Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials

Matthew R Sydes; Macey L Murray; Saiam Ahmed; Sophia Apostolidou; Judith M Bliss; Claire Bloomfield; Rebecca Cannings-John; James Carpenter; Tim Clayton; Madeleine Clout; Rebecca Cosgriff; Amanda J. Farrin; Aleksandra Gentry-Maharaj; Duncan C. Gilbert; Charlie Harper; Nicholas D. James; Ruth E. Langley; Sarah Lessels; Fiona Lugg-Widger; Isla S. Mackenzie; Marion Mafham; Usha Menon; Harriet Mintz; Heather Pinches; Michael Robling; Alexandra Wright-Hughes; Victoria Yorke-Edwards; Sharon B. Love

doi:10.1016/j.cct.2024.107514

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials

Matthew R Sydes (Lead / Corresponding author), Macey L Murray, Saiam Ahmed, Sophia Apostolidou, Judith M Bliss, Claire Bloomfield, Rebecca Cannings-John, James Carpenter, Tim Clayton, Madeleine Clout, Rebecca Cosgriff, Amanda J. Farrin, Aleksandra Gentry-Maharaj, Duncan C. Gilbert, Charlie Harper, Nicholas D. James, Ruth E. Langley, Sarah Lessels, Fiona Lugg-Widger, Isla S. MackenzieMarion Mafham, Usha Menon, Harriet Mintz, Heather Pinches, Michael Robling, Alexandra Wright-Hughes, Victoria Yorke-Edwards, Sharon B. Love

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Abstract

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.

METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.

DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.

Original language	English
Article number	107514
Number of pages	8
Journal	Contemporary Clinical Trials
Volume	141
Early online date	26 Mar 2024
DOIs	https://doi.org/10.1016/j.cct.2024.107514
Publication status	Published - Jun 2024

Keywords

Healthcare systems data
Health policy
Routinely-collected healthcare data
Electronic health records
Real world data
Routinely-collected data
RCTs
Data utility
Data utility comparison studies
DUCkS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Sydes, M. R., Murray, M. L., Ahmed, S., Apostolidou, S., Bliss, J. M., Bloomfield, C., Cannings-John, R., Carpenter, J., Clayton, T., Clout, M., Cosgriff, R., Farrin, A. J., Gentry-Maharaj, A., Gilbert, D. C., Harper, C., James, N. D., Langley, R. E., Lessels, S., Lugg-Widger, F., ... Love, S. B. (2024). Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials. Contemporary Clinical Trials, 141, Article 107514. https://doi.org/10.1016/j.cct.2024.107514

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title = "Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials",

abstract = "BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. {"}Data Utility Comparison Studies{"} (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at {"}patient-level{"} or {"}trial-level{"}, depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.",

keywords = "Healthcare systems data, Health policy, Routinely-collected healthcare data, Electronic health records, Real world data, Routinely-collected data, RCTs, Data utility, Data utility comparison studies, DUCkS",

author = "Sydes, {Matthew R} and Murray, {Macey L} and Saiam Ahmed and Sophia Apostolidou and Bliss, {Judith M} and Claire Bloomfield and Rebecca Cannings-John and James Carpenter and Tim Clayton and Madeleine Clout and Rebecca Cosgriff and Farrin, {Amanda J.} and Aleksandra Gentry-Maharaj and Gilbert, {Duncan C.} and Charlie Harper and James, {Nicholas D.} and Langley, {Ruth E.} and Sarah Lessels and Fiona Lugg-Widger and Mackenzie, {Isla S.} and Marion Mafham and Usha Menon and Harriet Mintz and Heather Pinches and Michael Robling and Alexandra Wright-Hughes and Victoria Yorke-Edwards and Love, {Sharon B.}",

note = "Publisher Copyright: {\textcopyright} 2024 The Authors",

year = "2024",

month = jun,

doi = "10.1016/j.cct.2024.107514",

language = "English",

volume = "141",

journal = "Contemporary Clinical Trials",

issn = "1551-7144",

publisher = "Elsevier",

}

Sydes, MR, Murray, ML, Ahmed, S, Apostolidou, S, Bliss, JM, Bloomfield, C, Cannings-John, R, Carpenter, J, Clayton, T, Clout, M, Cosgriff, R, Farrin, AJ, Gentry-Maharaj, A, Gilbert, DC, Harper, C, James, ND, Langley, RE, Lessels, S, Lugg-Widger, F, Mackenzie, IS, Mafham, M, Menon, U, Mintz, H, Pinches, H, Robling, M, Wright-Hughes, A, Yorke-Edwards, V & Love, SB 2024, 'Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials', Contemporary Clinical Trials, vol. 141, 107514. https://doi.org/10.1016/j.cct.2024.107514

TY - JOUR

T1 - Getting our ducks in a row

T2 - The need for data utility comparisons of healthcare systems data for clinical trials

AU - Sydes, Matthew R

AU - Murray, Macey L

AU - Ahmed, Saiam

AU - Apostolidou, Sophia

AU - Bliss, Judith M

AU - Bloomfield, Claire

AU - Cannings-John, Rebecca

AU - Carpenter, James

AU - Clayton, Tim

AU - Clout, Madeleine

AU - Cosgriff, Rebecca

AU - Farrin, Amanda J.

AU - Gentry-Maharaj, Aleksandra

AU - Gilbert, Duncan C.

AU - Harper, Charlie

AU - James, Nicholas D.

AU - Langley, Ruth E.

AU - Lessels, Sarah

AU - Lugg-Widger, Fiona

AU - Mackenzie, Isla S.

AU - Mafham, Marion

AU - Menon, Usha

AU - Mintz, Harriet

AU - Pinches, Heather

AU - Robling, Michael

AU - Wright-Hughes, Alexandra

AU - Yorke-Edwards, Victoria

AU - Love, Sharon B.

PY - 2024/6

Y1 - 2024/6

N2 - BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.

AB - BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.

KW - Healthcare systems data

KW - Health policy

KW - Routinely-collected healthcare data

KW - Electronic health records

KW - Real world data

KW - Routinely-collected data

KW - RCTs

KW - Data utility

KW - Data utility comparison studies

KW - DUCkS

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U2 - 10.1016/j.cct.2024.107514

DO - 10.1016/j.cct.2024.107514

M3 - Article

C2 - 38537901

SN - 1551-7144

VL - 141

JO - Contemporary Clinical Trials

JF - Contemporary Clinical Trials

M1 - 107514

ER -

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials

Abstract

Keywords

UN SDGs

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