954 resultados para Sample selection


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Objective: To assess extent of coder agreement for external causes of injury using ICD-10-AM for injury-related hospitalisations in Australian public hospitals. Methods: A random sample of 4850 discharges from 2002 to 2004 was obtained from a stratified random sample of 50 hospitals across four states in Australia. On-site medical record reviews were conducted and external cause codes were assigned blinded to the original coded data. Code agreement levels were grouped into the following agreement categories: block level, 3-character level, 4-character level, 5th-character level, and complete code level. Results: At a broad block level, code agreement was found in over 90% of cases for most mechanisms (eg, transport, fall). Percentage disagreement was 26.0% at the 3-character level; agreement for the complete external cause code was 67.6%. For activity codes, the percentage of disagreement at the 3-character level was 7.3% and agreement for the complete activity code was 68.0%. For place of occurrence codes, the percentage of disagreement at the 4-character level was 22.0%; agreement for the complete place code was 75.4%. Conclusions: With 68% agreement for complete codes and 74% agreement for 3-character codes, as well as variability in agreement levels across different code blocks, place and activity codes, researchers need to be aware of the reliability of their specific data of interest when they wish to undertake trend analyses or case selection for specific causes of interest.

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Police services in a number of Australian states and overseas jurisdictions have begun to implement or consider random road-side drug testing of drivers. This paper outlines research conducted to provide an estimate of the extent of drug driving in a sample of Queensland drivers in regional, rural and metropolitan areas. Oral fluid samples were collected from 2657 Queensland motorists and screened for illicit substances including cannabis (delta 9 tetrahydrocannibinol [THC]), amphetamines, ecstasy, and cocaine. Overall, 3.8% of the sample (n = 101) screened positive for at least one illicit substance, although multiple drugs were identified in a sample of 23 respondents. The most common drugs detected in oral fluid were ecstasy (n = 53), and cannabis (n = 46) followed by amphetamines (n = 23). A key finding was that cannabis was confirmed as the most common self-reported drug combined with driving and that individuals who tested positive to any drug through oral fluid analysis were also more likely to report the highest frequency of drug driving. Furthermore, a comparison between drug vs. drink driving detection rates for one region of the study, revealed a higher detection rate for drug driving (3.8%) vs. drink driving (0.8%). This research provides evidence that drug driving is relatively prevalent on Queensland roads, and may in fact be more common than drink driving. This paper will further outline the study findings’ and present possible directions for future drug driving research.