Journal of clinical epidemiology · 2009
Unexplained differences between hospital and mortality data indicated mistakes in death certification: an investigation of 1,094 deaths in Sweden during 1995.
СтатьяМногоцентровое исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Johansson Lars Age, Björkenstam Charlotte, Westerling Ragnar
Аннотация
OBJECTIVE: Mortality statistics are important for epidemiological research. We examine if discrepancies between death certificate (DC) and hospital discharge condition (HDC) indicate certification errors.
STUDY DESIGN AND SETTING: From 39,872 hospital deaths in Sweden in 1995, we randomly selected 600 "cases," where DC and HDC were incompatible, and 600 compatible "controls," matched on sex, age, and underlying cause of death. We obtained case summaries for 1,094 (91%) of these. Using a structured protocol, we assessed the accuracy of DCs.
RESULTS: Regression analysis indicated diagnostic group and "case" or "control" as the variables that most affected the accuracy. Malignant neoplasm "controls" had the highest accuracy (92%), and benign and unspecified tumor "cases," the lowest (20%). For all diagnostic groups except one, compatible "controls" had better accuracy than incompatible "cases." The exception, chronic obstructive lung disease, had low accuracy for both "cases" (54%) and "controls" (52%).
CONCLUSION: Incompatibility between DC and HDC indicates a greater risk of certification errors. For some diagnostic groups, however, DCs are often inaccurate even when DC and HDC are compatible. By requesting additional information on incompatible cases and all deaths in high-risk diagnostic groups, producers of mortality statistics could improve the accuracy of the statistics.
STUDY DESIGN AND SETTING: From 39,872 hospital deaths in Sweden in 1995, we randomly selected 600 "cases," where DC and HDC were incompatible, and 600 compatible "controls," matched on sex, age, and underlying cause of death. We obtained case summaries for 1,094 (91%) of these. Using a structured protocol, we assessed the accuracy of DCs.
RESULTS: Regression analysis indicated diagnostic group and "case" or "control" as the variables that most affected the accuracy. Malignant neoplasm "controls" had the highest accuracy (92%), and benign and unspecified tumor "cases," the lowest (20%). For all diagnostic groups except one, compatible "controls" had better accuracy than incompatible "cases." The exception, chronic obstructive lung disease, had low accuracy for both "cases" (54%) and "controls" (52%).
CONCLUSION: Incompatibility between DC and HDC indicates a greater risk of certification errors. For some diagnostic groups, however, DCs are often inaccurate even when DC and HDC are compatible. By requesting additional information on incompatible cases and all deaths in high-risk diagnostic groups, producers of mortality statistics could improve the accuracy of the statistics.