Stroke nurse compliance with assessment standards is enhanced by reducing the documentation burden: An implementation...

Area of Science:

• Clinical implementation science
• Health informatics
• Medical device adoption

Background:

• Quantitative pupillometry (QP) is a superior, evidence-based method for assessing pupil reactivity compared to subjective measures.
• Despite QP's availability, its adoption in clinical practice is inconsistent, with documentation burden potentially being a significant barrier.
• Implementation research aims to identify factors influencing the uptake of evidence-based practices.

Purpose of the Study:

• To investigate if automated documentation technology facilitates the implementation of quantitative pupillometry (QP).
• To assess the impact of reduced documentation burden on the adoption of QP.

Main Methods:

• A comparative study design was used, analyzing data from a manual-entry cohort and an automated-upload cohort.
• Compliance with unit-based pupil assessment policies was measured over 4-hour intervals during intensive care unit stays.
• Institutional Review Board approval was obtained for this study.

Main Results:

• No significant demographic differences were observed between the manual-entry (122 patients) and automated-entry (229 patients) cohorts.
• The automated-entry cohort demonstrated significantly higher compliance (65.0%) compared to the manual-entry cohort (47.7%) (t = -6.42, P < 0.0001).
• This indicates a substantial increase in adherence to pupil assessment protocols with automated documentation.

Conclusions:

• Reduced documentation burden is directly associated with increased adoption and compliance with evidence-based practices like QP.
• Automated documentation systems can serve as a facilitator for implementing new clinical technologies.
• Streamlining documentation processes is crucial for improving the utilization of advanced medical assessment tools.