Evidence map›Paper›PMID 42644147›Full record

ReviewClinical epidemiology2026

Regional Electronic Health Records in Denmark: Research Potential for Clinical Epidemiology.

Mette Kielsholm Thomsen, Helene Rask Dalby, Anders Schram, Simon Kok Jensen, Lise Skovgaard Svingel, Kasper Bonnesen, Morten Schmidt, Magnus Kirketerp Krusell, Matilde Slot, Ole Halfdan Larsen and 1 more

Abstract readReview
In one paragraph

Review in Clinical epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Mette Kielsholm Thomsen *CONNECT - Center for Clinical and Genomic Data, Central Denmark Region, Aarhus, Denmark.ORCID 0000-0001-7308-3431
Helene Rask Dalby *Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.ORCID 0000-0001-8923-314X
Anders SchramMidtsim, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Simon Kok JensenCONNECT - Center for Clinical and Genomic Data, Central Denmark Region, Aarhus, Denmark.ORCID 0000-0002-0032-131X
Lise Skovgaard SvingelCONNECT - Center for Clinical and Genomic Data, Central Denmark Region, Aarhus, Denmark.ORCID 0000-0002-4938-037X
Kasper BonnesenDepartment of Clinical Pharmacology, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Morten SchmidtDepartment of Cardiology, Gødstrup Hospital, Herning, Denmark.ORCID 0000-0002-4935-4059
Magnus Kirketerp KrusellData and Data Applications, Central Denmark Region, Aarhus, Denmark11Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Matilde SlotCONNECT - Center for Clinical and Genomic Data, Central Denmark Region, Aarhus, Denmark.
Ole Halfdan LarsenCONNECT - Center for Clinical and Genomic Data, Central Denmark Region, Aarhus, Denmark.
Christian Fynbo ChristiansenCONNECT - Center for Clinical and Genomic Data, Central Denmark Region, Aarhus, Denmark.ORCID 0000-0002-0727-953X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Denmark has a well-established tradition of utilizing national registries for epidemiological research. Healthcare services in Denmark are managed by five administrative regions and documented in electronic health records (EHRs). While certain EHR data are mandatorily transferred to national registries, the national registries capture only a fraction of the information available within regional EHR systems. In this review, we describe and discuss the context, content, and research potential of regional EHR data in Denmark for observational studies and pragmatic clinical trials. Throughout, examples and descriptions of data infrastructure primarily stem from one region (the Central Denmark Region). As each region governs its own healthcare delivery and IT systems, there are regional variations in EHR data sources and availability for research purposes. Overall, EHRs integrate clinical information, including structured entries (diagnoses, procedures, and treatments); semi-structured input of clinical information; free-text clinical notes; results from biochemical, microbiological, and pathological analyses; radiological images and descriptions; administered medicines; and administrative data such as appointment and procedure bookings. Regional EHRs include several data types unavailable or incompletely captured in national registries, including semi-structured and free-text clinical information, certain laboratory results, radiology descriptions, and hospital-administered or prescribed medicines before 2018. These data hold specific potential for research. Overall, the utilization of EHR data holds significant promise for improving both clinical trials and observational studies. In pragmatic trials, EHRs can facilitate patient recruitment and data collection on patient characteristics, outcomes, and adverse events within routine care, enabling larger, more generalizable study designs at lower costs. In observational research, EHR data can provide highly detailed clinical information and data types not captured in population-based registries. However, the use of regional EHR data also presents important challenges, including inter-regional heterogeneity in data systems and governance, variable data completeness, and methodological difficulties related to the extraction and analysis of unstructured clinical information. Despite these limitations, EHR data in Denmark provide large-scale, unique clinical information that complements population-based registries and represents an increasingly important resource for research. As data systems mature and the methods to utilize unstructured clinical information develop, the potential of these data to facilitate observational studies and pragmatic trials will continue to expand.

Indexed as

epidemiologyhealthcareregistriessecondary data sourcestrials

Identifiers

PMID42644147
PMCPMC13505535

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.