TY - JOUR
T1 - Integrated rapid-cycle comparative effectiveness trials using flexible point of care randomisation in electronic health record systems
AU - Wilson, Matthew G.
AU - Palmer, Edward
AU - Asselbergs, Folkert W.
AU - Harris, Steve K.
N1 - Funding Information: MGW is funded through a doctoral training program award from the Medical Research Council (Grant Number: MR/N013867/1). FWA and SKH are supported by University College London Hospitals National Institute for Health Research Biomedical Research Centre. SKH is supported by a Health Foundation Improvement Science Fellowship. EP is supported through an academic clinical lectureship funded by the National Institute for Health Research. Publisher Copyright: © 2022
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Whilst the Randomised Controlled Trial remains the gold standard for deriving robust causal estimates of treatment efficacy, too often a traditional design proves prohibitively expensive or cumbersome when it comes to assessing questions regarding the comparative effectiveness of routinely used treatments. As a result, patients experience variation in practice as clinicians lack the evidence needed to personalise treatments effectively. This variation may be classified as unwarranted, where existing evidence is ignored, or legitimate where in the absence of evidence, clinicians rely on experience, expert opinion, and inferred principles from basic science to make decisions. We argue that within the right ethical and technological framework, legitimate variation can be transformed into a mechanism for evidence generation and learning. Learning Health Systems which harness existing variation in practice, represent a novel approach for generating evidence from everyday clinical practice. The development of these systems has gained traction due to the increased availability of modern Electronic Health Record Systems. However, despite their promise, overcoming hurdles to successfully integrating clinical trials within Learning Health Systems has proven challenging. This article describes the origins of integrated clinical trials and explores two main barriers to their further implementation - how best to obtain informed consent from patients to participate in routine comparative effectiveness research, and how to automate and integrate randomisation into a clinical workflow. Having described these barriers, we present a potential solution in the form of a research pipeline using a novel form of flexible point-of-care randomisation to allow clinicians and patients to participate in studies where there is clinical equipoise.
AB - Whilst the Randomised Controlled Trial remains the gold standard for deriving robust causal estimates of treatment efficacy, too often a traditional design proves prohibitively expensive or cumbersome when it comes to assessing questions regarding the comparative effectiveness of routinely used treatments. As a result, patients experience variation in practice as clinicians lack the evidence needed to personalise treatments effectively. This variation may be classified as unwarranted, where existing evidence is ignored, or legitimate where in the absence of evidence, clinicians rely on experience, expert opinion, and inferred principles from basic science to make decisions. We argue that within the right ethical and technological framework, legitimate variation can be transformed into a mechanism for evidence generation and learning. Learning Health Systems which harness existing variation in practice, represent a novel approach for generating evidence from everyday clinical practice. The development of these systems has gained traction due to the increased availability of modern Electronic Health Record Systems. However, despite their promise, overcoming hurdles to successfully integrating clinical trials within Learning Health Systems has proven challenging. This article describes the origins of integrated clinical trials and explores two main barriers to their further implementation - how best to obtain informed consent from patients to participate in routine comparative effectiveness research, and how to automate and integrate randomisation into a clinical workflow. Having described these barriers, we present a potential solution in the form of a research pipeline using a novel form of flexible point-of-care randomisation to allow clinicians and patients to participate in studies where there is clinical equipoise.
KW - Clinically integrated trials
KW - Comparative effectiveness research
KW - Electronic health record trials
KW - Learning health systems
KW - Point of care randomisation
UR - http://www.scopus.com/inward/record.url?scp=85144328984&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.jbi.2022.104273
DO - https://doi.org/10.1016/j.jbi.2022.104273
M3 - Comment/Letter to the editor
C2 - 36535604
SN - 1532-0464
VL - 137
JO - Journal of biomedical informatics
JF - Journal of biomedical informatics
M1 - 104273
ER -