PURPOSE: To estimate and compare reliability of traffic mortality data of the police and the healthcare sector in Arkhangelsk, Russia. METHODS: The study matched traffic mortality data of the police and the regional healthcare statistics centre for the period from 2005 to 2010. Individual investigations of unmatched cases were performed, and the underlying causes of the non-matches were established. The obtained distribution of non-matches by causes served as basis for estimating the true numbers of traffic fatalities in the two sources, in appliance with corresponding fatality definitions and registration rules. A data accuracy index (DAI) was calculated for each source by using an adapted version of the formula for calculating accuracy of a diagnostic test. This was used as a measure for data reliability. Time trends in annual DAIs were estimated for each source by χ(2)-test for linear trend. RESULTS: During the 6-year period, the police and the healthcare statistics centre registered 217 and 237 traffic fatalities in Arkhangelsk, respectively. Matching of data from the two sources resulted in 162 matched cases, 55 unmatched cases in the police data, and 75 unmatched cases in the healthcare data. More than a half (56%) of the non-matches were attributed to incompatibility of the definitions in the two data registration systems; 39% were attributed to failures in the healthcare data. Other non-matches were due to scarce identifying information (2%) or were not classifiable (2%). None of the non-matches were clearly attributable to failures in the police data. The 6-year DAI was 98% for the police data and 80% for the healthcare data. The DAI for the police data was stable over 2005-2010 (ranging from 96% to 100%). The DAI for the healthcare data increased from 66% in 2005 to 98% in 2010 (Ptrend<0.001). CONCLUSION: The findings suggest that traffic mortality data of the police were more reliable, compared to the healthcare data. However, reliability of the healthcare data was improving during the study period.
PURPOSE: To estimate and compare reliability of traffic mortality data of the police and the healthcare sector in Arkhangelsk, Russia. METHODS: The study matched traffic mortality data of the police and the regional healthcare statistics centre for the period from 2005 to 2010. Individual investigations of unmatched cases were performed, and the underlying causes of the non-matches were established. The obtained distribution of non-matches by causes served as basis for estimating the true numbers of traffic fatalities in the two sources, in appliance with corresponding fatality definitions and registration rules. A data accuracy index (DAI) was calculated for each source by using an adapted version of the formula for calculating accuracy of a diagnostic test. This was used as a measure for data reliability. Time trends in annual DAIs were estimated for each source by χ(2)-test for linear trend. RESULTS: During the 6-year period, the police and the healthcare statistics centre registered 217 and 237 traffic fatalities in Arkhangelsk, respectively. Matching of data from the two sources resulted in 162 matched cases, 55 unmatched cases in the police data, and 75 unmatched cases in the healthcare data. More than a half (56%) of the non-matches were attributed to incompatibility of the definitions in the two data registration systems; 39% were attributed to failures in the healthcare data. Other non-matches were due to scarce identifying information (2%) or were not classifiable (2%). None of the non-matches were clearly attributable to failures in the police data. The 6-year DAI was 98% for the police data and 80% for the healthcare data. The DAI for the police data was stable over 2005-2010 (ranging from 96% to 100%). The DAI for the healthcare data increased from 66% in 2005 to 98% in 2010 (Ptrend<0.001). CONCLUSION: The findings suggest that traffic mortality data of the police were more reliable, compared to the healthcare data. However, reliability of the healthcare data was improving during the study period.
Authors: Alexander V Kudryavtsev; Odd Nilssen; Johan Lund; Andrej M Grjibovski; Børge Ytterstad Journal: Int J Circumpolar Health Date: 2012-09-24 Impact factor: 1.228