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Zusammenfassung Hintergrund Diabetes mellitus ist eine Erkrankung von hoher Public-Health-Relevanz. Zur Schätzung der zeitlichen Entwicklung der Prävalenz kommen auch Routinedaten der gesetzlichen Krankenversicherung zum Einsatz. In diesen primär zu Abrechnungszwecken generierten Daten stellt die Definition von Erkrankungen eine besondere methodische Herausforderung dar. In der vorliegenden Studie wurde ein Algorithmus zur Unterscheidung von Typ-1- und Typ-2-Diabetes für die Analyse von Routinedaten entwickelt. Methodik Datengrundlage ist eine alters- und geschlechtsstratifizierte Zufallsstichprobe der Versicherten der Barmer mit einer durchgehenden Versicherungsdauer von 2010 bis 2018 in der Größenordnung von 1% der deutschen Bevölkerung. Ein Diabetes wurde im Berichtsjahr 2018 definiert als Dokumentation (1) einer gesicherten ICD-Diagnose E10.- bis E14.- im ambulanten Sektor in mindestens 2 Quartalen, (2) einer gesicherten ICD-Diagnose E10.- bis E14.- in einem Quartal mit einer zusätzlichen Antidiabetikaverordnung (ATC-Codes A10) oder (3) einer ICD-Diagnose E10.- bis E14.- im stationären Sektor, dem ambulanten Operieren oder der Arbeitsunfähigkeit. Anhand der ICD-Diagnosen E10.- bis E14.- und der verordneten Arzneimittel, unterschieden nach Insulin und anderen Antidiabetika, wurden die Personen einem Diabetestypen zugeordnet. Nicht eindeutige oder widersprüchliche Konstellationen wurden anhand des Alters, der Häufigkeit sowie überjährigen Betrachtung der Diagnosedokumentation zugeordnet. Die Einschreibung in ein Disease-Management-Programm wurde in einer Sensitivitätsanalyse berücksichtigt. Ergebnisse Die Prävalenz des dokumentierten Diabetes in der Stichprobe der Barmer betrug im Jahr 2018 8,8%. Anhand des Algorithmus konnten 98,5% der Personen mit Diabetes dem Typ-1-Diabetes (5,5%), dem Typ-2-Diabetes (92,6%) oder einer weiteren spezifischen Diabetesform (0,43%) zugeordnet werden. Somit ergaben sich für das Jahr 2018 Prävalenzen von 0,48% für den Typ-1-Diabetes und 8,1% für den Typ-2-Diabetes. Schlussfolgerung Bereits anhand weniger Merkmale wie Diagnosen, Arzneimittelverordnung und dem Alter lässt sich die große Mehrzahl der Personen mit Diabetes einem Typ zuordnen. In weiterführenden Studien sollte im Abgleich mit Primärdaten die externe Validität geprüft werden. So ermöglicht der Algorithmus die Auswertung wichtiger epidemiologischer Kennzahlen und der Häufigkeit von Folge- und Begleiterkrankungen auf Basis von Routinedaten differenziert nach Typ-1- und Typ-2-Diabetes, welche in der Surveillance des Diabetes zukünftig berücksichtigt werden sollen.

Zusammenfassung Am Robert Koch-Institut wurde ein indikatorbasiertes Diabetes-Surveillance-System für Deutschland aufgebaut. Auf Basis bundesweiter Primär- und Sekundärdaten werden 40 zentrale Indikatoren bzw. Indikatorgruppen mit Blick auf Risikofaktoren, Häufigkeit, Versorgung und Folgen des Diabetes abgebildet. Die Ergebnisse werden über eine Webseite und weitere nutzerorientierte Ergebnisformate bereitgestellt. Der Ausbau zu einer Surveillance nichtübertragbarer Krankheiten (NCD-Surveillance) ist geplant.

ObjectivesTo investigate whether the risk of developing an incident autoimmune disease is increased in patients with previous COVID-19 disease compared to people without COVID-19.MethodA cohort was selected from German routine health care data covering 38.9 million individuals. Based on documented diagnoses, we identified individuals with polymerase chain reaction (PCR)-confirmed COVID-19 through December 31, 2020. Patients were matched 1:3 to control patients without COVID-19. Both groups were followed up until June 30, 2021. We used the four quarters preceding the index date until the end of follow-up to analyze the onset of autoimmune diseases during the post-acute period. Incidence rates (IR) per 1000 person-years were calculated for each outcome and patient group. Poisson models were deployed to estimate the incidence rate ratios (IRRs) of developing an autoimmune disease conditional on a preceding diagnosis of COVID-19.ResultsIn total, 641,704 patients with COVID-19 were included. Comparing the incidence rates in the COVID-19 (IR=15.05, 95% CI: 14.69-15.42) and matched control groups (IR=10.55, 95% CI: 10.25-10.86), we found a 42.63% higher likelihood of acquiring autoimmunity for patients who had suffered from COVID-19. This estimate was similar for common autoimmune diseases, such as Hashimoto thyroiditis, rheumatoid arthritis, or Sjögren syndrome. The highest IRR was observed for autoimmune disease of the vasculitis group. Patients with a more severe course of COVID-19 were at a greater risk for incident autoimmune diseases.ConclusionsSARS-CoV-2 infection is associated with an increased risk of developing new-onset autoimmune diseases after the acute phase of infection.

BACKGROUND: Diabetes mellitus (DM) is a major risk factor for complications of pregnancy. Based on information for all inpatient births in Germany, we assessed the risks for selected pregnancy complications in women with pregestational diabetes mellitus (preDM) or gestational diabetes mellitus (GDM). METHOD: The underlying data comprised all singleton births contained in the inpatient perinatal medicine quality assurance statistics for the years 2013–2019. The frequencies of premature birth, elevated birth weight (large for gestational age, LGA), cesarean section, transfer of the newborn to the perinatal unit, and stillbirth were stratified by maternal age and diabetes status (preDM, GDM, no DM). Poisson regression was used to calculate the relative risks (RR) with 95% confidence intervals (95% CI) for the whole period and for each individual year in women with preDM or GDM relative to women without DM. RESULTS: Among the 4 991 275 singleton births included, GDM was documented in 283 210 (5.7%) and preDM in 46 605 (0.93%) cases. GDM was associated with higher RR for premature birth (1.13 [1.12; 1.15]), LGA (1.57 [1.55; 1.58]), cesarean section (1.26 [1.25; 1.27]), and transfer of the newborn (1.54 [1.52; 1.55]). These associations were even stronger in women with preDM: premature birth (2.13 [2.08; 2.18]), LGA (2.72 [2.67; 2.77]), cesarean section (1.62 [1.60; 1.64]), transfer of the newborn (2.61 [2.56; 2.66]). PreDM increased the risk of stillbirth (RR: 2.34 [2.11; 2.59]); GDM was associated with a lower risk (RR: 0.67 [0.62; 0.72]). For women with preDM, the risk of pregnancy complications increased over the study period. CONCLUSION: GDM and preDM are still associated with elevated risks of pregnancy complications. In the case of preDM, the risks may be attributable to the fact that the hyperglycemia is more severe and is already present before conception. Continuous monitoring should include risk factors in pregnant women and care-relevant aspects.

BACKGROUND: Summary measures such as disability-adjusted life years (DALY) are becoming increasingly important for the standardized assessment of the burden of disease due to death and disability. The BURDEN 2020 pilot project was designed as an independent burden-of-disease study for Germany, which was based on nationwide data, but which also yielded regional estimates. METHODS: DALY is defined as the sum of years of life lost due to death (YLL) and years lived with disability (YLD). YLL is the difference between the age at death due to disease and the remaining life expectancy at this age, while YLD quantifies the number of years individuals have spent with health impairments. Data are derived mainly from causes of death statistics, population health surveys, and claims data from health insurers. RESULTS: In 2017, there were approximately 12 million DALY in Germany, or 14 584 DALY per 100 000 inhabitants. Conditions which caused the greatest number of DALY were coronary heart disease (2321 DALY), low back pain (1735 DALY), and lung cancer (1197 DALY). Headache and dementia accounted for a greater disease burden in women than in men, while lung cancer and alcohol use disorders accounted for a greater disease burden in men than in women. Pain disorders and alcohol use disorders were the leading causes of DALY among young adults of both sexes. The disease burden rose with age for some diseases, including cardiovascular diseases, dementia, and diabetes mellitus. For some diseases and conditions, the disease burden varied by geographical region. CONCLUSION: The results indicate a need for age- and sex-specific prevention and for differing interventions according to geographic region. Burden of disease studies yield comprehensive population health surveillance data and are a useful aid to decision-making in health policy.

Diabetes mellitus is a disease of high public health relevance. To estimate the temporal development of prevalence, routine data of statutory health insurances (SHI) are being increasingly used. However, these data are primarily collected for billing purposes and the case definition of specific diseases remains challenging. In this study, we present an algorithm for differentiation of diabetes types analyzing SHI routine data.The basis for the analysis was an age and sex-stratified random sample of persons of the Barmer SHI with a continuous insurance duration from 2010 to 2018 in the magnitude of 1% of the German population. Diabetes was defined in the reporting year 2018, as documentation of (1) a "confirmed" ICD diagnosis E10.- to E14.- in at least two quarters, (2) a "confirmed" ICD diagnosis E10.- to E14.- in one quarter with an additional prescription of an antidiabetic drug (ATC codes A10), or (3) an ICD diagnosis E10.- to E14.- in the inpatient sector, outpatient surgery, or work disability. Individuals were assigned to a diabetes type based on the specific ICD diagnosis E10.- to E14.- and prescribed medications, differentiated by insulin and other antidiabetics. Still unclear or conflicting constellations were assigned on the basis of the persons' age or the frequency and observation of the diagnosis documentation over more than one year. The participation in a disease management program was considered in a sensitivity analysis.The prevalence of documented diabetes in the Barmer sample was 8.8% in 2018. Applying the algorithm, 98.5% of individuals with diabetes could be classified as having type 1 diabetes (5.5%), type 2 diabetes (92.6%), or another specific form of diabetes (0.43%). Thus, the prevalence was 0.48% for type 1 diabetes and 8.1% for type 2 diabetes in 2018.The vast majority of people with diabetes can be classified by their diabetes type on the basis of just a few characteristics, such as diagnoses, drug prescription, and age. Further studies should assess the external validity by comparing the results with primary data. The algorithm enables the analysis of important epidemiological indicators and the frequency of comorbidities based on routine data differentiated by type 1 and type 2 diabetes, which should be considered in the surveillance of diabetes in the future.Diabetes mellitus ist eine Erkrankung von hoher Public-Health-Relevanz. Zur Schätzung der zeitlichen Entwicklung der Prävalenz kommen auch Routinedaten der gesetzlichen Krankenversicherung zum Einsatz. In diesen primär zu Abrechnungszwecken generierten Daten stellt die Definition von Erkrankungen eine besondere methodische Herausforderung dar. In der vorliegenden Studie wurde ein Algorithmus zur Unterscheidung von Typ-1- und Typ-2-Diabetes für die Analyse von Routinedaten entwickelt.Datengrundlage ist eine alters- und geschlechtsstratifizierte Zufallsstichprobe der Versicherten der Barmer mit einer durchgehenden Versicherungsdauer von 2010 bis 2018 in der Größenordnung von 1% der deutschen Bevölkerung. Ein Diabetes wurde im Berichtsjahr 2018 definiert als Dokumentation (1) einer gesicherten ICD-Diagnose E10.- bis E14.- im ambulanten Sektor in mindestens 2 Quartalen, (2) einer gesicherten ICD-Diagnose E10.- bis E14.- in einem Quartal mit einer zusätzlichen Antidiabetikaverordnung (ATC-Codes A10) oder (3) einer ICD-Diagnose E10.- bis E14.- im stationären Sektor, dem ambulanten Operieren oder der Arbeitsunfähigkeit. Anhand der ICD-Diagnosen E10.- bis E14.- und der verordneten Arzneimittel, unterschieden nach Insulin und anderen Antidiabetika, wurden die Personen einem Diabetestypen zugeordnet. Nicht eindeutige oder widersprüchliche Konstellationen wurden anhand des Alters, der Häufigkeit sowie überjährigen Betrachtung der Diagnosedokumentation zugeordnet. Die Einschreibung in ein Disease-Management-Programm wurde in einer Sensitivitätsanalyse berücksichtigt.Die Prävalenz des dokumentierten Diabetes in der Stichprobe der Barmer betrug im Jahr 2018 8,8%. Anhand des Algorithmus konnten 98,5% der Personen mit Diabetes dem Typ-1-Diabetes (5,5%), dem Typ-2-Diabetes (92,6%) oder einer weiteren spezifischen Diabetesform (0,43%) zugeordnet werden. Somit ergaben sich für das Jahr 2018 Prävalenzen von 0,48% für den Typ-1-Diabetes und 8,1% für den Typ-2-Diabetes.Bereits anhand weniger Merkmale wie Diagnosen, Arzneimittelverordnung und dem Alter lässt sich die große Mehrzahl der Personen mit Diabetes einem Typ zuordnen. In weiterführenden Studien sollte im Abgleich mit Primärdaten die externe Validität geprüft werden. So ermöglicht der Algorithmus die Auswertung wichtiger epidemiologischer Kennzahlen und der Häufigkeit von Folge- und Begleiterkrankungen auf Basis von Routinedaten differenziert nach Typ-1- und Typ-2-Diabetes, welche in der Surveillance des Diabetes zukünftig berücksichtigt werden sollen.

Zusammenfassung Hintergrund Datengrundlagen für systematische, fortlaufende Analysen zur Häufigkeit mikrovaskulärer Komplikationen von Diabetes mellitus in Deutschland sind bislang nur begrenzt vorhanden. Erstmals wurde geprüft, ob Versichertendaten aller gesetzlichen Krankenversicherungen (GKV) nach Datentransparenzverordnung hierfür geeignet sind. Methode Analysiert wurden die GKV-Versichertendaten der Berichtsjahre 2012 und 2013. Die Bezugspopulation wurde identifiziert: Versicherte mit Diabetes, definiert als Dokumentation mindestens zweier ambulanter oder einer stationären Diabetesdiagnose gemäß der Internationalen Klassifikation der Krankheiten (ICD-Codes E10–E14). Komplikationen wurden anhand folgender ICD-Codes definiert: Nephropathie (N08.3), Retinopathie (H36.0), Polyneuropathie (G63.2), diabetisches Fußsyndrom (DFS; E10-14.74, E10-14.75), chronische Niereninsuffizienz (N18.-) und Dialysebehandlung (Z49.1, Z49.2, Z99.2). Die Ergebnisse wurden mit Prävalenzschätzungen aus Routine- und Registerdaten in Deutschland und im Ausland verglichen. Ergebnisse Im Jahr 2013 wurde für 6,6 Mio. GKV-Versicherte ein Diabetes dokumentiert (2012: 6,5 Mio.). Die chronische Niereninsuffizienz stellte die häufigste Komplikation im Jahr 2013 dar (15,0 %), gefolgt von diabetischer Polyneuropathie (13,5 %), Nephropathie (7,6 %), Retinopathie (7,0 %), DFS (6,1 %) und Dialysebehandlung (0,56 %). Während Ergebnisse zu diabetischer Retinopathie, Nephropathie und Polyneuropathie im Vergleich zu anderen Prävalenzschätzungen für Personen mit Typ-2-Diabetes niedriger ausfielen, sind diese zu Niereninsuffizienz, Dialysebehandlung und DFS vergleichbar. Schlussfolgerung Verstetigte Analysen der GKV-Daten sind von hohem Wert für die Diabetes-Surveillance, erfordern jedoch vertiefende Analysen zur Überprüfung und Vereinheitlichung von Falldefinitionen und Dokumentationsverhalten.

ZusammenfassungGesundheitsberichterstattung (GBE) als integrales Element von Public Health spielt eine wichtige Rolle bei der Entwicklung von Strategien und Konzepten, die das Ziel haben, die Gesundheit jeder Alters- und Bevölkerungsgruppe zu verbessern. Der Artikel gibt eine Übersicht zu Definition und Aufgaben der Gesundheitsberichterstattung des Bundes und beschreibt wichtige GBE-Komponenten in ihrer aktuellen Form. So wird das Publikationsformat des Journal of Health Monitoring vorgestellt, das als vielseitiges Format für die unterschiedlichen Nutzergruppen der Gesundheitsberichterstattung entwickelt wurde. Weiter werden Beispiele für die Nutzung und Wirkungen der Gesundheitsberichterstattung exemplarisch dargestellt. Gesundheitsberichterstattung ist dabei als flexibles System angelegt: So werden Veränderungen bei Datengrundlagen und Kommunikationsformen bei der Weiterentwicklung der Gesundheitsberichterstattung berücksichtigt.Die Weiterentwicklung der Gesundheitsberichterstattung setzt eine enge interdisziplinäre Zusammenarbeit unterschiedlicher Akteure voraus, um sowohl aktuelle Forschungsergebnisse verschiedener Wissenschaftsdisziplinen in die Prozesse der Gesundheitsberichterstattung zu integrieren als auch die Reichweite sowie den Impact der Gesundheitsberichterstattung weiter auszubauen. Neben der Weiterentwicklung der Gesundheitsberichterstattung auf der wissenschaftlichen Ebene stellen auch der Ausbau von partizipativen Elementen sowie eine stärkere Internationalisierung wichtige künftige Aufgaben dar.

During the COVID-19 pandemic in Germany, non-pharmaceutical interventions were imposed to contain the spread of the virus. Based on cross-sectional waves in March, July and December 2020 of the COVID-19 Snapshot Monitoring (COSMO), the present study investigated the impact of the introduced measures on the perceived access to health care. Additionally, for the wave in December, treatment occasion as well as utilization and satisfaction regarding telemedicine were analysed. For 18–74-year-old participants requiring medical care, descriptive and logistic regression analyses were performed. During the less strict second lockdown in December, participants reported more frequently ensured access to health care (91.2%) compared to the first lockdown in March (86.8%), but less frequently compared to July (94.2%) during a period with only mild restrictions. In December, main treatment occasions of required medical appointments were check-up visits at the general practitioner (55.2%) and dentist (36.2%), followed by acute treatments at the general practitioner (25.6%) and dentist (19.0%), treatments at the physio-, ergo- or speech therapist (13.1%), psychotherapist (11.9%), and scheduled hospital admissions or surgeries (10.0%). Of the participants, 20.0% indicated utilization of telemedical (15.4% telephone, 7.6% video) consultations. Of them, 43.7% were satisfied with the service. In conclusion, for the majority of participants, access to medical care was ensured during the COVID-19 pandemic, however, access slightly decreased during phases of lockdown. Telemedicine complemented the access to medical appointments.

ObjectivesLittle is known about the age-specific excess mortality pattern of people with diagnosed diabetes in Germany. Thus, our goal was to determine the excess mortality in diagnosed diabetes overall and stratified by age and sex based on claims data.DesignRoutine data analysis using a claims dataset from all statutory health-insured persons in Germany in 2013, which accounts for about 90% of the population.ParticipantsWe included persons who lived in Germany, were insured at least 360 days, were not self-paying any health services and were aged 30 years or older leading to a total number of 47.3 million insured persons for analyses.ExposureDiabetes was determined by the International Classification of Diseases-10 codes E10–E14, which were documented in 2013 in at least two-quarters on an outpatient setting or at least once on an inpatient setting.Outcome measuresThe vital status in the study population was drawn from the claims dataset for the year 2014. We derived the excess mortality estimated as an age-adjusted mortality rate ratio (MRR) by sex and for age groups using a Poisson model.Main resultsWe found age-adjusted MRRs (95% CI) for diabetes of 1.52 (1.51 to 1.52) for women and 1.56 (1.56 to 1.56) for men. These figures declined with increasing age and were highest for ages 30–34 years with 6.76 (4.99 to 9.15) for women and 6.87 (5.46 to 8.64) for men, and lowest for age 95 years and older with 1.13 (1.10 to 1.15) for women and 1.11 (1.05 to 1.17) for men.ConclusionsWe derived deeply age-stratified figures on excess mortality in diabetes for Germany. Establishing a sustainable analysis of excess mortality is aimed at within the framework of diabetes surveillance.

As a condition, diabetes mellitus is associated with risk factors and diseases such as obesity. At the same time, cardiovascular diseases are a frequent consequence of diabetes. There have yet to be any findings on the Germany-wide prevalence of diabetes and diabetes comorbidities based on statutory health insurance data. This study estimates the documented prevalence of diabetes in 2019 on the basis of all ambulatory physicians' claims data of German statutory health insurance. In addition, the prevalence of obesity, high blood pressure, coronary heart disease, heart failure, stroke and depression is calculated for diabetes and non-diabetes patients, and the prevalence ratio (PR) is determined as a quotient. The approach used was a case-control design, which assigns a control person without diabetes to each diabetes patient who is similar in terms of age, region and sex. In diabetes patients, a PR greater than 1 was observed for all examined diseases across all age groups, thus demonstrating a higher prevalence compared to persons without diabetes. The highest PR across all age groups for women (3.8) and men (3.7) was found for obesity. In a comparison over time, documented prevalence figures of diabetes in Germany stagnate. With the exception of depression, the documented prevalences of comorbidities correspond well with the prevalences found in population-wide examination surveys.

Gestational diabetes mellitus (GDM) is an important risk factor for pregnancy complications. Since 2012, the Federal Joint Committee's maternity directive recommends a two-step screening for GDM with a pre-test and subsequent diagnostic test if the pre-test is positive. This study analyses the implementation and development over time of GDM screening participation and prevalence in Germany. The data basis is the external inpatient obstetrics quality assurance documentation, which covers all births in hospital. Women with diabetes before pregnancy were excluded. The study defined women as GDM cases if the condition was documented in maternity records or if the ICD-10 diagnosis O24.4 was coded for inpatients at discharge and figures were determined for the years 2013 to 2018. As the documentation of screening tests has only been included in the data set since 2016, screening participation for the years 2016 to 2018 were estimated and evaluated based on the pre-test and/or diagnostic tests documented in maternity records. In 2018, the majority of all women who gave birth in hospitals had had a pre-test conducted (65.0%) or a pre-test and diagnostic test (18.2%) in line with the two-step procedure. A further 6.7% received a diagnostic test alone. GDM screening participation increased over time from 83.4% in 2016 to 89.9% in 2018. The prevalence of a documented GDM increased from 4.6% to 6.8% between 2013 and 2018. In 2018, this equates to 51,318 women with GDM. Reliably assessing the extent and causes of this development will require continuous analyses of screening implementation, documentation and changes in maternal risk factors.

Data sources for the systematic and ongoing analysis of prevalence of microvascular complications of diabetes mellitus are limited in Germany. For the first time, we estimated the complications prevalence based on claims data of all statutory health insurance (SHI) providers according to the Data Transparency Act.Health claims data of the reporting years 2012 and 2013 were analyzed. The reference population was identified as insured persons with a diabetes diagnosis according to the international classification of disease. Diabetes was defined as documentation of at least two confirmed diabetes diagnoses in an outpatient setting or one diagnosis in an inpatient setting (ICD codes E10-E14). Complications were defined based on the following ICD codes: nephropathy (N08.3), retinopathy (H36.0), polyneuropathy (G63.2), diabetic foot syndrome (DFS; E10-14.74, E10-14.75), chronic kidney disease (N18.-), and treatment with dialysis (Z49.1, Z49.2, Z99.2). Results were compared to prevalence estimates based on routine data and registries in Germany and abroad.In 2013, diabetes was documented for 6.6 million persons with SHI (2012: 6.5 million). In 2013, chronic kidney disease (15.0%) was the most frequent complication, followed by diabetic polyneuropathy (13.5%), nephropathy (7.6%), retinopathy (7.0%), DFS (6.1%), and treatment with dialysis (0.56%). While results for diabetic retinopathy, nephropathy, and polyneuropathy are lower than prevalence estimates from other type 2 diabetes studies, they are comparable for chronic kidney disease, treatment with dialysis, and DFS.Continuous analysis of health claims data is highly valuable for the diabetes surveillance. However, detailed analyses are required for verification and harmonization of case definitions and documentation practice.

Background While life expectancy (LE) is rising, years lived with severe health impairments especially due to chronic diseases also increase. Diabetes is one of the major chronic diseases with high potential for co-morbidity and premature deaths needing life-long care. Therefore, information about loss in LE and healthy life years (HLY) in people with diabetes compared to people without diabetes is essential for assessing the burden of diabetes. Methods Data on all-cause mortality rates for the general population of Germany in 2014 was drawn from the Federal Statistical Office; mortality rate ratios for people with diabetes compared to people without diabetes were based on claims data from about 70 million people covered by statutory health insurances in 2014. Data of three nationwide health telephone surveys conducted among adults in Germany 2009-2012 (n ∼ 60,000) were used to assess severe health impairments defined as self-reported limitations in daily activities due to diseases for at least six months in people with and without diabetes. Based on these figures, estimates on LE and HLY could be calculated by sex and 5-year age-groups for people with and without diabetes aged ≥ 30 years. Results In both sexes and in all 5-year age-groups, LE and HLY were substantially lower for people with than for people without diabetes. For example, among women in the age group 30-34 years, LE and HLY estimates were 48.0 and 36.4 years for those with diabetes compared to 54.9 and 47.6 years for those without diabetes; in men, these figures were estimated as 42.6 and 32.4 years for those with diabetes compared to 50.3 and 44.1 years for those without diabetes. Differences in LE and HLY between people with and without diabetes attenuated with increasing age. Conclusions The present study revealed substantial reductions in LE and HLY related to diabetes and underlines the importance of integrating both figures in a national diabetes surveillance. Key messages There are substantial differences in life expectancy and healthy life years between people with and without diabetes. Specific intervention and prevention activities should be implemented to tackle disability in persons with diabetes.

Background Non-communicable diseases (NCD) are a major public health challenge in Germany and throughout the world. The epidemiology of diabetes, in particular type 2 diabetes, exemplifies the need for effective prevention and control. To support policy making with actionable evidence, the Robert Koch Institute (RKI) is developing a diabetes surveillance system for Germany serving as model for NCD surveillance. Methods First, we consented a conceptual framework and key indicators among experts and stakeholders based on an extensive literature review including national and international NCD surveillance systems. After prioritization of indicators applying a two-step Delphi method, we identified data sources for sustainable surveillance including data from nationwide RKI health surveys as well as external data such as claims or registry data. Lastly, in cooperation with stakeholders we developed first dissemination products. Results During concept phase, we identified 40 indicators ranging from risk factors, disease incidence and prevalence to quality of care, mortality and burden of disease. During implementation, suitable data sources and results on temporal trends have been obtained for a large part of the indicators. For dissemination we developed a website with interactive visualization of results supported by an explainer video on YouTube. Additionally, we prepared a printed diabetes report summarizing and interpreting key findings for a broader audience, including health politicians and public health researchers. Conclusions We demonstrated the feasibility of the systematic collection and analysis of health data to describe the disease and care situation of diabetes in Germany. The methodology and data sources of indicators can be transferred to further NCDs and shared risk factors are already depicted. Next steps are to close remaining data gaps and to advance dissemination products in collaboration with our stakeholder network tailored to their information needs. Key messages Considering available health data, we showed the feasibility of implementing a diabetes surveillance system for Germany providing reliable information on disease dynamics for various stakeholders. The knowledge on methodology and data sources gained establishing a diabetes surveillance system can be extended to other noncommunicable diseases.

Eine Kernaufgabe von Public Health ist die kontinuierliche Erfassung und Analyse von gesundheitsbezogenen Daten zu relevanten Krankheiten (Surveillance). Sie dient der zeitnahen Umsetzung von Maßnahmen zum Schutz der Gesundheit in der Bevölkerung. Dafür müssen relevante Informationen zur richtigen Zeit und in geeigneter Weise für die entscheidenden Zielgruppen bereitgestellt werden (Dissemination). Eine Disseminationsstrategie unterstützt die effektive Ergebniskommunikation und berücksichtigt 3 Kernfragen: (1) „Was sind die relevanten Inhalte der Surveillance?“, (2) „Wer benötigt welche Informationen?“ und (3) „Wie werden die Ergebnisse den Zielgruppen bereitgestellt?“ Die Digitalisierung eröffnet hierbei neue Möglichkeiten für die Gestaltung der Formate. Seit 2015 wird am Robert Koch-Institut die Diabetes-Surveillance aufgebaut. In einem strukturierten Konsensprozess wurden 4 gesundheitspolitisch relevante Handlungsfelder mit 40 Kennzahlen (Indikatoren) definiert. Anschließend wurden gemeinsam mit dem wissenschaftlichen Projektbeirat unter Berücksichtigung neuer Möglichkeiten durch die Digitalisierung erste Publikationsformate erarbeitet. Neben Artikeln in Fachzeitschriften stellen der Bericht „Diabetes in Deutschland“ und eine Webseite mit interaktiver Visualisierung der Ergebnisse die wichtigsten Formate der ersten Projektphase dar. Begleitend werden Twitter und Youtube für die Erhöhung der Reichweite genutzt. In der nächsten Projektphase steht neben der Weiterentwicklung des Indikatorensets der Ausbau der Dissemination hin zu einer nutzer- und handlungsorientierten Berichterstattung im Mittelpunkt. In engem Austausch mit dem wissenschaftlichen Beirat sollen Anforderungen der Zielgruppen erfasst und in der Entwicklung weiterer Formate berücksichtigt werden.

ZusammenfassungEine Kernaufgabe von Public Health ist die kontinuierliche Erfassung und Analyse von gesundheitsbezogenen Daten zu relevanten Krankheiten (Surveillance). Sie dient der zeitnahen Umsetzung von Maßnahmen zum Schutz der Gesundheit in der Bevölkerung. Dafür müssen relevante Informationen zur richtigen Zeit und in geeigneter Weise für die entscheidenden Zielgruppen bereitgestellt werden (Dissemination).Eine Disseminationsstrategie unterstützt die effektive Ergebniskommunikation und berücksichtigt 3 Kernfragen: (1) „Was sind die relevanten Inhalte der Surveillance?“, (2) „Wer benötigt welche Informationen?“ und (3) „Wie werden die Ergebnisse den Zielgruppen bereitgestellt?“ Die Digitalisierung eröffnet hierbei neue Möglichkeiten für die Gestaltung der Formate.Seit 2015 wird am Robert Koch-Institut die Diabetes-Surveillance aufgebaut. In einem strukturierten Konsensprozess wurden 4 gesundheitspolitisch relevante Handlungsfelder mit 40 Kennzahlen (Indikatoren) definiert. Anschließend wurden gemeinsam mit dem wissenschaftlichen Projektbeirat unter Berücksichtigung neuer Möglichkeiten durch die Digitalisierung erste Publikationsformate erarbeitet. Neben Artikeln in Fachzeitschriften stellen der Bericht „Diabetes in Deutschland“ und eine Webseite mit interaktiver Visualisierung der Ergebnisse die wichtigsten Formate der ersten Projektphase dar. Begleitend werden Twitter und Youtube für die Erhöhung der Reichweite genutzt.In der nächsten Projektphase steht neben der Weiterentwicklung des Indikatorensets der Ausbau der Dissemination hin zu einer nutzer- und handlungsorientierten Berichterstattung im Mittelpunkt. In engem Austausch mit dem wissenschaftlichen Beirat sollen Anforderungen der Zielgruppen erfasst und in der Entwicklung weiterer Formate berücksichtigt werden.

Health reporting as an integral part of public health plays an important role in the development of strategies and concepts that aim to improve the health of all population groups. This article provides an overview of the definition and tasks of federal health reporting and describes important health reporting components in their current form. The publication format of the Journal of Health Monitoring, which was developed for different user groups of health monitoring, is presented. Examples of the uses and effects of health reporting are also presented. Health reporting is designed as a flexible system: changes in databases as well as forms of communication are taken into account in the further development of health reporting.The further development of health reporting requires close interdisciplinary cooperation between different actors in order to integrate current research results from various scientific disciplines into the processes of health reporting, as well as to further expand the scope and impact of health reporting. In addition, to further develop health reporting on a scientific level, the expansion of participatory elements and a stronger internationalization will be important future tasks.

Diabetes mellitus ist eine nichtubertragbare Krankheit von hoher Public-Health-Relevanz. In Deutschland verfugbare Daten werden bislang nicht ausreichend fur eine zielorientierte Analyse und Bereitstellung von Ergebnissen genutzt. Ziel ist der Aufbau einer nationalen Diabetes-Surveillance am Robert Koch-Institut (RKI). Erarbeitet wird ein wissenschaftliches Rahmenkonzept mit 4 Handlungsfeldern und 40 Indikatoren auf Basis von Literaturreviews und strukturiertem Expertenkonsens. Es erfolgt eine Bestandsaufnahme zu verfugbaren Datenquellen und nachhaltiger Nutzbarkeit zur Abbildung der Indikatoren nach soziodemografischen Kriterien, zeitlichen Veranderungen und regionalen Unterschieden. Handlungsfeld 1 umfasst 10 Indikatoren zur Primarpravention von Diabetes. Die Handlungsfelder 2 bis 4 enthalten 30 Prozess- und Ergebnisindikatoren zur Sekundarpravention von Diabetes. Essenzielle Datenquellen sind bundesweite RKI-Gesundheitssurveys, Abrechnungs‑/Versorgungsdaten, amtliche Statistiken und Typ-1-Diabetes-Register. Erste Analysen zeigen eine Verbesserung in Prozessen und Ergebnissen. Bei patientennahen Indikatoren weisen die Ergebnisse auf Verbesserungspotenziale hin. Verbleibende Datenlucken und Nutzungsbarrieren bestehen bezuglich des Gestationsdiabetes und diabetesassoziierter Komplikationen. Analysen zu sozialen und regionalen Unterschieden sind bislang nicht uberall moglich. Die Diabetes-Surveillance ermoglicht systematische und fortlaufende Analysen zur Epidemiologie und Krankheitslast von Diabetes in Deutschland und kann als Entscheidungshilfe fur die Planung und Umsetzung von Masnahmen dienen. Datengrundlagen sowie Print- und Online-Produkte fur eine zeitnahe und adressatengerechte Ergebnisdarstellung mussen kontinuierlich weiterentwickelt werden.

Diabetes mellitus and other noncommunicable diseases (NCDs) represent an emerging global public health challenge. In Germany, about 6.7 million adults are affected by diabetes according to national health surveys, including 1.3 million with undiagnosed diabetes. Complications of diabetes result in an increasing burden for individuals and society as well as enormous costs for the health care system. In response, the Federal Ministry of Health commissioned the Robert Koch Institute (RKI) to implement a diabetes surveillance system and the Federal Center for Health Education (BZgA) to develop a diabetes prevention strategy. In a two-day workshop jointly organized by the RKI and the BZgA, representatives from public health institutes in seven countries shared their expertise and knowledge on diabetes prevention and surveillance. Day one focused on NCD surveillance systems and emphasized both the strengthening of sustainable data sources and the timely and targeted dissemination of results using innovative formats. The second day focused on diabetes prevention strategies and highlighted the importance of involving all relevant stakeholders in the development process to facilitate its acceptance and implementation. Furthermore, the effective translation of prevention measures into real-world settings requires data from surveillance systems to identify high-risk groups and evaluate the effect of measures at the population level based on analyses of time trends in risk factors and disease outcomes. Overall, the workshop highlighted the close link between diabetes prevention strategies and surveillance systems. It was generally stated that only robust data enables effective prevention measures to encounter the increasing burden from diabetes and other NCDs.

The prevalence and incidence of documented diabetes are two essential indicators intended to be reported on a periodic basis within the framework of diabetes surveillance in Germany.Data provided based on the Data Transparency Act were analyzed. The data contain information on outpatient and inpatient care for all approximately 70 million persons with statutory health insurance. The case definition for the prevalence of documented diabetes comprises a confirmed outpatient diagnosis in at least two quarters of a year or an inpatient diagnosis in at least one quarter of a year in accordance with ICD-10 codes E10.- to E14.-. The incidence was calculated based on the same definition and with one year of diagnosis-free lead time.In 2011, a prevalence of 9.7% (women: 9.4%, men: 10.1%) was observed for persons with statutory health insurance. There are considerable differences in prevalence between the federal states and the maximum gap is 7.1 percentage points (age standardized: 4.0 percentage points). Type 2 and type 1 diabetes show a documented prevalence of 7.5% and 0.28%, respectively. Unspecified diabetes is documented relatively frequently with 1.9%. In 0.21% of persons, the diagnosis diabetes is documented via one inpatient secondary diagnosis. In addition, 0.17% of people without documented diabetes have at least one prescription of an antidiabetic drug. In 2012, 565,040 insured persons were newly diagnosed with diabetes; this corresponds to 1.0% of the insured persons (women: 1.0%, men: 1.1%).The developed reference analysis is suitable for reporting the prevalence and incidence of documented diabetes within the framework of diabetes surveillance. The differentiation of diabetes types is difficult due to coding practice.

Hintergrund: Prävalenz und Inzidenz des dokumentierten Diabetes sind wesentliche Kennzahlen, für die im Rahmen der Nationalen Diabetes-Surveillance eine wiederkehrende Ermittlung geplant ist. Methodik: Es wurden Daten nach der Datentransparenzverordnung ausgewertet, die ambulante und stationäre Versorgungsinformationen zu allen rund 70 Mio. gesetzlich Krankenversicherten enthalten. Die Falldefinition für die Prävalenz des dokumentierten Diabetes umfasst eine in mindestens zwei Quartalen eines Jahres vorliegende gesicherte ambulante Diagnose oder eine in mindestens einem Quartal eines Jahres vorliegende stationäre Diagnose gemäß ICD-10-Codes E10.- bis E14.-. Die Inzidenz wurde auf Grundlage derselben Definition und mit einem Jahr diagnosefreier Vorlaufzeit berechnet. Ergebnisse: Im Jahr 2011 ist für gesetzlich Versicherte eine Prävalenz von 9,7 % (Frauen: 9,4 %, Männer: 10,1 %) beobachtbar. Es existieren Prävalenzunterschiede zwischen den Bundesländern, wobei der maximale Unterschied 7,1 %-Punkte (altersstandardisiert: 4,0 %-Punkte) beträgt. Typ-2- und Typ-1-Diabetes zeigen eine Prävalenz von 7,5 % bzw. 0,28 %. Ein unspezifischer Diabetes wird mit 1,9 % relativ häufig dokumentiert. Bei 0,21 % der Personen wird der Diabetes ausschließlich über eine stationäre Nebendiagnose dokumentiert. Zusätzlich weisen 0,17 % der Personen ohne dokumentierten Diabetes mindestens eine Verordnung eines Antidiabetikums auf. Im Jahr 2012 sind 565.040 Versicherte neu an Diabetes erkrankt, dies entspricht 1,0 % der Versicherten (Frauen: 1,0 %, Männer: 1,1 %). Diskussion: Die erarbeitete Referenzauswertung ist für die Berichterstattung von Prävalenz und Inzidenz des dokumentierten Diabetes im Rahmen der Diabetes-Surveillance geeignet. Die Unterscheidung der Diabetestypen ist aufgrund der Codierungspraxis schwierig., Background: The prevalence and incidence of documented diabetes are two essential indicators intended to be reported on a periodic basis within the framework of diabetes surveillance in Germany. Methodology: Data provided based on the Data Transparency Act were analyzed. The data contain information on outpatient and inpatient care for all approximately 70 million persons with statutory health insurance. The case definition for the prevalence of documented diabetes comprises a confirmed outpatient diagnosis in at least two quarters of a year or an inpatient diagnosis in at least one quarter of a year in accordance with ICD-10 codes E10.- to E14.-. The incidence was calculated based on the same definition and with one year of diagnosis-free lead time. Results: In 2011, a prevalence of 9.7% (women: 9.4%, men: 10.1%) was observed for persons with statutory health insurance. There are considerable differences in prevalence between the federal states and the maximum gap is 7.1 percentage points (age standardized: 4.0 percentage points). Type 2 and type 1 diabetes show a documented prevalence of 7.5% and 0.28%, respectively. Unspecified diabetes is documented relatively frequently with 1.9%. In 0.21% of persons, the diagnosis diabetes is documented via one inpatient secondary diagnosis. In addition, 0.17% of people without documented diabetes have at least one prescription of an antidiabetic drug. In 2012, 565,040 insured persons were newly diagnosed with diabetes; this corresponds to 1.0% of the insured persons (women: 1.0%, men: 1.1%). Discussion: The developed reference analysis is suitable for reporting the prevalence and incidence of documented diabetes within the framework of diabetes surveillance. The differentiation of diabetes types is difficult due to coding practice.

Background Diabetes mellitus is a non-communicable disease with high public health relevance in Germany. Therefore, the Robert Koch Institute startetd to establish a national diabetes surveillance system in Germany in 2016. Essential part of a surveillance system is the dissemination of health information to the relevant stakeholders to facilitate its translation into action. Methods For the development of the dissemination strategy, different sources of information were used. First, an online-survey combined with structured web-research explored dissemination approaches in the international context. Secondly, a workshop with public health experts from seven countries highlighted best practice examples. Based on this information, a dissemination strategy was developed in close alignment with the scientific advisory board of the diabetes surveillance including experts from politics, prevention research, regional health reporting, physicians/diabetologists and public health scientists. Results Three main questions were identified to be considered in the dissemination of health information: Which audience group is addressed? Which content is relevant to this group? What is the preferred format to communicate the information? Therefore, a diabetes report will be generated focusing on health policy makers summarizing the key information on the disease dynamic. A website containing all information including a visualization tool should facilitate access for stakeholders. Additionally, awareness needs to be raised using social media, classical media and direct interactions with relevant stakeholders. Conclusions In alignment with different stakeholder groups, the diabetes surveillance developed a dissemination strategy considering international best practice examples and innovative ideas for health data visualization. The next steps are to refine the dissemination strategy based on feedback from the different stakeholder groups to ensure the use of the provided information. Key messages A dissemination strategy for the diabetes surveillance has been developed in a participatory approach including experts from various stakeholder groups. Next steps include the refinement of the dissemination strategy and its formats based on stakeholders feedback requirements.

Mevalonate kinase deficiency, a rare autosomal recessive autoinflammatory disease, is caused by mutations in the MVK gene encoding mevalonate kinase (MK). MK catalyzes the phosphorylation of mevalonic acid to mevalonate-5-phosphate (MVAP) in the pathway of isoprenoid and sterol synthesis. The disease phenotype correlates with residual activity ranging from0.5% for mevalonic aciduria to 1-7% for the milder hyperimmunoglobulinemia D and periodic fever syndrome (HIDS). Hence, assessment of loss-of-function requires high accuracy measurements. We describe a method using isotope dilution UPLC-MS/MS for precise and sensitive determination of MK activity.Wild-type MK and the variant V261A, which is associated with HIDS, were recombinantly expressed in Escherichia coli. Enzyme activity was determined by formation of MVAP over time quantified by isotope dilution UPLC-MS/MS. The method was validated according to the FDA Guidance for Bioanalytical Method Validation.Sensitivity for detection of MAVP by UPLC-MS/MS was improved by derivatization with butanol-HCl (LLOQ, 5.0 fmol) and the method was linear from 0.5 to 250 μmol/L (R(2)0.99) with a precision of ≥ 89% and an accuracy of ± 2.7%. The imprecision of the activity assay, including the enzymatic reaction and the UPLC-MS/MS quantification, was 8.3%. The variant V261A showed a significantly decreased activity of 53.1%.Accurate determination of MK activity was enabled by sensitive and reproducible detection of MVAP using UPLC-MS/MS. The novel method may improve molecular characterization of MVK mutations, provide robust genotype-phenotype correlations, and accelerate compound screening for drug candidates restoring variant MK activity.