Evidence map›Paper›PMID 37658391›Full record

Trial reportTrials2023

Optimizing data integration in trials that use EHR data: lessons learned from a multi-center randomized clinical trial.

Sudha R Raman, Laura G Qualls, Bradley G Hammill, Adam J Nelson, Ester Kim Nilles, Keith Marsolo, Emily C O'Brien

Abstract readRandomized Controlled TrialMulticenter StudyLetter
In one paragraph

Trial report in Trials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sudha R RamanDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA. sudha.raman@duke.edu.ORCID http://orcid.org/0000-0001-8659-189X
Laura G QuallsDuke Clinical Research Institute, Durham, NC, USA.
Bradley G HammillDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.
Adam J NelsonDuke Clinical Research Institute, Durham, NC, USA.
Ester Kim NillesDuke Clinical Research Institute, Durham, NC, USA.
Keith MarsoloDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.
Emily C O'BrienDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite great promise, trials that ascertain patient clinical data from electronic health records (EHR), referred to here as "EHR-sourced" trials, are limited by uncertainty about how existing trial sites and infrastructure can be best used to operationalize study goals. Evidence is needed to support the practical use of EHRs in contemporary clinical trial settings. MAIN TEXT: We describe a demonstration project that used EHR data to complement data collected for a contemporary multi-center pharmaceutical industry outcomes trial, and how a central coordinating center supported participating sites through the technical, governance, and operational aspects of this type of activity. We discuss operational considerations related to site selection, data extraction, site performance, and data transfer and quality review, and we outline challenges and lessons learned. We surveyed potential sites and used their responses to assess feasibility, determine the potential capabilities of sites and choose an appropriate data extraction strategy. We designed a flexible, multimodal approach for data extraction, enabling each site to either leverage an existing data source, create a new research datamart, or send all data to the central coordinating center to produce the requisite data elements. We evaluated site performance, as reflected by the speed of contracting and IRB approval, total patients enrolled, enrollment yield, data quality, and compared performance by data collection strategy.

conclusionWhile broadening the type of sites able to participate in EHR-sourced trials may lead to greater generalizability and improved enrollment, sites with fewer technical resources may require additional support to participate. Central coordinating center support is essential to facilitate the execution of operational processes. Future work should focus on sharing lessons learned and creating reusable tools to facilitate participation of heterogeneous trial sites.

Indexed as

Electronic Health RecordsMedicineData AccuracyData CollectionDrug IndustryHumansData qualityElectronic health recordsPragmatic clinical trial as topicResearch design

Identifiers

PMID37658391
PMCPMC10474626

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.