Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Introduction: Drug-related mortality is a key epidemiological indicator that is collected nationally and internationally. Significant efforts were made in 2006-2007 to improve the quality of data concerning drug-related mortality in the Czech Republic. The aim of this article is to identify the effect of a quality improvement project on the drug-induced mortality data reported in the General Mortality Registry (GMR), and to demonstrate how to identify, quantify and interpret changes in drug-induced mortality based on the example of the Czech Republic.
Methods: We extracted data on illicit drug-induced deaths from the Czech Republic GMR and Special Mortality registry (SMR) for the years between 2004 and 2012, and aggregated monthly and quarterly time series. We applied a new procedure to identify structural breakpoints in time series based on dating structural changes in standard linear regression models.
Results: In the GMR, breakpoints were identified in three time series: (i) opioid-related deaths; (ii) other stimulant-related deaths; and (iii) total drug-induced deaths. In the SMR, the structural breaks were identified for opioids, volatile substances and selection D time series. In each of these time series, the analysis identified a decrease in the intercepts in the different segments.
Discussion And Conclusions: The structural breaks identified and quantified in the GMR time series were plausibly caused by the quality improvement efforts that started in 2006. These results demonstrate that it is critical for the analysis and use of drug mortality data collected in the registries to identify practice changes in the relevant registries, to quantify their influence and to adjust mortality estimates accordingly.
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http://dx.doi.org/10.1111/dar.13296 | DOI Listing |
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