Using Ontario's "Telehealth" health telephone helpline as an early-warning system: a study protocol.
BACKGROUND
The science of syndromic surveillance is still very much in its infancy. While a number of syndromic surveillance systems are being evaluated in the US, very few have had success thus far in predicting an infectious disease event. Furthermore, to date, the majority of syndromic surveillance systems have been based primarily in emergency department settings, with varying levels of enhancement from other data sources. While research has been done on the value of telephone helplines on health care use and patient satisfaction, very few projects have looked at using a telephone helpline as a source of data for syndromic surveillance, and none have been attempted in Canada. The notable exception to this statement has been in the UK where research using the national NHS Direct system as a syndromic surveillance tool has been conducted.


METHODS
The purpose of our proposed study is to evaluate the effectiveness of Ontario's telephone nursing helpline system as a real-time syndromic surveillance system, and how its implementation, if successful, would have an impact on outbreak event detection in Ontario. Using data collected retrospectively, all "reasons for call" and assigned algorithms will be linked to a syndrome category. Using different analytic methods, normal thresholds for the different syndromes will be ascertained. This will allow for the evaluation of the system's sensitivity, specificity and positive predictive value. The next step will include the prospective monitoring of syndromic activity, both temporally and spatially.


CONCLUSIONS
As this is a study protocol, there are currently no results to report. However, this study has been granted ethical approval, and is now being implemented. It is our hope that this syndromic surveillance system will display high sensitivity and specificity in detecting true outbreaks within Ontario, before they are detected by conventional surveillance systems. Future results will be published in peer-reviewed journals so as to contribute to the growing body of evidence on syndromic surveillance, while also providing an non US-centric perspective.
Rolland
Elizabeth
E
Ontario Syndromic Surveillance Project, Kingston, Canada. erolland@gmail.com
Moore
Kieran M
KM
Robinson
Victoria A
VA
McGuinness
Don
D
D000465:Algorithms; D023482:Bioterrorism / Q000517:prevention & control / Q000706:statistics & numerical data; D021821:Communicable Diseases, Emerging / Q000453:epidemiology* / Q000517:prevention & control; D003199:Computer Systems; D004196:Disease Outbreaks / Q000517:prevention & control*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D006302:Health Services Research; D015277:Hotlines / Q000706:statistics & numerical data*; D006801:Humans; D007253:Information Centers / Q000706:statistics & numerical data*; D009739:Nursing Services / Q000706:statistics & numerical data; D009864:Ontario / Q000453:epidemiology; D011159:Population Surveillance / Q000379:methods*; D012107:Research Design; D013577:Syndrome