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Proof of impact and pipeline planning: directions and challenges for social audit in the health sector

Overview of attention for article published in BMC Health Services Research, December 2011
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Title
Proof of impact and pipeline planning: directions and challenges for social audit in the health sector
Published in
BMC Health Services Research, December 2011
DOI 10.1186/1472-6963-11-s2-s16
Pubmed ID
Authors

Neil Andersson

Abstract

Social audits are typically observational studies, combining qualitative and quantitative uptake of evidence with consultative interpretation of results. This often falters on issues of causality because their cross-sectional design limits interpretation of time relations and separation out of other indirect associations.Social audits drawing on methods of randomised controlled cluster trials (RCCT) allow more certainty about causality. Randomisation means that exposure occurs independently of all events that precede it--it converts potential confounders and other covariates into random differences. In 2008, CIET social audits introduced randomisation of the knowledge translation component with subsequent measurement of impact in the changes introduced. This "proof of impact" generates an additional layer of evidence in a cost-effective way, providing implementation-ready solutions for planners.Pipeline planning is a social audit that incorporates stepped wedge RCCTs. From a listing of districts/communities as a sampling frame, individual entities (communities, towns, districts) are randomly assigned to waves of intervention. Measurement of the impact takes advantage of the delay occasioned by the reality that there are insufficient resources to implement everywhere at the same time. The impact in the first wave contrasts with the second wave, which in turn contrasts with a third wave, and so on until all have received the intervention. Provided care is taken to achieve reasonable balance in the random allocation of communities, towns or districts to the waves, the resulting analysis can be straightforward.Where there is sufficient management interest in and commitment to evidence, pipeline planning can be integrated in the roll-out of programmes where real time information can improve the pipeline. Not all interventions can be randomly allocated, however, and random differences can still distort measurement. Other issues include contamination of the subsequent waves, ambiguity of indicators, "participant effects" that result from lack of blinding and lack of placebos, ethics and, not least important, the skills to do pipeline planning correctly.

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Student > Master 7 18%
Student > Doctoral Student 5 13%
Researcher 3 8%
Student > Postgraduate 3 8%
Other 4 11%
Unknown 6 16%
Readers by discipline Count As %
Medicine and Dentistry 12 32%
Social Sciences 6 16%
Nursing and Health Professions 4 11%
Environmental Science 2 5%
Agricultural and Biological Sciences 1 3%
Other 6 16%
Unknown 7 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 March 2013.
All research outputs
#2,898,547
of 3,631,167 outputs
Outputs from BMC Health Services Research
#1,495
of 1,753 outputs
Outputs of similar age
#65,864
of 85,520 outputs
Outputs of similar age from BMC Health Services Research
#86
of 93 outputs
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