Summary
Background: Preoperative 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.
Methods: An 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.
Results: During the study period, 73 802 (0.015%) of the 485 062 902 audit log accesses were
pre-operative 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.
Conclusions: This 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.
Keywords
Visual - analytics - anesthesia
