We found considerable differences in the prevalence of chronic diseases between German health insurance funds that remained after controlling for age and sex, and even after adjustment for further health-related variables. Further methodological studies are urgently needed to assess strengths and weaknesses of German claim data.

Among the direct medical costs of childhood diabetes, the highest economic burden was due to glucose self measurement, hospitalization, and insulin. The costs were considerably higher in adolescents with poor metabolic control, especially the costs for hospitalization. Outpatient education programs in pediatric diabetes care, in particular targeting children with poor metabolic control, should be encouraged, including their evaluation with respect to cost and effectiveness.

A high prevalence of functional bowel disorders was found in this population-based study in Germany. Only about half of the subjects reported health care seeking due to their bowel disorders. Self-medication with over-the-counter agents was frequently performed.

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Mainly because of the large number of people affected and associated significant health policy implications, the Robert Koch Institute (RKI) is developing a public health surveillance system using diabetes as an example. In a first step to ensure long-term and comparable data collection and establish efficient surveillance structures, the RKI has defined a set of relevant indicators for diabetes surveillance. An extensive review of the available literature followed by a structured process of consensus provided the basis for a harmonised set of 30 core and 10 supplementary indicators. They correspond to the following four fields of activity: (1) reducing diabetes risk, (2) improving diabetes early detection and treatment, (3) reducing diabetes complications, (4) reducing the disease burden and overall costs of the disease. In future, in addition to the primary data provided by RKI health monitoring diabetes surveillance needs to also consider the results from secondary data sources. Currently, barriers to accessing this data remain, which will have to be overcome, and gaps in the data closed. The RKI intentends to continuously update this set of indicators and at some point apply it also to further chronic diseases with high public health relevance.

Background Risk prediction with the GRACE risk model is guideline-recommended clinical practice in acute coronary syndrome (ACS). However, more modern risk models such as ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines) and National Cardiovascular Data Registry (NCDR) risk models are available. We aimed to compare these models to the established GRACE risk model in ACS. Methods and results In-hospital mortality was retrospectively assessed in 1,138 patients undergoing cardiac catheterization for Non-ST-Elevation Myocardial Infarction (NSTEMI, 566 patients, 70.7% male) or ST-Elevation Myocardial Infarction (STEMI, 572 patients, 69.1% male) at a German University Hospital from 2014 to 2017. In-hospital mortality was 14.7% for STEMI and 3.7% for NSTEMI, respectively. GRACE, ACTION and NCDR risk models for prediction of in-hospital mortality were calculated for individual patients, 0.75% missing data were imputed. ACTION risk model showed a good discrimination of risk (c-index 0.85, 95% confidence interval (CI) 0.83–0.87) with a slight numerical advantage in NSTEMI (c-index 0.92, 95% CI 0.86–0.98) over STEMI patients (c-index 0.83, 95% CI 0.79–0.88). The NCDR risk model showed comparable performance in the overall cohort (c-index 0.86, 95% CI 0.84–0.88; NCDR vs. ACTION p=0.4097), also with superior performance in NSTEMI (c-index 0.89, 95% CI 0.86–0.91) vs. STEMI (c-index 0.81, 95% CI 0.78–0.84). The GRACE risk model showed significantly worse performance in the overall cohort (c-index 0.76, 95% CI 0.74–0.79; vs ACTION p<0.0001; vs. NCDR p<0.0001) and in STEMI patients (c-index 0.72, 95% CI 0.69–0.76; vs ACTION p<0.0001; vs. NCDR p=0.0018). In NSTEMI patients, GRACE discrimination performance was comparable to NCDR (c-index 0.87, 95% CI 0.84–0.90, p=0.73), but still inferior to ACTION (p=0.04). The ACTION risk model showed a good calibration whereas NCDR and GRACE models lacked accuracy in our cohort. Conclusion In a contemporary German patient population with acute coronary syndrome, ACTION and NCDR risk models outperform the established GRACE risk model for prediction of in-hospital mortality. This performance difference was more pronounced in STEMI than in NSTEMI. Funding Acknowledgement Type of funding source: None