Impact of an electronic information system on physician workflow and data collection in the intensive care unit.
OBJECTIVE
To test the hypotheses that: (1) integrating information processing tasks using an electronic clinical information system (ECIS) decreases time to complete these tasks by hand; and (2) structured data entry encourages generation of more detailed records and capture of specific data elements even when entry is voluntary.


METHODS
Prospective observational time analysis during medical documentation tasks. Retrospective analysis of clinical documentation completed by hand or electronically.


METHODS
Eleven bed pediatric intensive care unit within an academic medical center.


METHODS
Five pediatric intensive care medicine attending physicians.


METHODS
Compared handwritten and electronic documentation to determine: (1) time spent entering data or composing notes; (2) number of descriptors documenting patients' physical exams; (3) users' preferences for structured or unstructured data entry; (4) frequency of documenting specific data elements related to nutritional support.


RESULTS
Documentation time varied by user but not charting method: it took 13 % less time to document using the ECIS but this was not significant. Electronic documents were more detailed than handwritten containing 50 % more descriptors (17.8 +/- 1.4 vs 11.6 +/- 1.4) overall and some data elements that were not handwritten: information related to nutritional supplementation was recorded in 13 % of electronic documents but in none of 89 handwritten documents.


CONCLUSIONS
Electronic and handwritten documentation consumed equal amounts of time. Structured entry, compared to handwriting, may encourage recording of specific or otherwise unincorporated data elements resulting in a more detailed record. This suggests that user interfaces and decision support components may influence both the types and complexity of clinical data recorded by caregivers.
Apkon
M
M
Pediatrics and Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06520-8064, USA. Michael.apkon@yale.edu
Singhaviranon
P
P
D000704:Analysis of Variance; D001292:Attitude to Computers; D003658:Decision Making, Computer-Assisted; D004282:Documentation; D017598:Efficiency, Organizational; D006751:Hospital Information Systems; D006801:Humans; D015278:Intensive Care Units, Pediatric / Q000458:organization & administration*; D015999:Multivariate Analysis; D009323:Natural Language Processing; D010820:Physicians; D011446:Prospective Studies; D012189:Retrospective Studies; D013647:Task Performance and Analysis; D013997:Time Factors; D014481:United States; D014584:User-Computer Interface