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J Crit Care. 2018 Oct;47:295-301. doi: 10.1016/j.jcrc.2018.07.021. Epub 2018 Jul 22.

Secondary EMR data for quality improvement and research: A comparison of manual and electronic data collection from an integrated critical care electronic medical record system.

Author information

1
W21C Research & Innovation Centre, Cumming School of Medicine, University of Calgary, GD01-TRW Building, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6, Canada.
2
Department of Critical Care Medicine, University of Calgary, Foothills Medical Centre, Ground Floor-McCaig Tower, 1403-29 St NW, Calgary, AB T2N 5A1, Canada.
3
Department of Critical Care Medicine, University of Calgary, Foothills Medical Centre, Ground Floor-McCaig Tower, 1403-29 St NW, Calgary, AB T2N 5A1, Canada; eCritical Alberta Program, Alberta Health Services, Alberta, Canada.
4
Department of Critical Care Medicine, University of Calgary, Foothills Medical Centre, Ground Floor-McCaig Tower, 1403-29 St NW, Calgary, AB T2N 5A1, Canada; O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, 3rd Floor TRW Building, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3D10, 3280 Hospital Dr NW, Calgary, Alberta T2N 4Z6, Canada.
5
Department of Critical Care Medicine, Faculty of Medicine and Dentistry and School of Public Health, University of Alberta, 2-124E Clinical Sciences Building, 8440-112 St NW, Edmonton, Alberta T6G 2B7, Canada; Alberta Health Services, Alberta, Canada.
6
Department of Critical Care Medicine, University of Calgary, Foothills Medical Centre, Ground Floor-McCaig Tower, 1403-29 St NW, Calgary, AB T2N 5A1, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3D10, 3280 Hospital Dr NW, Calgary, Alberta T2N 4Z6, Canada.
7
Department of Critical Care Medicine, Faculty of Medicine and Dentistry and School of Public Health, University of Alberta, 2-124E Clinical Sciences Building, 8440-112 St NW, Edmonton, Alberta T6G 2B7, Canada; School of Public Health, University of Alberta, 3-300 Edmonton Clinic Health Academy, 11405-87 Ave Edmonton, Alberta T6G 1C9, Canada.
8
Department of Critical Care Medicine, University of Calgary, Foothills Medical Centre, Ground Floor-McCaig Tower, 1403-29 St NW, Calgary, AB T2N 5A1, Canada; O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, 3rd Floor TRW Building, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3D10, 3280 Hospital Dr NW, Calgary, Alberta T2N 4Z6, Canada; Alberta Health Services, Alberta, Canada. Electronic address: tstelfox@ucalgary.ca.

Abstract

PURPOSE:

This study measured the quality of data extracted from a clinical information system widely used for critical care quality improvement and research.

MATERIALS AND METHODS:

We abstracted data from 30 fields in a random sample of 207 patients admitted to nine adult, medical-surgical intensive care units. We assessed concordance between data collected: (1) manually from the bedside system (eCritical MetaVision) by trained auditors, and (2) electronically from the system data warehouse (eCritical TRACER). Agreement was assessed using Cohen's Kappa for categorical variables and intraclass correlation coefficient (ICC) for continuous variables.

RESULTS:

Concordance between data sets was excellent. There was perfect agreement for 11/30 variables (35%). The median Kappa score for the 16 categorical variables was 0.99 (IQR 0.92-1.00). APACHE II had an ICC of 0.936 (0.898-0.960). The lowest concordance was observed for SOFA renal and respiratory components (ICC 0.804 and 0.846, respectively). Score translation errors by the manual auditor were the most common source of data discrepancies.

CONCLUSIONS:

Manual validation processes of electronic data are complex in comparison to validation of traditional clinical documentation. This study represents a straightforward approach to validate the use of data repositories to support reliable and efficient use of high quality secondary use data.

KEYWORDS:

Data accuracy; Data concordance; Data quality; Electronic medical records; Medical record abstraction; Secondary data use

PMID:
30099330
DOI:
10.1016/j.jcrc.2018.07.021

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