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Assessing Data Quality in Manual Entry of Ventilator Settings
Open accessAbstract
OBJECTIVE: To evaluate the data quality of ventilator settings recorded by respiratory therapists using a computer charting application and assess the impact of incorrect data on computerized ventilator management protocols. DESIGN An analysis of 29,054 charting events gathered over 12 months from 678 ventilated patients (1,736 ventilator days) in four intensive care units at a tertiary care hospital. MEASUREMENTS: Ten ventilator settings were examined, including fraction of inspired oxygen (Fio (2)), positive end-expiratory pressure (PEEP), tidal volume, respiratory rate, peak inspiratory flow, and pressure support. Respiratory therapists entered values for each setting approximately every two hours using a computer charting application. Manually entered values were compared with data acquired automatically from ventilators using an implementation of the ISO/IEEE 11073 Medical Information Bus (MIB). Data quality was assessed by measuring the percentage of time that the two sources matched. Charting delay, defined as the interval between data observation and data entry, also was measured. RESULTS: The percentage of time that settings matched ranged from 99.0% (PEEP) to 75.9% (low tidal volume alarm setting). The average charting delay for each charting event was 6.1 minutes, including an average of 1.8 minutes spent entering data in the charting application. In 559 (3.9%) of 14,263 suggestions generated by computerized ventilator management protocols, one or more manually charted setting values did not match the MIB data. CONCLUSION: Even at institutions where manual charting of ventilator settings is performed well, automatic data collection can eliminate delays, improve charting efficiency, and reduce errors caused by incorrect data.
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In three of the four articles assessing currency, researchers reviewed whether desired data were entered into the EHR within a set time limit.
“In three of the four, researchers reviewed whether desired data were entered into the EHR within a set time limit.36 46 52”
From Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research (2013) · cites this paper as [46]
The Methods (Data Analysis; page unavailable) say the researchers measured charting delay—the interval between observing ventilator settings and entering them into the computer—to assess timeliness. The Results report an average delay of 6.1 minutes, but the study does not assess whether entries met a set time limit. The 30-minute limit in the Background describes an earlier study by East et al., not this study's measure. (LLM, conf=0.85)
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Weiskopf, N. G., & Weng, C. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000681 · Cited by 1,216
Cusack, C. M., Hripcsak, G., Bloomrosen, M., Rosenbloom, S. T., Weaver, C. A., Wright, A., Vawdrey, D. K., Walker, J., & Mamykina, L. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001093 · Cited by 103
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Metadata
- Authors
- Vawdrey, D. K., Gardner, R. M., Evans, R. S., Orme, J. F., Clemmer, T. P., Greenway, L., & Drews, F. A.
- Affiliations
- Intermountain Healthcare (US)
- Corresponding author
- Vawdrey, D. K.
- ORCID
- Drews, F. A.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-05-01
- Volume
- 14
- Issue
- 3
- Pages
- 295-303
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC2244881
- OpenAlex
- W2158305775
- Cited by
- 48
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 1 · 2022: 1 · 2021: 3 · 2020: 3 · 2016: 3 · 2015: 2 · 2014: 4 · 2013: 2 · 2012: 3
- FWCI
- 11.78
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Intermountain Healthcare
- U.S. National Library of Medicine (# LM007124, T15LM007124)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Health Sciences › Nursing › Research and Theory › Nursing Diagnosis and Documentation
- Keywords
- ventilator settings, data quality, ISO/IEEE 11073, respiratory therapists, intensive care unit, automated data collection, clinical decision support, data entry errors
- MeSH terms
- Data Collection, Forms and Records Control, Hospital Information Systems, Humans, Positive-Pressure Respiration, Prospective Studies, Ventilators, Mechanical, Respiratory Therapy, Therapy, Computer-Assisted, User-Computer Interface, Medical Records Systems, Computerized
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