OBJECTIVE: There is a paucity of information regarding the usefulness of non-traditional data streams for real-time syndromic surveillance systems. The objective of this paper is to examine the temporal relation between Ontario's emergency department (ED) visits and telephone health line (Telehealth) call volume for respiratory illnesses to test the feasibility of using Ontario's Telehealth system for real-time surveillance. METHODS: Retrospective time-series data from the National Ambulatory Care Reporting System (NACRS) and the Telehealth Ontario program from June 1, 2004, to March 31, 2006, were analyzed. The added value of Telehealth Ontario data was determined by comparing it temporally with NACRS data, which uses the International Classification of Diseases (ICD) 10-Canadian Enhancement coding system for discharge diagnoses. RESULTS: Telehealth Ontario had 216,105 calls for respiratory complaints, while 819,832 ICD-coded complaints from NACRS were identified with a comparable diagnosis of respiratory illness. Telehealth Ontario call volume was heavily weighted for the 0-4 years age group (49%), while the NACRS visits were mainly from those 18-64 years old (44%). The Spearman rank correlation coefficient was calculated to be 0.97, with the time-series analysis also resulting in significant correlations at lags (semi-monthly) 0 and 1, indicating that increases in Telehealth Ontario call volume correlate with increases in NACRS discharge diagnosis data for respiratory illnesses. CONCLUSION: Telehealth Ontario call volume fluctuation reflects directly on ED respiratory visit data on a provincial basis. These call complaints are a timely, useful and representative data stream that shows promise for integration into a real-time syndromic surveillance system.
OBJECTIVE: There is a paucity of information regarding the usefulness of non-traditional data streams for real-time syndromic surveillance systems. The objective of this paper is to examine the temporal relation between Ontario's emergency department (ED) visits and telephone health line (Telehealth) call volume for respiratory illnesses to test the feasibility of using Ontario's Telehealth system for real-time surveillance. METHODS: Retrospective time-series data from the National Ambulatory Care Reporting System (NACRS) and the Telehealth Ontario program from June 1, 2004, to March 31, 2006, were analyzed. The added value of Telehealth Ontario data was determined by comparing it temporally with NACRS data, which uses the International Classification of Diseases (ICD) 10-Canadian Enhancement coding system for discharge diagnoses. RESULTS: Telehealth Ontario had 216,105 calls for respiratory complaints, while 819,832 ICD-coded complaints from NACRS were identified with a comparable diagnosis of respiratory illness. Telehealth Ontario call volume was heavily weighted for the 0-4 years age group (49%), while the NACRS visits were mainly from those 18-64 years old (44%). The Spearman rank correlation coefficient was calculated to be 0.97, with the time-series analysis also resulting in significant correlations at lags (semi-monthly) 0 and 1, indicating that increases in Telehealth Ontario call volume correlate with increases in NACRS discharge diagnosis data for respiratory illnesses. CONCLUSION: Telehealth Ontario call volume fluctuation reflects directly on ED respiratory visit data on a provincial basis. These call complaints are a timely, useful and representative data stream that shows promise for integration into a real-time syndromic surveillance system.
Authors: Cynthia Lucero-Obusan; Carla A Winston; Patricia L Schirmer; Gina Oda; Mark Holodniy Journal: Public Health Rep Date: 2017 Jul/Aug Impact factor: 2.792
Authors: R A Morbey; S Harcourt; R Pebody; M Zambon; J Hutchison; J Rutter; H Thomas; G E Smith; A J Elliot Journal: Epidemiol Infect Date: 2017-04-17 Impact factor: 4.434
Authors: W Katherine Yih; Kathryn S Teates; Allyson Abrams; Ken Kleinman; Martin Kulldorff; Robert Pinner; Robert Harmon; Stanley Wang; Richard Platt Journal: PLoS One Date: 2009-04-17 Impact factor: 3.240