The identification of artefacts in reporting of drug-induced deaths using structural breaks analysis of time series statistics
Jazyk angličtina Země Austrálie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
33880791
DOI
10.1111/dar.13296
Knihovny.cz E-zdroje
- Klíčová slova
- drug-induced deaths, drug-related mortality, overdose, structural change, time series,
- MeSH
- artefakty MeSH
- časové faktory MeSH
- lidé MeSH
- opioidní analgetika MeSH
- předávkování léky * MeSH
- stimulanty centrálního nervového systému * MeSH
- zakázané drogy * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- opioidní analgetika MeSH
- stimulanty centrálního nervového systému * MeSH
- zakázané drogy * MeSH
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.
Department of Public Health Sciences University of Connecticut School of Medicine Farmington USA
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