ArticleJournal of medical Internet research2022
A Wolf in Sheep's Clothing: Reuse of Routinely Obtained Laboratory Data in Research.
Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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.
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Who cites it
10 citing papers in PubMed.
- Early auxiliary diagnosis model for chest pain triad based on artificial intelligence multimodal fusion.JAMIA open · 2025Article
- Comparison of estimated glomerular filtration rate equations on prediction of mortality, kidney failure and acute kidney injury.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025Article
- The future of healthcare-associated infection surveillance: Automated surveillance and using the potential of artificial intelligence.Journal of internal medicine · 2025Review
- Article
- Optimising coronary imaging decisions with machine learning: an external validation study.Open heart · 2025Article
- Beyond the numbers: the importance of contextual data when reusing blood pressure data from electronic health records.Frontiers in digital health · 2025Article
- Implementing Findable, Accessible, Interoperable, Reusable (FAIR) Principles in Child and Adolescent Mental Health Research: Mixed Methods Approach.JMIR mental health · 2024Article
- Left Ventricular Diastolic Dysfunction across Levels of Kidney Function: A Cross-Sectional Study Based on Routine Clinical Practice Data.Journal of clinical medicine · 2024Article
- Design, validation and implementation of an automated e-alert for acute kidney injury: 6-month pilot study shows increased awareness.BMC nephrology · 2023Article
- A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data.Scientific data · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electronic health records (EHRs) contain valuable data for reuse in science, quality evaluations, and clinical decision support. Because routinely obtained laboratory data are abundantly present, often numeric, generated by certified laboratories, and stored in a structured way, one may assume that they are immediately fit for (re)use in research. However, behind each test result lies an extensive context of choices and considerations, made by both humans and machines, that introduces hidden patterns in the data. If they are unaware, researchers reusing routine laboratory data may eventually draw incorrect conclusions. In this paper, after discussing health care system characteristics on both the macro and micro level, we introduce the reader to hidden aspects of generating structured routine laboratory data in 4 steps (ordering, preanalysis, analysis, and postanalysis) and explain how each of these steps may interfere with the reuse of routine laboratory data. As researchers reusing these data, we underline the importance of domain knowledge of the health care professional, laboratory specialist, data manager, and patient to turn routine laboratory data into meaningful data sets to help obtain relevant insights that create value for clinical care.
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Registered trials
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.