Syndromic Surveillance: Early CBRN Attack Detection by Computerized Medical Record Surveillance in Grey Bruce Richard Davies MD, PhD Professor of Medicine University of Ottawa Heart Institute
Premise Access to accurate health care data in large populations is a rate te- limiting step for many activities. Counterterrorism surveillance. Surveillance for naturally occurring infectious outbreaks. Surveillance and management of chronic diseases/health care reform. rm. Population based medical research. This information is already being collected at the bedside, and making it accessible across populations is a worthwhile challenge. e. Syndromic Surveillance does this for ER record chief complaints and infectious disease outbreaks. Extending this technology to chronic diseases is a next logical step.
Early CBRN Attack Detection by Computerized Medical Records Surveillance (ECADS)
CRTI: CBRN (Chemical Biological Radiation Nuclear) Research and Technology Initiative
CRTI Investment Priority Areas Collective Command, Control, Communications, Coordination and Information (C4I) Capabilities for CBRN Planning and Response S&T for Equipping & Training 1 st Responders Prevention, Surveillance & Alert Capabilities Immediate Reaction and Near-Term Consequence Management Capabilities Longer-Term Consequence Management Capabilities Criminal Investigation Capabilities S&T Dimensions of Risk Assessment Public Confidence & Psycho-Social Factors
ECADS Proposal to CRTI Develop Syndromic Surveillance capability and prove it does something useful. Retrospective analysis of ER text mining in detecting the Walkerton gastroenteritis outbreak in 2000. Prove we can deploy it in a Canadian setting On line technology demonstration in Grey Bruce area Hospitals and Public Health Unit Extend capability Work with NRC IIT to improve and extend the technology for text mining of health records Integrate with ongoing Surveillance initiatives. Roadmap for development and deployment
ECADS Team Scientific Team Ottawa Heart Institute (RF Davies, ECADS PI) Michigan State University National Food Safety and Toxicology Center (Ewen( Todd) Carnegie Mellon University Auton Laboratory (Andrew Moore, Daniel Neil) Grey Bruce Public Health Unit (Hazel Lynn, Alana Leffley) Grey Bruce area Hospitals Technical Team AMITA Corporation Performance Support Services Inc Cam Emergency Preparedness e-privacy Systems Inc Federal Government Partners National Research Council, Institute for Marine Biosciences (NRC/IMB) (Laura Brown) National Research Council, Institute for Information Technology (NRC/IIT) (Joel Martin) Public Health Agency of Canada, Laboratory Centre for Disease Control (LCDC) (Paul Sockett, Division of Foodborne and Waterborne Diseases)
ECADS Collaborators Michigan State Department of Public Health QUESST Project (KFLA Public Health Unit, Ontario MOHLTC) CNPHI Project, PHAC Office for Public Health Practice, PHAC (Centre for Surveillance Coordination) Canada Health Infoway Canadian Institute for Health Information Ottawa Hospital Division of Endocrinology Ottawa Hospital Division of Family Medicine Ottawa Public Health University of Guelph Dept. of Computer Science.
What do we mean by Syndromic Surveillance?
Syndromes Syndromes in clinical medicine The sum of symptoms and signs of any morbid state. A pattern of multiple anomalies believed to be pathogenetically related. Dorland s s lists > 1200 distinct syndromes Why are syndromes important? Presumptive diagnosis based on a cluster of findings. Classifies a patient based on the information at hand. Makes triage, investigation and initial management possible in the absence of a confirmed diagnosis.
Syndromic Surveillance Epidemiological definition of syndrome an increased frequency of events in a population potentially associated with a disease outbreak. Use of IT to extend the number of data streams that can be monitored. Medical records an important potential data source for this kind of surveillance. Also includes other non-traditional data sources. OTC Drugs Absenteeism from work or school
ECADS Exercise 1 Retrospective Study of Walkerton Outbreak
Courtesy of Dr. Hazel Lynn, Grey Bruce Public Health Unit
ECADS Exercise 1: Methods (1/2) Research Protocol with Research Ethics Board Approval Ottawa Heart Institute Owen Sound South Bruce Grey Health Centre 396,698 Anonymized ER Records 392,699 Electronic (Three EHR Systems, 9 Hospitals) 3,999 Manual (Hanover, 3 months) Three year data (Jan 1, 1999 Dec 31, 2001) 9 Grey Bruce Area Hospitals Three month data (April 1, 2000 June 30, 2000) 10 Grey Bruce Area Hospitals
ECADS Exercise 1: Methods 2/2 Electronic data provided directly to AMITA Hanover data collected by chart abstraction, entered manually by OHI and provided to AMITA AMITA Installed RODS Cleaned data Processed three month and three year data sets. RODS Chief complaint categorized into 7 syndromes, other or default. Produces Maps and Graphs and Alerts Produced a processed data set for further analysis. OHI Carnegie Mellon