Using electronic health records for clinical trials: Where do we stand and where can we go?

Cord, Kimberly A. Mc; Hemkens, Lars G

doi:10.1503/cmaj.180841

Cited by 60 publications

(42 citation statements)

References 32 publications

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“…We provide a general framework with the various potential applications and challenges of using routinely collected data in different trial conduct phases elsewhere. 3,6 The author-reported costs could support the assumption that using routinely collected data for RCTs may promote cost reduction as long as the outcome data source is already established and is not a financial responsibility of the research endeavour. In the 3 trials in which the EHR infrastructure was well established and was merely redirected for use in the trials, 18,27,34 the cost per patient (median $44) was much lower than often-reported costs in traditional trials.…”

Section: Discussionmentioning

confidence: 98%

Current use and costs of electronic health records for clinical trial research: a descriptive study

Cord¹,

Ewald²,

Ladanie³

et al. 2019

cmajo

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R andomized controlled trials (RCTs) are the standard for evaluating benefits and harms of medical treatments. However, they are often time consuming and expensive to conduct, and some trials rely on strictly standardized research settings that may limit the generalizability of their results. 1 Electronic health records (EHRs)-electronic databases containing patient-level variables that are gathered during routine medical care (Appendix 1, available at www.cmajopen.ca/content/7/1/E23/suppl/DC1)-provide great potential for implementing large and pragmatic trials. 2,3 Randomized controlled trials could be integrated directly into routine care, offering almost perfect generalizability of their results. 4 Recently, the Patient-Centered Outcomes Research Institute awarded US$332 million to 28 pragmatic clinical studies, many of them using EHR infrastructures and many of them integrated in routine care. 5 Great debate regarding the potential barriers and limitations of EHR use in clinical research persists, and further details on these obstacles have been discussed elsewhere. 3,6 Briefly, the 2 largest direct advantages of using routinely

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Section: Discussionmentioning

confidence: 98%

Current use and costs of electronic health records for clinical trial research: a descriptive study

Cord¹,

Ewald²,

Ladanie³

et al. 2019

cmajo

Self Cite

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“…EHRs are often collected by centralised registries and audits (national or regional) for purposes other than clinical research to gather detailed information on specific diseases, treatments or populations. However, there are concerns, depending on the source, that data collected in this way may not be of appropriate detail or quality for use in clinical trials [ 6 ]. Access to EHRs by researchers usually requires a formal application to the data holder where specific criteria must be evidenced including compliance with information governance (IG) regulations and a clear purpose and legal basis for the data access.…”

Section: Introductionmentioning

confidence: 99%

Accessing routinely collected health data to improve clinical trials: recent experience of access

Macnair

Love

Murray

et al. 2021

Trials

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Background Routinely collected electronic health records (EHRs) have the potential to enhance randomised controlled trials (RCTs) by facilitating recruitment and follow-up. Despite this, current EHR use is minimal in UK RCTs, in part due to ongoing concerns about the utility (reliability, completeness, accuracy) and accessibility of the data. The aim of this manuscript is to document the process, timelines and challenges of the application process to help improve the service both for the applicants and data holders. Methods This is a qualitative paper providing a descriptive narrative from one UK clinical trials unit (MRC CTU at UCL) on the experience of two trial teams’ application process to access data from three large English national datasets: National Cancer Registration and Analysis Service (NCRAS), National Institute for Cardiovascular Outcomes Research (NICOR) and NHS Digital to establish themes for discussion. The underpinning reason for applying for the data was to compare EHRs with data collected through case report forms in two RCTs, Add-Aspirin (ISRCTN 74358648) and PATCH (ISRCTN 70406718). Results The Add-Aspirin trial, which had a pre-planned embedded sub-study to assess EHR, received data from NCRAS 13 months after the first application. In the PATCH trial, the decision to request data was made whilst the trial was recruiting. The study received data after 8 months from NICOR and 15 months for NHS Digital following final application submission. This concluded in May 2020. Prior to application submission, significant time and effort was needed particularly in relation to the PATCH trial where negotiations over consent and data linkage took many years. Conclusions Our experience demonstrates that data access can be a prolonged and complex process. This is compounded if multiple data sources are required for the same project. This needs to be factored in when planning to use EHR within RCTs and is best considered prior to conception of the trial. Data holders and researchers are endeavouring to simplify and streamline the application process so that the potential of EHR can be realised for clinical trials.

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“…This pragmatic design allows broad inclusion of dialysis centers and a large representative sample of patients that should yield highly generalizable findings (Figure 1). 44,45…”

Section: Methodsmentioning

confidence: 99%

“…This pragmatic design allows broad inclusion of dialysis centers and a large representative sample of patients that should yield highly generalizable findings (Figure 1). 44,45 Hemodialysis centers were randomized (1:1) to provide (1) a personalized temperature-reduced dialysate protocol (see "Intervention" section) or (2) a standard dialysate temperature of 36.5°C, which reflects usual practice at Ontario hemodialysis centers. Randomization with concealed allocation was conducted centrally on February 1, 2017, and centers were notified of their group allocation by the study team 2 months before the intervention start date.…”

Section: Study Design and Overviewmentioning

confidence: 99%

Major Outcomes With Personalized Dialysate TEMPerature (MyTEMP): Rationale and Design of a Pragmatic, Registry-Based, Cluster Randomized Controlled Trial

Al-Jaishi

McIntyre

Sontrop

et al. 2020

Can J Kidney Health Dis

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Background: Small randomized trials demonstrated that a lower compared with higher dialysate temperature reduced the average drop in intradialytic blood pressure. Some observational studies demonstrated that a lower compared with higher dialysate temperature was associated with a lower risk of all-cause mortality and cardiovascular mortality. There is now the need for a large randomized trial that compares the effect of a low vs high dialysate temperature on major cardiovascular outcomes. Objective: The purpose of this study is to test the effect of outpatient hemodialysis centers randomized to (1) a personalized temperature-reduced dialysate protocol or (2) a standard-temperature dialysate protocol for 4 years on cardiovascular-related death and hospitalizations. Design: The design of the study is a pragmatic, registry-based, open-label, cluster randomized controlled trial. Setting: Hemodialysis centers in Ontario, Canada, were randomized on February 1, 2017, for a trial start date of April 3, 2017, and end date of March 31, 2021. Participants: In total, 84 hemodialysis centers will care for approximately 15 500 patients and provide over 4 million dialysis sessions over a 4-year follow-up. Intervention: Hemodialysis centers were randomized (1:1) to provide (1) a personalized temperature-reduced dialysate protocol or (2) a standard-temperature dialysate protocol of 36.5°C. For the personalized protocol, nurses set the dialysate temperature between 0.5°C and 0.9°C below the patient’s predialysis body temperature for each dialysis session, to a minimum dialysate temperature of 35.5°C. Primary outcome: A composite of cardiovascular-related death or major cardiovascular-related hospitalization (a hospital admission with myocardial infarction, congestive heart failure, or ischemic stroke) captured in Ontario health care administrative databases. Planned primary analysis: The primary analysis will follow an intent-to-treat approach. The hazard ratio of time-to-first event will be estimated from a Cox model. Within-center correlation will be considered using a robust sandwich estimator. Observation time will be censored on the trial end date or when patients die from a noncardiovascular event. Trial Registration: www.clinicaltrials.gov ; identifier: NCT02628366.

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Using electronic health records for clinical trials: Where do we stand and where can we go?

Cited by 60 publications

References 32 publications

Current use and costs of electronic health records for clinical trial research: a descriptive study

Current use and costs of electronic health records for clinical trial research: a descriptive study

Accessing routinely collected health data to improve clinical trials: recent experience of access

Major Outcomes With Personalized Dialysate TEMPerature (MyTEMP): Rationale and Design of a Pragmatic, Registry-Based, Cluster Randomized Controlled Trial

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