Evidence map›Paper›PMID 26767060›Full record

ArticleApplied clinical informatics2015

Using Visual Analytics to Determine the Utilization of Preoperative Anesthesia Assessments.

J P Wanderer, C L Gruss, J M Ehrenfeld

Abstract read
In one paragraph

Article in Applied clinical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

J P WandererDepartments of Anesthesiology and Biomedical Informatics, Vanderbilt University , Nashville, TN, United States.
C L GrussDepartment of Anesthesiology, Vanderbilt University , Nashville, TN, United States.
J M EhrenfeldDepartments of Anesthesiology, Biomedical Informatics and Surgery, Vanderbilt University , Nashville, TN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreoperative assessments are a required and essential element of anesthetic care, yet little is known about the utilization of these documents by clinicians who are not part of the anesthesia care team. As part of perioperative workflow restructuring, we implemented a data visualization technique of electronic medical record audit log data to understand the utilization of preoperative anesthesia assessments by non-anesthesia personnel.

methodsAn audit log cache containing 140 days of data was queried for all accesses of preoperative anesthesia assessment documents for any patient who had a preoperative anesthesia assessment that was accessed during that period. User roles were aggregated into categories. Descriptive statistics and data visualization were generated using R (R Software Foundation, Vienna, Austria). Comparisons were performed with the Wilcoxon signed rank test with continuity correction.

resultsDuring the study period, 73 802 (0.015%) of the 485 062 902 audit log accesses were preoperative anesthesia assessments representing 412 departments, 302 user roles, and 3 916 distinct users who accessed preoperative anesthesia assessments from 14 235 surgical cases. Each assessment was accessed 2.9 times on average. Assessments performed in the preoperative anesthesia assessment clinic were accessed more frequently than those created on the day of surgery in the preoperative holding room (3.58 ± 5.18 v. 1.98 ± 1.76 average views; p<0.0001). We observed accesses of these documents by pathology and general surgery researchers, as well as orthopedics attending physicians accessing documents that were two years old.

conclusionsThis approach revealed patterns of utilization that had not been previously identified, including usage by surgical residents, surgical faculty, and pathology researchers both before and after the surgical event for which the documents are generated. Knowledge of these dependencies directly informed perioperative workflow restructuring efforts. This visual analytic approach could be broadly utilized to understand documentation dependencies in a variety of clinical contexts.

Indexed as

Preoperative PeriodAlgorithmsAnesthesiaDocumentationElectronic Health RecordsHumansMedical AuditanalyticsanesthesiaVisual

Identifiers

PMID26767060
PMCPMC4704033

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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.