Exploring the use of routine health data in improving the efficiency of randomised implementation trials

PROJECT STATUS: Closed
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START DATE AND DURATION: January 2022 - January 2024
Summary

Randomised implementation trials are designed to evaluate the effects of implementation strategies on implementation outcomes. Routine healthcare data are increasingly used in randomised controlled trials to support participant identification, outcome assessment, and intervention delivery. However, the role and impact of routine healthcare data within implementation trials remain underexplored, and there is a lack of clarity around how such data may influence trial efficiency. In addition, there is a heterogeneity in understanding “efficiency” within the trial context.

Key Findings
The majority of implementation trials extracted data from electronic health records, and used routine data for outcome ascertainment.
Trial efficiency is multifaceted, encompassing four theoretical constructs scientific, operational, statistical, and economic which are operationalised within five essential building blocks: trial design, trial process, infrastructure, superstructure, and stakeholders.
Common facilitators of using routine data in improving implementation trials’ efficiency included sufficient IT and hardware capacity, relatively low cost, centralised regulatory approval, and strong collaboration and partnerships. Common barriers included administrative complexity, redundant bureaucratic processes, and challenges with data sharing requirements. Data quality serves as both a facilitator and a barrier.
The potential of routine healthcare data to enhance implementation trial efficiency is highly context-specific. This research contributes to the theoretical understanding of trial efficiency and provides a set of recommendations to optimise the use of routine data in future implementation trials, with the ultimate goal of increasing the uptake of evidence-based interventions into routine healthcare practice.
IMPACTS
The potential of routine healthcare data to enhance implementation trial efficiency is highly context-specific. This research contributes to the theoretical understanding of trial efficiency and provides a set of recommendations to optimise the use of routine data in future implementation trials, with the ultimate goal of increasing the uptake of evidence-based interventions into routine healthcare practice.
Partners & Collaborators

Queen Mary University of London (QMUL)

The University of Edinburgh

Lead Investigator
Charis Xuan Xie (QMUL)
Clare Relton (Primary Supervisor, QMUL)
Investigating Team
Clare Relton (QMUL)
Sandra Eldridge (QMUL)
Hilary Pinnock (Edinburgh)
Anna De Simoni (QMUL)
Resources
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