Evidence map›Paper›PMID 41726083›Full record

ArticleDigital health

Single source - triple flow: Structured electronic data capture for pancreatic surgery patients.

Max Blumenstock, Fleur Fritz-Kebede, Niels Siegel, Nathalia Giese, Ulrike Heger, Christian Niklas, Tobias Dittrich, Nelly Zental, Matthias Ganzinger, Christoph U Lehmann and 4 more

Abstract read
In one paragraph

Article in Digital health. 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

14 authors.

Max BlumenstockInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-9816-0445
Fleur Fritz-KebedeInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-9005-6766
Niels SiegelDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Nathalia GieseDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Ulrike HegerDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Christian NiklasInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.
Tobias DittrichInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.
Nelly ZentalInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.
Matthias GanzingerInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.
Christoph U LehmannClinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Martin LoosDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Ulf HinzDepartment of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.ORCID https://orcid.org/0000-0001-8227-968X
Martin DugasInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.ORCID https://orcid.org/0000-0001-9740-0788
Thomas M PauschInstitute of Medical Informatics, Heidelberg University, Heidelberg, Germany.ORCID https://orcid.org/0000-0001-6145-3263

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Advancements in clinical medicine depend on state-of-the-art healthcare analytics, which require patient data from electronic health record (EHR) systems and electronic data capture (EDC). We developed and implemented an independent, yet integrated EDC system (designated IMI-EDC) in a tertiary hospital. This system ensures that clinical data are available for patient care and research while complying with regulatory standards. In this study, we compared the first cohort of IMI-EDC users against those using the predecessor paper-mediated system, measuring patient comfort and satisfaction, data quality, and facilitation of workflow facilitation. Methods: Until July 2025, more than 5000 patients were able to submit their medical history and health-related quality of life questionnaires via the IMI-EDC. All patients using tablets were surveyed regarding their user experience. Additionally, a subset of 100 EDC submissions was compared to 100 submissions via the paper-based system with respect to data completeness, correctness, clarity, and readability. Finally, the time to transfer data to the Heidelberg Pancreas Registry (HPR) research database was measured. Results: IMI-EDC was successfully implemented at our center. Approximately three-quarters (75%) of patients using tablets were comfortable with the system. Tablet users were significantly more likely to submit completed documents than those using paper (98/100 vs. 66/100), and among submitted forms, fully completed questionnaires were more frequent in the tablet group (70/98 vs. 24/66). Data transfers to the HPR were quicker for tablet submissions than for paper submissions in a small pragmatic subsample (4.2 minutes vs. 9.9 minutes; 7 tablet vs. 7 paper cases). Conclusions: IMI-EDC is satisfactory for patients and staff in terms of user experience, data completeness, and workload reduction in the setting of a high-volume surgical center.

Indexed as

Electronic data capturemedical informaticspancreas surgerypatient-reported outcomes measuresresearch data managementsingle source

Identifiers

PMID41726083
PMCPMC12921161

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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.