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ISDS 2012 Conference Abstracts

A System for Surveillance Directly from the EMR
Richard F. Davies*1, Jason Morin1, Ramanjot S. Bhatia1 and Lambertus de Bruijn2

1University of Ottawa Heart Institute, Ottawa, ON, Canada; 2National Research Council Canada, Ottawa, ON, Canada

Objective
Our objective was to conduct surveillance of nosocomial infec-

tions directly from multiple EMR data streams in a large multi-loca-
tion Canadian health care facility. The system developed
automatically triggers bed-day-level-location-aware reports and de-
tects and tracks the incidents of nosocomial infections in hospital by
ward.

Introduction
Hospital acquired infections are a major cause of morbidity, mor-

tality and increased resource utilization. CDC estimates that in the
US alone, over 2 million patients are affected by nosocomial infec-
tions costing approximately $34.7 billion to $45 billion annually (1).
The existing process of detection and reporting relies on time con-
suming manual processing of records and generation of alerts based
on disparate definitions that are not comparable across institutions or
even physicians.

Methods
A multi-stakeholder team consisting of experts from medicine, in-

fection control, epidemiology, privacy, computing, artificial intelli-
gence, data fusion and public health conducted a proof of concept
from four complete years of admission records of all patients at the
University of Ottawa Heart Institute . Figure 1 lists the data elements
investigated. Our system uses an open source enterprise bus ‘Mirth
Connect’ to receive and store data in HL7 format. The processing of
information is handled by individual components and alerts are
pushed back to respective locations.The free text components were
classified using natural language processing. Negation detection was
performed using NegEx (2). Data-fusion algorithms were used to
merge information to make it meaningful and allow complex syn-
drome definitions to be mapped onto the data.

Results
The system monitors: Ventilator Associated Pneumonia (VAP),

Central Line Infections (CLI), Methicillin Resistant Staph Aureus
(MRSA), Clostridium difficile (C. Diff) and Vancomycin resistant
Enterococcus (VRE).

21452 hospital admissions occurred in 17670 unique patients over
four years. There were 41720 CXRs performed in total, of which
10546 were classified as having an infiltrate. 4575 admissions were
associated with at least one CXR showing an infiltrate, 2266 of which
were hospital-acquired. Hospital acquired infiltrates were associated
with an increased hospital mortality (6.3% vs 2.6%)* and length of
stay (19.5 days vs 6.5 days)*. 253 patients had at least one positive
blood culture. This was also associated with an increased hospital
mortality (23,3% vs. 2.8%)* and length of stay (10.8 vs 40.9 days)*.
(* all p values < 0.00001)

Conclusions
This proof of concept system demonstrates the capability of mon-

itoring and analyzing multiple available data streams to automatically

detect and track infections without the need for manual data capture
and entry. It acquires directly from the EMR data to identify and clas-
sify health care events, which can be used to improve health outcomes
and costs. The standardization of definitions used for detection will
allow for generalization across institutions.

Keywords
electronic health records; surveillance; pneumonia; hospital acquired
infections

Acknowledgments

This work was supported by Defence Research and Development Canada
Centre for Security Science and the Chemical, Biological, Radiologi-
cal/Nuclear, and Explosives Research and Technology Initiative (CRTI)
under project CRTI 06-0234TA and the following participatory and ad-
visory partners.

References

1. Report on CDC Website (http://www.cdc.gov/hai/pdfs/hai/scott_cost-
paper.pdf) Accessed: 10th September, 2012.

2. Chapman, W. et. al. 2001. Evaluation of negation phrases in narrative
clinical reports. Proc AMIA Symposium, 105-114.

*Richard F. Davies
E-mail: rfdavies@ottawaheart.ca

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e29, 2013