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Routinely collected data for randomized trials: promises, barriers, and implications
by
Mc Cord, Kimberly A.
, Hemkens, Lars G.
, Ioannidis, John P. A.
, Strech, Daniel
, Treweek, Shaun
, Al-Shahi Salman, Rustam
, Gardner, Heidi
, Whiteley, William
in
Alliances
/ Analysis
/ Biomedicine
/ Clinical epidemiology
/ Clinical trials
/ Consent
/ Cost control
/ Cost reduction
/ Data Collection
/ Drug therapy
/ Electronic health records
/ Epidemiology
/ Ethics, Research
/ Evidence-based medicine
/ Funding
/ Health Sciences
/ Humans
/ Information management
/ Infrastructure
/ Medicine
/ Medicine & Public Health
/ Patients
/ Randomized Controlled Trials as Topic - economics
/ Rare diseases
/ Registries
/ Research Design
/ Review
/ Routinely collected health data
/ Statistics for Life Sciences
/ Trials
2018
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Routinely collected data for randomized trials: promises, barriers, and implications
by
Mc Cord, Kimberly A.
, Hemkens, Lars G.
, Ioannidis, John P. A.
, Strech, Daniel
, Treweek, Shaun
, Al-Shahi Salman, Rustam
, Gardner, Heidi
, Whiteley, William
in
Alliances
/ Analysis
/ Biomedicine
/ Clinical epidemiology
/ Clinical trials
/ Consent
/ Cost control
/ Cost reduction
/ Data Collection
/ Drug therapy
/ Electronic health records
/ Epidemiology
/ Ethics, Research
/ Evidence-based medicine
/ Funding
/ Health Sciences
/ Humans
/ Information management
/ Infrastructure
/ Medicine
/ Medicine & Public Health
/ Patients
/ Randomized Controlled Trials as Topic - economics
/ Rare diseases
/ Registries
/ Research Design
/ Review
/ Routinely collected health data
/ Statistics for Life Sciences
/ Trials
2018
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Do you wish to request the book?
Routinely collected data for randomized trials: promises, barriers, and implications
by
Mc Cord, Kimberly A.
, Hemkens, Lars G.
, Ioannidis, John P. A.
, Strech, Daniel
, Treweek, Shaun
, Al-Shahi Salman, Rustam
, Gardner, Heidi
, Whiteley, William
in
Alliances
/ Analysis
/ Biomedicine
/ Clinical epidemiology
/ Clinical trials
/ Consent
/ Cost control
/ Cost reduction
/ Data Collection
/ Drug therapy
/ Electronic health records
/ Epidemiology
/ Ethics, Research
/ Evidence-based medicine
/ Funding
/ Health Sciences
/ Humans
/ Information management
/ Infrastructure
/ Medicine
/ Medicine & Public Health
/ Patients
/ Randomized Controlled Trials as Topic - economics
/ Rare diseases
/ Registries
/ Research Design
/ Review
/ Routinely collected health data
/ Statistics for Life Sciences
/ Trials
2018
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Routinely collected data for randomized trials: promises, barriers, and implications
Journal Article
Routinely collected data for randomized trials: promises, barriers, and implications
2018
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Overview
Background
Routinely collected health data (RCD) are increasingly used for randomized controlled trials (RCTs). This can provide three major benefits: increasing value through better feasibility (reducing costs, time, and resources), expanding the research agenda (performing trials for research questions otherwise not amenable to trials), and offering novel design and data collection options (e.g., point-of-care trials and other designs directly embedded in routine care). However, numerous hurdles and barriers must be considered pertaining to regulatory, ethical, and data aspects, as well as the costs of setting up the RCD infrastructure. Methodological considerations may be different from those in traditional RCTs: RCD are often collected by individuals not involved in the study and who are therefore blinded to the allocation of trial participants. Another consideration is that RCD trials may lead to greater misclassification biases or dilution effects, although these may be offset by randomization and larger sample sizes. Finally, valuable insights into external validity may be provided when using RCD because it allows pragmatic trials to be performed.
Methods
We provide an overview of the promises, challenges, and potential barriers, methodological implications, and research needs regarding RCD for RCTs.
Results
RCD have substantial potential for improving the conduct and reducing the costs of RCTs, but a multidisciplinary approach is essential to address emerging practical barriers and methodological implications.
Conclusions
Future research should be directed toward such issues and specifically focus on data quality validation, alternative research designs and how they affect outcome assessment, and aspects of reporting and transparency.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
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