Knowledge, competencies and attitudes regarding external post-mortem physical examination: A survey among German post-graduate trainees in general practice

[Cause of death statistics-how to avoid misinterpretation of mortality data]

National mortality registers provide important data for monitoring population health. Analyses of cardiovascular mortality in particular-and especially mortality from coronary heart disease-are frequently the basis for conclusions about the quality of healthcare and prevention. To be able to interpret disease-specific mortality differences between countries and changes in mortality over time, it is necessary to know the basics of monocausal cause-of-death statistics and the associated limitations in comparative statements.Conclusions from disease-specific mortality data can be problematic due to the highly subjective selection of diseases that are entered on a death certificate after a post-mortem examination. In death certification, unawareness of the different "roles" of specific diseases-known at the time of death-within the causal chain leading to death can result in incomplete death certificates as a data basis for mortality statistics. Comparisons of disease-specific mortality rates are difficult due to different proportions of non-informative-including unknown-causes of death and due to country-specific preferences for which diseases are recorded on a death certificate-especially in the prevalence of multimorbidity. A population's morbidity is therefore only reflected to a limited extent by mortality rates. Conceptual ambiguities with regard to the concepts of lethality and mortality when describing mortality rates can also lead to erroneous conclusions.Training of medical staff on how to complete a death certificate and the introduction of an electronic death certificate can improve the quality of mortality data. Irrespective of this, knowing potential pitfalls when analyzing mortality data will improve the quality of health reporting.

[The Logic Model - a rationale for an encompassing evaluation framework of the German Competence Centers for Postgraduate Medical Education in general practice]

BACKGROUND

The Competence Centers for Postgraduate Medical Education (KW) established throughout Germany represent complex programs to increase the efficiency and quality of postgraduate medical education in general practice. So-called Logic Models serve as the framework for evaluations and quality management processes of complex programs in many areas. The aim of this article is to develop such a model, using the example of the Competence Center in Baden-Württemberg (KWBW) in order to structure its complex program logic and use it as a framework for future evaluations and quality management processes.

METHODS

The adaptation of the Logic Model to the KWBW took place in an informal, nominal group process with employees and participants of the program.

RESULTS

We identified 76 core elements of the KWBW. These core elements were classified in one of the five pillars of the Logic Model (input, activity, output, outcome and impact) and categorized according to fields of action and target groups.

DISCUSSION

The Logic Model, which was developed using the KWBW as an example, identifies and structures important core elements of a complex postgraduate medical training program for the first time. It seems to be well suited for visualizing the internal logic of this complex program and the interaction of the various elements within the KWBW. It can thus be used as the basis for a comprehensive and systematic evaluation concept and for quality assurance.

CONCLUSION

The model is also a prerequisite for comparative research questions of other university programs for postgraduate medical education and thus offers an opportunity for cooperative development efforts. This article therefore contributes to promoting quality in continuing medical training.

Decline of coronary heart disease mortality is strongly effected by changing patterns of underlying causes of death: an analysis of mortality data from 27 countries of the WHO European region 2000 and 2013

Mortality rates for coronary heart disease (CHD) experience a longstanding decline, attributed to progress in prevention, diagnostics and therapy. However, CHD mortality rates vary between countries. To estimate whether national patterns of causes of death impact CHD mortality, data from the WHO “European detailed mortality database” for 2000 and 2013 for populations aged ≥ 80 years was analyzed. We extracted mortality rates for total mortality, cardiovascular diseases, neoplasms, dementia and ill-defined causes. We calculated proportions of selected causes of death among all deaths, and proportions of selected cardiovascular causes among cardiovascular deaths. CHD mortality rates were recalculated after re-coding ill-defined causes of death. Association between CHD mortality rates and proportions of CHD deaths was estimated by population-weighted linear regression. National patterns of causes of death were divers. In 2000, CHD was assigned as cause of death in 13–53% of all cardiovascular deaths. Until 2013, this proportion changed between − 65% (Czech Republic) and + 57% (Georgia). Dementia was increasingly assigned as underlying cause of death in Western Europe, but rarely in eastern European countries. Ill-defined causes accounted for between < 1% and 53% of all cardiovascular deaths. CHD mortality rates were closely linked to a countries’ proportion of cardiovascular deaths assigned to CHD (R² = 0.95 for 2000 and 0.99 for 2013). We show that CHD mortality is considerably influenced by national particularities in certifying death. Changes in CHD mortality rates reflect changes in certifying competing underlying causes of death. This must be accounted for when discussing reasons for the CHD mortality decline.