ArticleAcademic pathology
Evaluating the utility and challenges associated with "unknown" and fictional patients in the electronic medical record.
Article in Academic pathology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electronic medical records (EMRs) allow for the creation of "fictional" and unknown patients within the EMR production environment. Surprisingly, there is sparse literature regarding the use cases for these patients or the challenges associated with their existence in the EMR. Here, we identified three classes of patients in regular use at our institution: true fictional patients with medical record numbers (MRNs) used to test EMR functions in the production environment, "confidential patients" used to store sensitive data, and "unknown" patients that are assigned temporary MRNs in emergency situations until additional information can be acquired. A further layer of complexity involving the merging of records for unknown patients once they are identified is also explored. Each class of patients, real or fictional, poses a variety of challenges from a clinical laboratory standpoint, which are often dealt with on a case-by-case basis. Here, we present a series of instructional cases adapted from actual patient safety events at our institution involving fictional, confidential, and unknown patient records. These illustrative cases highlight the utility of these fictional and unknown patients, as well as the challenges they pose on an institutional and individual level, including issues that arise from merging clinical data from temporary MRNs to identified patient charts. Lastly, we provide recommendations on how best to manage similar scenarios that may arise.
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