical trials: systematic review. BMJ. 2010;341:c3920.CrossRefPubMedPubMedCentral
9.
go back to reference Freemantle N, Calvert M, Wood J, Eastaugh J, Griffin C. Composite outcomes in randomised trials: greater precision but with greater uncertainty? JAMA. 2003;289(19):2554–9.CrossRefPubMed Freemantle N, Calvert M, Wood J, Eastaugh J, Griffin C. Composite outcomes in randomised trials: greater precision but with greater uncertainty? JAMA. 2003;289(19):2554–9.CrossRefPubMed
13.
go back to reference Harris M. Integrating primary care and public health - learning from the Brazilian way. London J Prim Care. 2012;4:126–32.CrossRef Harris M. Integrating primary care and public health - learning from the Brazilian way. London J Prim Care. 2012;4:126–32.CrossRef
15.
go back to reference Macinko J, Marinho de Souza F, Guanais FC, da Silva Simões CC. Going to scale with community-based primary care: an analysis of the Family Health Programme and Infant Mortality in Brazil, 1999–2004. Soc Sci Med. 2007;65(10):2070–80.CrossRefPubMed Macinko J, Marinho de Souza F, Guanais FC, da Silva Simões CC. Going to scale with community-based primary care: an analysis of the Family Health Programme and Infant Mortality in Brazil, 1999–2004. Soc Sci Med. 2007;65(10):2070–80.CrossRefPubMed
16.
go back to reference Macinko J, Dourado I, Aquino R, Bonolo Pde F, Lima-Costa MF, Medina MG, et al. Major expansion of primary care in brazil linked to decline in unnecessary hospitalization. Health Aff. 2010;29(12):2149–60.CrossRef Macinko J, Dourado I, Aquino R, Bonolo Pde F, Lima-Costa MF, Medina MG, et al. Major expansion of primary care in brazil linked to decline in unnecessary hospitalization. Health Aff. 2010;29(12):2149–60.CrossRef
17.
go back to reference Guanais F, Macinko J. The health effects of decentralizing primary care in brazil. Health Aff. 2009;28:4.CrossRef Guanais F, Macinko J. The health effects of decentralizing primary care in brazil. Health Aff. 2009;28:4.CrossRef
19.
go back to reference Rocha A, Soares R. Evaluating the impact of community-based health interventions: evidence from Brazil’s family health program. Health Econ. 2010;19:126–58.CrossRefPubMed Rocha A, Soares R. Evaluating the impact of community-based health interventions: evidence from Brazil’s family health program. Health Econ. 2010;19:126–58.CrossRefPubMed
20.
go back to reference Rasella D, Harhay MO, Pamponet ML, Aquino R, Barreto ML. Impact of primary health care on mortality from heart and cerebrovascular diseases in Brazil: a nationwide analysis of longitudinal data. BMJ. 2014;348:g4014. doi:10.1136/bmj.g4014.CrossRef Rasella D, Harhay MO, Pamponet ML, Aquino R, Barreto ML. Impact of primary health care on mortality from heart and cerebrovascular diseases in Brazil: a nationwide analysis of longitudinal data. BMJ. 2014;348:g4014. doi:10.​1136/​bmj.​g4014.CrossRef
21.
go back to reference Johnson C, Noyes J, Haines A, Thomas K, Stockport C, Ribas AN, et al. Learning from the Brazilian community health worker model in north wales. Glob Health. 2013;9:25.CrossRef Johnson C, Noyes J, Haines A, Thomas K, Stockport C, Ribas AN, et al. Learning from the Brazilian community health worker model in north wales. Glob Health. 2013;9:25.CrossRef
27.
go back to reference ONS 2012a Civil partnerships five years on [report containing data on the Internet]. Office for National Statistics. 2012. Available from: file://icnas3.cc.ic.ac.uk/hwatt/downloads/13poptrends145ros_tcm77-230895.pdf. Accessed 30 March 2015. ONS 2012a Civil partnerships five years on [report containing data on the Internet]. Office for National Statistics. 2012. Available from: file://icnas3.cc.ic.ac.uk/hwatt/downloads/13poptrends145ros_tcm77-230895.pdf. Accessed 30 March 2015.
33.
go back to reference The National Chlamydia Screening Programme. The National Chlamydia Screening Programme in England: core requirements. 4th edition. 2008 The National Chlamydia Screening Programme. The National Chlamydia Screening Programme in England: core requirements. 4th edition. 2008
34.
go back to reference Department of Health. The Green Book: Influenza. Chapter 19. Department of Health. The Green Book: Influenza. Chapter 19.
35.
go back to reference Department of Health. The Green Book: Immunisation Schedule. Chapter 11. Department of Health. The Green Book: Immunisation Schedule. Chapter 11.
36.
go back to reference Department of Health. The Green Book: HPV. Chapter 18a. Department of Health. The Green Book: HPV. Chapter 18a.
37.
go back to reference Health and Social Care Information Centre: Statistics on Smoking in England, 2008. The NHS Information Centre. Health and Social Care Information Centre: Statistics on Smoking in England, 2008. The NHS Information Centre.
41.
go back to reference Viswanathan M, Kraschnewski J, Nishikawa B, Morgan LC, Thieda P, Honeycutt A, et al. Outcomes of Community Health Worker Interventions Agency for Healthcare Research and Quality. Evidence Report/Technology Assessment Number 18. June 2009 Viswanathan M, Kraschnewski J, Nishikawa B, Morgan LC, Thieda P, Honeycutt A, et al. Outcomes of Community Health Worker Interventions Agency for Healthcare Research and Quality. Evidence Report/Technology Assessment Number 18. June 2009
42.
go back to reference Prieto-Merino D, Smeeth L, van Staa T, Roberts I. Dangers of non-specific composite outcome measures in clinical trials. BMJ. 2013;347:f6782.CrossRefPubMed Prieto-Merino D, Smeeth L, van Staa T, Roberts I. Dangers of non-specific composite outcome measures in clinical trials. BMJ. 2013;347:f6782.CrossRefPubMed
43.
go back to reference Lyons R, Jones K, John G, Brooks CJ, Verplancke JP, Ford DV, et al. The SAIL databank: linking multiple health and social care datasets. BMC Med Inf Decis Mak. 2009;9:3. doi:10.1186/1472-6947-9-3.CrossRef Lyons R, Jones K, John G, Brooks CJ, Verplancke JP, Ford DV, et al. The SAIL databank: linking multiple health and social care datasets. BMC Med Inf Decis Mak. 2009;9:3. doi:10.1186/1472-6947-9-3.CrossRef
Metadata
Title
Development of a composite outcome score for a complex intervention - measuring the impact of Community Health Workers
Authors
Hilary Watt
Matthew Harris
Jane Noyes
Rhiannon Whitaker
Zoe Hoare
Rhiannon Tudor Edwards
Andy Haines
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Trials / Issue 1/2015
Electronic ISSN: 1745-6215
DOI
https://doi.org/10.1186/s13063-015-0625-1

Other articles of this Issue 1/2015

Trials 1/2015 Go to the issue