'Rapid learning': Using real world data to improve clinical practice
Price, G
Price, G
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Abstract
Abstract text
Real world data – the information routinely collected
about patients over their care pathway – offers an
opportunity to provide evidence where Randomized
Controlled Trials (RCTs) are not practical. There is an
unmet need for such approaches in radiotherapy where
many changes to practice are not suited to RCTs meaning
there is often only limited assessment of their impact on
clinical outcomes. The quantity and quality of data
collected in modern radiotherapy mean it is ideally suited
to such analyses.
Furthermore, if real world data can be used to evaluate
the effect of changes to radiotherapy practice, it opens
the door to the use of iterative quality improvement
techniques to optimize treatments. In this approach, often
called rapid learning, a change to practice is made, its
effect evaluated, and this information used to refine the
next change before testing its effect again. It has the
potential to transform the way in which new technologies
and protocols are introduced into the radiotherapy clinic.
It is not yet, however, in widespread use.
This lecture will explore the promise of rapid learning and
consider some of the challenges to its routine
implementation. It will discuss the advantages and
disadvantages of working with real world data in different
ways, comparing the use of selective ‘simple trials’ and
Trials within Cohorts (TwiCs) to before-after and timeseries
analyses. As well as examining the trade-offs in the
evidence produced by different methodologies we will
discuss their practicalities, including consideration of
different patient consent models. Finally we will use a
case study of heart sparing in lung radiotherapy to discuss
the steps that need to be taken to move rapid learning into
the clinic.
Authors
Description
Date
2020
Publisher
Collections
Keywords
Type
Meetings and Proceedings
Citation
Price G. SP-0152: “Rapid learning”: Using real world data to improve clinical practice. Radiotherapy and Oncology . 2020 Nov;152:S71.