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Aim: The aim was to investigate the possibility to evaluate the mortality pattern in a community intervention programme against cardiovascular disease by official death certificates. Methods: For all deceased in the intervention area (Norsjö), the accuracy of the official death certificates were compared with matched controls in the rest of Västerbotten. The official causes of death were compared with new certificates, based on the last clinical record, issued by three of the authors, and coded by one of the authors, all four accordingly blinded. Results: The degree of agreement between the official underlying causes of death in “cardiovascular disease” (CVD) and the re-evaluated certificates was not found to differ between Norsjö and the rest of Västerbotten. The agreement was 87% and 88% at chapter level, respectively, but only 55% and 55% at 4-digit level, respectively. The reclassification resulted in a 1% decrease of “cardiovascular deaths” in both Norsjö and the rest of Västerbotten. Conclusions: The disagreements in the reclassification of cause of death were equal but large in both directions. The official death certificates should be used with caution to evaluate CVD in small community intervention programmes, and restricted to the chapter level and total populations.

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.

Statistics on causes of death are important for epidemiologic research. Studies that evaluate the source data often give conflicting results, which raise questions about comparability and validity of methods.For 44 recent evaluation studies we examined the methods employed and assessed the reproducibility.Thirty studies stated who reviewed the source data. Six studies reported reliability tests. Twelve studies included all causes of death, but none specified criteria for identifying the underlying cause when several, etiologically independent conditions were present. We assessed these as not reproducible. Of 32 studies that focussed on a specific condition, 21 provided diagnostic criteria such that the verification of the focal diagnosis is reproducible. Of 16 that discussed the difference between dying "with" and "from" a condition, eight described how competing causes had been handled. For these eight, the selection of a principal cause is reproducible, but in three the selection strategy conflicts with the international instructions issued by the World Health Organization.Methods and criteria are often insufficiently described. When described, they sometimes disagree with the international standard. Explicit descriptions of methods and criteria would contribute to methodologic improvement and would allow readers to assess the generalizability of the conclusions.

Background and Objective Physicians may find it confusing to decide whether to report diagnoses in part I or part II of the death certificate. The aim of this study was to contrast differences in diabetes mortality through a comparison of physicians’ habits in reporting diabetes in part I of death certification among Taiwan, Australia, and Sweden. Methods A cross-sectional, intercountry comparison study. We calculated the proportion of deaths with mention of diabetes in which diabetes was reported in part I of the death certificate and the proportion of deaths with mention of diabetes in which diabetes was selected as underlying cause of death. Results We found that half of the differences in reported diabetes mortality among Taiwan, Australia, and Sweden were due to differences in reporting deaths with mention of diabetes anywhere on the certificate, and half due to differences in proportion of deaths with mention of diabetes in which diabetes was reported in part I of the death certificate. Conclusion Differences in the reporting of diabetes in part I of the death certificate among physicians in Taiwan, Australia, and Sweden was one of the factors that affected differing reported diabetes mortality in Taiwan, Australia, and Sweden.

In 1981, the registration routines of the Swedish cause-of-death register were adjusted. The aim of this study was to assess what influence these changes in registration practice might have had on the cause-of-death trends after 1981. The Eighth Revision of the International Classification of Diseases (ICD-8) was used throughout the study period (1976-1985). Significant changes in the registered number of cases were found in 13 of the 18 diagnostic groups scrutinized. Four main types of outcomes were observed: (a) the number of underlying causes increased while the number of contributing causes decreased or vice versa; (b) the number of both underlying and contributory causes changed in the same direction, due to the transfer of a diagnostic group from one ICD category to another; (c) the number of both underlying and contributory causes changed in the same direction, but not due to the transfer of a diagnostic group; or (d) the number of either underlying or contributory causes changed, but not both. In general, the altered registration practice led to more conditions that are often considered as terminal complications to other diseases being registered as the underlying cause of death. While most of the 1981 instructions meant a more literal application of the ICD-8, those concerning cardiac valvular diseases deviated substantially from it. We conclude that (a) important changes in registration practice may occur at any point in time, and not only in connection with the implementation of a new version of the ICD; and (b) national adaptations of the ICD coding instructions may amount to a reversal of the instructions included in the ICD manuals. These findings must be considered when comparing cause-of-death statistics from different countries, and both underlying and contributing cause-of-death statistics should be considered in such analyses of cause-of-death trends.

The new standard of cause of death classification is an automated selection of the underlying cause of death using the international software Automated Classification of Medical Entities (ACME). Norwegian mortality rates are, however, based on manual classification of deaths. The aim of this study was to investigate how the use of ACME would influence Norwegian prostate cancer mortality rates. A previously described cohort of Norwegian prostate cancer patients deceased during 1996 was applied. Multiple causes of death data based on information from death certificates, autopsies and queries was coded according to ACME specifications, thereby ACME selected the underlying cause of death. In addition, the underlying cause of death that originally was manually classified for the official mortality statistics was retrieved from Statistics Norway in all cases. Age-standardized prostate cancer mortality rates (world population) per 100,000 person-years were calculated. A total of 2012 cases were included. On the basis of ACME classification, the age-standardized prostate cancer mortality rate in Norway for 1996 would have been 24.4 (95% confidence interval: 22.9-26.0) as compared with the rate based on manual classification for the official mortality statistics of 24.9 (95% confidence interval: 23.4-26.5). Thus, automated classification by ACME does not significantly influence the age-adjusted Norwegian prostate cancer mortality rate for the year 1996. There is reason to assume that the use of manual classification of deaths is not a major explanation of the high prostate cancer mortality rates in Norway.

Study objective: The quality of mortality statistics is important for epidemiological research. Considerable discrepancies have been reported between death certificates and corresponding hospital discharge records. This study examines whether differences between the death certificate9s underlying cause of death and the main condition from the final hospital discharge record can be explained by differences in ICD selection procedures. The authors also discuss the implications of unexplained differences for mortality data quality. Design: Using ACME, a standard software for the selection of underlying cause of death, the compatibility between the underlying cause of death and the final main condition was examined. The study also investigates whether data available in the hospital discharge record, but not reported on the death certificate, influence the selection of the underlying cause of death. Setting: Swedish death certificates for 1995 were linked to the national hospital discharge register. The resulting database comprised 69 818 people who had been hospitalised during their final year of life. Main results: The underlying cause of death and the main condition differed at Basic Tabulation List level in 54% of the deaths. One third of the differences could not be explained by ICD selection procedures. Adding hospital discharge data changed the underlying cause in 11% of deaths. For some causes of death, including medical misadventures and accidental falls, the effect was substantial. Conclusion: Most differences between underlying cause of death and final main condition can be explained by differences in ICD selection procedures. Further research is needed to investigate whether unexplained differences indicate lower data quality.

The aims of the study were: (i) to identify trends in the underlying cause-of-death statistics that are due to changes in the coders' selection and coding of causes, and (ii) to identify changes in the coders' documented registration principles that can explain the observed trends in the statistics. 31 Basic Tabulation List categories from the Swedish national cause-of-death register for 1970–1988 were studied. The coders' tendency to register a condition as the underlying cause of death (the underlying cause ratio) was estimated by dividing the occurrence of the condition as underlying cause (the underlying cause rate) with the total registration of the condition (the multiple cause rate). When the development of the underlying cause rate series followed more closely the underlying cause ratio series than the multiple cause rate series, and a corresponding change in the registration rules could be found, the underlying cause rate trend was concluded to be due to changes in the coders' tendency to register the condition. For thirteen categories (fourteen trends), the trends could be explained by changes in the coders' interpretation practice: five upward, four insignificant, and five downward trends. In addition, for three categories the trends could be explained by new explicit ICD-9 rules.

Background In the age of big data in healthcare, automated comparison of medical diagnoses in large scale databases is a key issue. Our objectives were: 1) to formally define and identify cases of independence between last hospitalization main diagnosis (MD) and death registry underlying cause of death (UCD) for deceased subjects hospitalized in their last year of life; 2) to study their distribution according to socio-demographic and medico-administrative variables; 3) to discuss the interest of this method in the specific context of hospital quality of care assessment. Methods 1) Elaboration of an algorithm comparing MD and UCD, relying on Iris, a coding system based on international standards. 2) Application to 421,460 beneficiaries of the general health insurance regime (which covers 70% of French population) hospitalized and deceased in 2008–2009. Results 1) Independence, was defined as MD and UCD belonging to different trains of events leading to death 2) Among the deaths analyzed automatically (91.7%), 8.5% of in-hospital deaths and 19.5% of out-of-hospital deaths were classified as independent. Independence was more frequent in elder patients, as well as when the discharge-death time interval grew (14.3% when death occurred within 30 days after discharge and 27.7% within 6 to 12 months) and for UCDs other than neoplasms. Conclusion Our algorithm can identify cases where death can be considered independent from the pathology treated in hospital. Excluding these deaths from the ones allocated to the hospitalization process could contribute to improve post-hospital mortality indicators. More generally, this method has the potential of being developed and used for other diagnoses comparisons across time periods or databases.