JOURNAL ARTICLE

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

Emilie Gladstone, Kate Smolina, Steven G Morgan, Kimberly A Fernandes, Diana Martins, Tara Gomes
Canadian Medical Association Journal: CMAJ 2016 March 1, 188 (4): E67-72
26622006

BACKGROUND: Comprehensive systems for surveilling prescription opioid-related harms provide clear evidence that deaths from prescription opioids have increased dramatically in the United States. However, these harms are not systematically monitored in Canada. In light of a growing public health crisis, accessible, nationwide data sources to examine prescription opioid-related harms in Canada are needed. We sought to examine the performance of 5 algorithms to identify prescription opioid-related deaths from vital statistics data against data abstracted from the Office of the Chief Coroner of Ontario as a gold standard.

METHODS: We identified all prescription opioid-related deaths from Ontario coroners' data that occurred between Jan. 31, 2003, and Dec. 31, 2010. We then used 5 different algorithms to identify prescription opioid-related deaths from vital statistics death data in 2010. We selected the algorithm with the highest sensitivity and a positive predictive value of more than 80% as the optimal algorithm for identifying prescription opioid-related deaths.

RESULTS: Four of the 5 algorithms had positive predictive values of more than 80%. The algorithm with the highest sensitivity (75%) in 2010 improved slightly in its predictive performance from 2003 to 2010.

INTERPRETATION: In the absence of specific systems for monitoring prescription opioid-related deaths in Canada, readily available national vital statistics data can be used to study prescription opioid-related mortality with considerable accuracy. Despite some limitations, these data may facilitate the implementation of national surveillance and monitoring strategies.

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