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Embedded point of care randomisation for evaluating comparative effectiveness questions: PROSPECTOR-critical care
Matthew G Wilson1, Folkert W Asselbergs2,3, Ruben Miguel4
1Institute of Health Informatics, University College London, London, UK matthew.wilson8@nhs.net.
This study explores using computer prompts for flexible randomization in clinical trials, comparing two designs and consent models for magnesium supplementation in critical care patients.
Area of Science:
- Clinical Trials
- Health Informatics
- Comparative Effectiveness Research
Background:
- Routinely administered treatments often lack evidence of effectiveness, leading to variable patient care.
- Standard randomized controlled trials are not well-suited for comparing routine treatment strategies.
- Integrating clinical trial infrastructure into electronic health records offers potential for large-scale, cost-effective treatment comparisons.
Purpose of the Study:
- To investigate the feasibility of using computer prompts for flexible randomization at the point of clinical decision-making.
- To compare the effectiveness of two electronic randomization prompt designs.
- To explore patient and clinician acceptability of different consent models for comparative effectiveness research.
Main Methods:
- A single-center, mixed-methods feasibility study.
- Recruitment of 50 patients undergoing elective surgery requiring postoperative critical care admission.
- Randomization to either 'Nudge' or 'Preference' prompt designs and liberal or restrictive magnesium supplementation.
Main Results:
- Primary outcome: proportion of prompts leading to successful randomization (compliance with magnesium strategy).
- Secondary outcomes: acceptability of prompt designs to clinicians.
- Secondary outcomes: acceptability of pre-emptive and opt-out consent models to patients.
Conclusions:
- Feasibility will be judged by successful randomization rates and acceptability of prompt and consent models.
- This study aims to inform future large-scale comparative effectiveness research integrated with electronic health records.
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