Evidence map›Paper›PMID 33409423›Full record

ArticleContemporary clinical trials communications2021

Assessing an Electronic Health Record research platform for identification of clinical trial participants.

Niina Laaksonen, Juha-Matti Varjonen, Minna Blomster, Antti Palomäki, Tuija Vasankari, Juhani Airaksinen, Risto Huupponen, Mika Scheinin, Juuso Blomster

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Article in Contemporary clinical trials communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
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

9 authors.

Niina LaaksonenInstitute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland.
Juha-Matti VarjonenAuria Clinical Informatics, Hospital District of Southwest Finland, PO Box 52, FI-20521, Turku, Finland.
Minna BlomsterAuria Clinical Informatics, Hospital District of Southwest Finland, PO Box 52, FI-20521, Turku, Finland.
Antti PalomäkiHeart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland.
Tuija VasankariHeart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland.
Juhani AiraksinenHeart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland.
Risto HuupponenInstitute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland.
Mika ScheininInstitute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland.
Juuso BlomsterInstitute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic health records (EHR) are a potential resource for identification of clinical trial participants. We evaluated how accurately a commercially available EHR Research Platform, InSite, is able to identify potential trial participants from the EHR system of a large tertiary care hospital. Patient counts were compared with results obtained in a conventional manual search performed for a reference study that investigated the associations of atrial fibrillation (AF) and cerebrovascular incidents. The Clinical Data Warehouse (CDW) of Turku University Hospital was used to verify the capabilities of the EHR Research Platform. The EHR query resulted in a larger patient count than the manual query (EHR Research Platform 5859 patients, manual selection 2166 patients). This was due to the different search logic and some exclusion criteria that were not addressable in structured digital format. The EHR Research Platform (5859 patients) and the CDW search (5840 patients) employed the same search logic. The temporal relationship between the two diagnoses could be identified when they were available in structured format and the time difference was longer than a single hospital visit. Searching for patients with the EHR Research Platform can help to identify potential trial participants from a hospital's EHR system by limiting the number of records to be manually reviewed. EHR query tools can best be utilized in trials where the selection criteria are expressed in structured digital format.

Indexed as

Clinical trialsElectronic health recordsPatient identificationPatient recruitment

Identifiers

PMID33409423
PMCPMC7773855

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.