ArticleJournal of clinical anesthesia2014
Are anesthesia start and end times randomly distributed? The influence of electronic records.
Article in Journal of clinical anesthesia, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Timing errors and temporal uncertainty in clinical databases-A narrative review.Frontiers in digital health · 2022Review
- A retrospective evaluation of the risk of bias in perioperative temperature metrics.Journal of clinical monitoring and computing · 2019Article
- Comparison of minute distribution frequency for anesthesia start and end times from an anesthesia information management system and paper records.Journal of clinical monitoring and computing · 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
Abstract
STUDY
objectiveTo perform a frequency analysis of start minute digits (SMD) and end minute digits (EMD) taken from the electronic, computer-assisted, and manual anesthesia billing-record systems.
designRetrospective cross-sectional review.
settingUniversity medical center. MEASUREMENTS: This cross-sectional review was conducted on billing records from a single healthcare institution over a 15-month period. A total of 30,738 cases were analyzed. For each record, the start time and end time were recorded. Distributions of SMD and EMD were tested against the null hypothesis of a frequency distribution equivalently spread between zero and nine. MAIN
resultsSMD and EMD aggregate distributions each differed from equivalency (P < 0.0001). When stratified by type of anesthetic record, no differences were found between the recorded and expected equivalent distribution patterns for electronic anesthesia records for start minute (P < 0.98) or end minute (P < 0.55). Manual and computer-assisted records maintained nonequivalent distribution patterns for SMD and EMD (P < 0.0001 for each comparison). Comparison of cumulative distributions between SMD and EMD distributions suggested a significant difference between the two patterns (P < 0.0001).
conclusionAn electronic anesthesia record system, with automated time capture of events verified by the user, produces a more unified distribution of billing times than do more traditional methods of entering billing times.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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