Summary
Objective: The objective of this study was to investigate and improve the use of automated data
collection procedures for nursing research and quality assurance.
Methods: A descriptive, correlational study analyzed 44 orthopedic surgical patients who were
part of an evidence-based practice (EBP) project examining post-operative oxygen therapy
at a Midwestern hospital. The automation work attempted to replicate a manually-collected
data set from the EBP project.
Results: Automation was successful in replicating data collection for study data elements
that were available in the clinical data repository. The automation procedures identified
32 “false negative” patients who met the inclusion criteria described in the EBP project
but were not selected during the manual data collection. Automating data collection
for certain data elements, such as oxygen saturation, proved challenging because of
workflow and practice variations and the reliance on disparate sources for data abstraction.
Automation also revealed instances of human error including computational and transcription
errors as well as incomplete selection of eligible patients.
Conclusion: Automated data collection for analysis of nursing-specific phenomenon is potentially
superior to manual data collection methods. Creation of automated reports and analysis
may require initial up-front investment with collaboration between clinicians, researchers
and information technology specialists who can manage the ambiguities and challenges
of research and quality assurance work in healthcare.
Citation: Byrne MD, Jordan TR, Welle T. Comparison of Manual versus Automated Data Collection
Method for an Evidence-Based Nursing Practice Study. Appl Clin Inf 2013; 4: 61–74
http://dx.doi.org/10.4338/ACI-2012-09-RA-0037
Keywords
Automation - comparative study - data collection - evidence-based nursing - nursing
methodology research