ArticleJournal of clinical monitoring and computing2017
Introduction of a new electronic medical record system has mixed effects on first surgical case efficiency metrics.
Article in Journal of clinical monitoring and computing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Which Electronic Health Record System Should We Use? A Systematic Review.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2022Pooled it
- Effect of the Implementation of a New Electronic Health Record System on Surgical Case Turnover Time.Journal of medical systems · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To evaluate the effect of deploying a new electronic medical record (EMR) system on first case starts in the operating room. Data on first case start times were collected after implementation of a new EMR (Epic) from June 2015 to May 2016, which replaced a legacy system of both paper and electronic records. These were compared to data from the same months in the three proceeding years. First patient in room (FPIR) on time was true if the patient was in operating room before 7:35 AM (or 9:35 AM on Wednesdays) and first case on time start (FCOTS) was true if completion of anesthetic induction was less than 20 min after the patient entered the operating room (or 35 min for cardiac and neurosurgery). Times beyond these cutoffs were quantified as FPIR and FCOTS delays in minutes. Average delays were compared by month with two-sample t tests and 95 % confidence intervals. There was a significant increase in FPIR delays in the first month (11.07 vs. 3.47 min, p < 0.0001), which abated by the fifth month. Post-implementation FCOTS delays improved by the third month (4.53 vs. 7.10 min, p < 0.0001). Both results persisted throughout the study. First month FPIR delays were not limited to any one specialty. EMRs have the potential to improve hospital workflows, but are not without learning curves. FPIR and FCOTS delays return to baseline after a few months, and in the case of FCOTS, can improve beyond baseline.
Indexed as
Identifiers
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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.