Collaborating to combat the inefficiency of randomised trials Heidi - - PowerPoint PPT Presentation

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Collaborating to combat the inefficiency of randomised trials Heidi - - PowerPoint PPT Presentation

Collaborating to combat the inefficiency of randomised trials Heidi Gardner @heidirgardner heidi.gardner.10@aberdeen.ac.uk Health Services Research Unit University of Aberdeen HSRU is funded by the Chief Scientist Office of the Scottish


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HSRU is funded by the Chief Scientist Office of the Scottish Government Health

  • Directorates. The author accepts full responsibility for this talk.

Health Services Research Unit University of Aberdeen

Collaborating to combat the inefficiency of randomised trials

Heidi Gardner

@heidirgardner heidi.gardner.10@aberdeen.ac.uk

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  • Financial efficiency: use of resources – technology, staff
  • Scientific efficiency: establishing need, the ‘right’ question, optimal

design

  • Regulatory efficiency: the ‘amendment cascade’, repetition in

approvals documentation

  • Integration of knowledge: at the beginning – PPI, multiple

stakeholders, at the end – dissemination to the research community and healthcare providers, public engagement

  • Process efficiency: recruitment, retention, data collection

What is an efficient trial?

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  • Approximately 25,000 trial results published every year1
  • The number of things we measure is increasing2
  • Data collection takes time and effort – patient burden as well as staff
  • Data management accounts for a lot of work; one estimate is that
  • ver a third of hours spent on a trial is spent by Data Managers3
  • 1. Bastian et al. PLoS Med. 2010; 7: e1000326
  • 2. Getz et al. Am J Ther. 2008; 15: 450-7
  • 3. O’Leary et al. Clinical Trials. 2013; 10: 624-32

Trials = Data

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Are these data informing decisions?

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Are these data informing decisions?

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  • Primary/secondary outcome data, health economics outcomes,

process outcomes, compliance data, participant identification, eligibility, demographics, safety data, data management items

  • Where do we invest our time when collecting outcome data?
  • Do we spend most of it on our most important outcomes?
  • Project led by Prof Shaun Treweek, Aberdeen and David Pickles,

Leeds

What are we collecting and why?

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Ongoing international trial: Time

3% on primary 85% on secondaries 12% on biomarkers Primary = 81 hours Biomarker = 324 hours Secondaries = 2265 hours Total = 2670 hours A working year? ~1725 hours

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Ongoing international trial: Cost

3% on primary 85% on secondaries 12% on biomarkers Primary = £2,106 Biomarker = £8,424 Secondaries = £58,890 Total = £69,420 A research nurse in Grampian costs around £26 per hour

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  • Random selection of 115 protocols for publicly funded RCTs

published between 2010 and 2014 (~24 per year)

  • Primary and secondary outcomes extracted from protocols
  • Data on time to complete each outcome sought from protocol,

corresponding authors, or Trial Managers familiar with the outcome

  • We’ve looked at 20 trials so far

Let’s look at a bigger sample

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A sample of 5 trials

Hours Trial ID

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A sample of 5 trials

Hours Trial ID

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..and for 20 trials

Hours Trial ID

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..and for 20 trials

Hours Trial ID

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Primaries and secondaries: Median time and cost

14% on primary 86% on secondaries Primary 68 hours / £1,785 Secondaries 417 hours / £10,946 Total 485 hours / £12,731

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Median ratio of time spent on primary vs secondary outcomes

A ratio to remember

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  • Collaborative project
  • Identify processes
  • Collate what we know
  • Spot gaps
  • Do work to fill those gaps
  • Disseminate

What is Trial Forge?

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Special thanks to Prof Shaun Treweek, Aberdeen & David Pickles, Leeds

HSRU is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The author accepts full responsibility for this talk.

Thank you!

@Trial_Forge

www.trialforge.org