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Sensitivity and specificity of administrative mortality data for identifying prescription opioid–related deaths


Background — Comprehensive systems for surveillance of prescription opioid-related harms provide clear evidence that deaths from prescription opioids have increased dramatically in the United States. However, prescription opioid-related harms in Canada are not systematically monitored. In light of this growing public health crisis, accessible, nation-wide data sources to examine prescription opioid-related harms in Canada are desperately needed. We examine the performance of several algorithms to identify prescription opioid-related deaths in Vital Statistics data against a gold standard.

Methods — We used data abstracted from the Office of the Chief Coroner of Ontario to identify all prescription opioid-related deaths in Ontario from January 2003 to December 2010. We identified prescription opioid-related deaths in Vital Statistics death data in 2010 using five different algorithms. We selected the algorithm with the highest sensitivity and a positive predictive value above 80% as the optimal algorithm to identify prescription opioid-related deaths.

Results — Four out of five of the algorithms had positive predictive values above 80%. The algorithm with the highest sensitivity (75%) in 2010 and improved slightly in its predictive performance from 2003 to 2010.

Interpretation — In the absence of existing systems for monitoring prescription opioid-related harms in Canada, readily-available national Vital Statistics mortality data can be used to study prescription opioid-related mortality with considerable accuracy. Despite some limitations, the use of these data may facilitate the implementation of national surveillance and monitoring strategies.



Gladstone E, Smolina K, Morgan SG, Fernandes KA, Martins D, Gomes T. CMAJ. 2016; 188(4):E67-72. Epub 2015 Nov 30.

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