ArticleEinstein (Sao Paulo, Brazil)2024
Electronic health record implementation: how to identify and analyze the possible negative impacts.
Article in Einstein (Sao Paulo, Brazil), 2024. 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
objectiveIdentify potential negative impacts arising from implementing an electronic medical record system, classify them according to the level of criticality, and analyze method's effectiveness after implementation.
methodsThe research involved identifying the negative impacts, classifying them according to the criteria for criticality, stratifying them as high, medium, or low severity, and finally, analyzing the effectiveness of the identification and classification methods.
resultsFindings confirmed that 89.20% of identified impacts occurred as predicted, and 88.94% of impacts had a level of criticality compatible with the severity of the problem.
conclusionPredicting and classifying negative impacts are important stages in implementing electronic health records in hospitals. The method for identification and classification of impacts were, in most cases, considered effective.
Indexed as
Identifiers
What OpenQuestion holds
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.