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Sepsis often leads to long-term functional deficits and increased mortality in survivors. Post-acute rehabilitation can decrease long-term sepsis mortality, but its impact on nursing care dependency, health care use and costs is insufficiently understood.To assess the short-term (7-12 months post-discharge) and long-term (13-36 months post-discharge) effect of inpatient rehabilitation within six months after hospitalization on mortality, nursing care dependency, health care use and costs.Observational cohort study using health claims data from the health insurer AOK (Allgemeine Ortskrankenkasse). Among 24.3 million AOK beneficiaries, we identified adult beneficiaries hospitalized with sepsis in 2013/14 by explicit ICD-10 codes. We included patients who were non-employed pre-sepsis, for whom rehabilitation is reimbursed by the AOK and thus included in the dataset, and who survived at least six months post-discharge. The effect of rehabilitation was estimated by statistical comparisons of patients with rehabilitation (treatment group) and those without (reference group). Possible differential effects were investigated for the subgroup of Intensive Care Unit (ICU)-treated sepsis survivors. We used inverse probability of treatment weighting based on propensity scores to adjust for differences in relevant covariates. Costs for rehabilitation in the six months post-sepsis were not included in the costs analysis.Among 41,918 six-months sepsis survivors, 17.2% (n=7,224) received rehabilitation. There was no significant difference in short-term survival between survivors with and without rehabilitation. Long-term survival rates were significantly higher in the rehabilitation group (90.4% vs. 88.7% (odds ratio [OR]=1.2 95% confidence interval [CI], 1.1-1.3) p=0.003)). Survivors with rehabilitation had a higher mean number of hospital readmissions (7-12 months after sepsis, 0.82 vs. 0.76, p=0.014) and were more frequently dependent on nursing care (7-12 and 13-36 months after sepsis, 47.8% vs. 42.3%, OR=1.2 (95% CI, 1.2-1.3), p0.001, and 52.5% vs. 47.5%, OR=1.2 (95% CI, 1.1-1.3), p0.001, respectively) compared to those without rehabilitation, while total health care costs 7-36 months did not differ between groups. ICU-treated sepsis patients with rehabilitation had higher short and long-term survival rates (93.5% vs. 90.9%, OR=1.5 (95% CI, 1.2-1.7), p0.001; 89.1% vs. 86.3%, OR= 1.3 (95% CI, 1.1-1.5), p0.001, respectively) than ICU-treated sepsis patients without rehabilitation.Rehabilitation within the first 6 months after ICU- and non-ICU treated sepsis is associated with increased long-term survival within three years after sepsis without added total health care costs. Future work should aim to confirm and explain these exploratory findings.

Background: We aimed to examine urban–rural disparities in sepsis case fatality rates among patients with community-acquired sepsis in Germany. Methods: Retrospective cohort study using de-identified data of the nationwide statutory health insurance AOK, covering approx. 30% of the German population. We compared in-hospital- and 12-month case fatality between rural and urban sepsis patients. We calculated odds ratios (OR) with 95% confidence intervals and the estimated adjusted odds ratio (ORadj) using logistic regression models to account for potential differences in the distribution of age, comorbidities, and sepsis characteristics between rural and urban citizens. Results: We identified 118,893 hospitalized patients with community-acquired sepsis in 2013–2014 with direct hospital admittance. Sepsis patients from rural areas had lower in-hospital case fatality rates compared to their urban counterparts (23.7% vs. 25.5%, p < 0.001, Odds Ratio (OR) = 0.91 (95% CI 0.88, 0.94), ORadj = 0.89 (95% CI 0.86, 0.92)). Similar differences were observable for 12-month case fatalities (45.8% rural vs. 47.0% urban 12-month case fatality, p < 0.001, OR = 0.95 (95% CI 0.93, 0.98), ORadj = 0.92 (95% CI 0.89, 0.94)). Survival benefits were also observable in rural patients with severe community-acquired sepsis or patients admitted as emergencies. Rural patients of

BACKGROUND: Collateral effects and consequences of the coronavirus disease 19 (COVID-19) pandemic on kidney transplant recipients remain widely unknown. METHODS: This retrospective cohort study examined changes in admission rates, incidences of diseases leading to hospitalization, in-patient procedures, and maintenance medication in long-term kidney transplant recipients with functioning graft during the early COVID-19 pandemic in Germany. Data were derived from a nationwide health insurance database. Analysis was performed from March 15 to September 30 and compared the years 2019 and 2020. Effects on mortality and adverse allograft events were compared with COVID-19-attributed effects. RESULTS: A total of 7725 patients were included in the final analysis. Admissions declined in 2020 by 17%, with the main dip during a 3-month lockdown (–31%) but without a subsequent rebound. Incidences for hospitalization did not increase for any investigated disease entities, whereas decreasing trends were noted for non-COVID-19 pulmonary and urogenital infections (incidence rate ratio 0.8, 95% CI, 0.62 to 1.03, and 0.82, 95% CI, 0.65 to 1.04, respectively). Non-COVID-19 hospital stays were 0.6 days shorter (P=0.03) and not complicated by increased dialysis, ventilation, or intensive care treatment rates. In-hospital and 90-day mortality remained stable. Incidences of severe COVID-19 requiring hospitalization was 0.09 per 1000 patient-days, and in-hospital mortality was 9%. A third (31%) of patients with calcineurin-inhibitor medication and without being hospitalized for COVID-19 reduced doses by at least 25%, which was associated with an increased allograft rejection risk (adjusted hazard ratio 1.29, 95% CI, 1.02 to 1.63). COVID-19 caused 17% of all deaths but had no significant association with allograft rejections. All-cause mortality remained stable (incidence rate ratio 1.15, 95% CI, 0.91 to 1.46), also when restricting analysis to patients with no or outpatient-treated COVID-19 (0.97, 95% CI, 0.76 to 1.25). CONCLUSION: Despite significant collateral effects, mortality remained unchanged during the early COVID-19 pandemic. Considerable temporary reductions in admissions are safe, whereas reducing immunosuppression results in increased allograft rejection risk.

BACKGROUND National classifications and terminologies already routinely used for documentation within patient care settings enable the unambiguous representation of clinical information. However, the diversity of different vocabularies across healthcare institutions and countries is a barrier to achieve semantic interoperability and to exchange data across sites. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) enables the standardization of structure and medical terminology. It allows mapping of national vocabularies into so-called standard-concepts representing normative expressions for international analyses and research. Within our project “Hybrid quality indicators using machine learning methods (Hybrid-QI)”, we faced the challenge of harmonizing source codes used in German claims data vocabularies currently not available in OMOP CDM. OBJECTIVE The objective of this study is to increase the coverage of German vocabularies in OMOP CDM. With our work, we want to achieve the complete transformation of source codes used in German claims data to OMOP CDM without data loss as well as making German claims data usable for research based on OMOP CDM. METHODS To prepare the missing German vocabularies for OMOP CDM we defined a vocabulary preparation approach consisting of the identification of all codes of the corresponding vocabularies, their assembly in machine-readable tables and the translation of German designations into English. Furthermore, we used two proposed approaches for OMOP-compliant vocabulary preparation: the mapping to standard-concepts using the OHDSI tool Usagi and the preparation of new 2-billion-concepts. Finally, we evaluated the prepared vocabularies regarding completeness and correctness using synthetic German claims data and calculated the coverage of German claims data vocabularies in OMOP CDM. RESULTS With our vocabulary preparation approach, we were able to map three missing German vocabularies to standard-concepts and to prepare eight vocabularies as new 2-billion-concepts. The results of the completeness evaluation showed that the prepared vocabularies cover most of the source codes contained in German claims data. From the results of the correctness evaluation, it can be seen that the specified validity periods in OMOP CDM are compliant for the majority of source codes and associated dates in the German claims data. The calculation of the vocabulary coverage showed a noticeable decrease of missing vocabularies from 55% to 10% due to our preparation approach. CONCLUSIONS By preparing a total of ten vocabularies, we were able to show that our approach is applicable to any type of vocabulary used in a source dataset. The prepared vocabularies resulting from our work are currently limited to German vocabularies, which can only be used in national OMOP CDM research projects. Reason for this is a missing mapping of new 2-billion-concepts to standard-concepts. To be able to participate in international OHDSI network studies with German claims data, future work is required to map the prepared 2-billion-concepts to standard-concepts.

The coronavirus disease-19 (COVID-19) pandemic constitutes a major challenge for transplantation medicine. Given the potential risk of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection and adverse disease courses for recently transplanted recipients, many transplant centers have adapted kidney transplantation programs during the pandemic [1-3]. However, the severity of adaptions considerably differed between countries. Whereas numbers of kidney transplant procedures decreased substantially in the United States, Italy or France [1-3], partially accompanied by changes in early immunosuppressive regimens, countries of the Eurotransplant network virtually maintained transplant activity [4].

ZusammenfassungIn Deutschland ist mit der Fallpauschalenbezogenen Krankenhausstatistik (DRG-Statistik) eine Vollerhebung der Abrechnungsdaten nahezu aller akutstationären Krankenhausbehandlungsfälle verfügbar. Die Mikrodaten, d. h. die Datensätze der einzelnen Behandlungsfälle, werden von den Forschungsdatenzentren der Statistischen Ämter des Bundes und der Länder für die wissenschaftliche Nutzung bereitgestellt. Krankenhausabrechnungsdaten werden zu Abrechnungszwecken erhoben und haben – wie andere Datenquellen auch – spezifische Besonderheiten und Eigenschaften, die bei der Planung von Analysen und im Studiendesign angemessen berücksichtigt werden müssen. Eine besondere Herausforderung ist dabei die sachgerechte Operationalisierung von Analyseeinheiten, Zielgrößen und weiteren Variablen, die u. a. eine mögliche unterschiedliche Kodierpraxis in verschiedenen Krankenhäusern antizipiert und deren Auswirkungen über eine durchdachte Variablendefinition minimiert. In diesem Beitrag wird anhand von praktischen Beispielen aufgezeigt, was bei der Definition von Variablen in fallbezogenen Krankenhausabrechnungsdaten beachtet werden sollte, um das Risiko von kodierungs- oder anderweitig bedingten Verzerrungen möglichst gering zu halten. Ausgehend von den Erfahrungen der Autoren werden die wichtigsten Schritte und Herausforderungen in Bezug auf ein typisches retrospektives Beobachtungsstudiendesign in der Versorgungsforschung beschrieben. Basierend auf bereits durchgeführten Projekten auf der Grundlage der Mikrodaten der Fallpauschalenbezogenen Krankenhausstatistik (DRG-Statistik) werden Beispiele anhand eigener Berechnungen illustriert. Die Verlässlichkeit und Interpretierbarkeit von Analysen auf der Grundlage der Mikrodaten der DRG-Statistik hängt entscheidend von der sachgerechten Operationalisierung der Variablen ab. Um das Risiko von Verzerrungen und Fehlinterpretationen möglichst gering zu halten, sind umfangreiche Vorüberlegungen notwendig, die neben medizinisch-klinischen Aspekten auch den Kontext der Datenerhebung und die klassifikatorischen Möglichkeiten zur Abbildung bestimmter Sachverhalte berücksichtigen. Es ist zu hoffen, dass die Akzeptanz von Studien auf der Grundlage von Krankenhausabrechnungsdaten weiter zunimmt und der wertvolle Datenbestand der DRG-Statistik in Zukunft noch intensiver für Forschungszwecke genutzt wird.

Zusammenfassung Ziel der Arbeit Amputationen vermindern irreversibel die Lebensqualität. Das Ziel vorangehender Versorgung ist stets eine Amputation zu verhindern. Diese Versorgung sollte bundesweit mit derselben Ergebnisqualität gewährleistet sein. Ziel dieser Arbeit ist es, regionale Versorgungsunterschiede sichtbar zu machen, indem Amputationsfallzahlen nach Amputationshöhen auf Kreisebene analysiert werden. Methodik In den deutschlandweiten Krankenhausabrechnungsdaten (DRG-Statistik) wurden alle Behandlungsfälle mit Amputation an der unteren Extremität zwischen 2011 und 2015 identifiziert. Auf Kreisebene wurden rohe Raten sowie alters- und geschlechtsstandardisierte Raten pro 100 000 Einwohner dargestellt. Daneben wurde die systematische Variationskomponente (SCV) zwischen den Kreisen betrachtet und das standardisierte Morbiditätsverhältnis (SMR) in Funnel Plots dargestellt. Ergebnisse Im Beobachtungszeitraum belief sich die mediane jährliche Amputationsrate auf 67 Fälle pro 100 000 Einwohner. Auf Kreisebene variierte die rohe Rate um das 6-fache. Unabhängig von demografischen Unterschieden zeigten sich Variationen zwischen den Kreisen. Erhöhte Amputationsraten wurden überwiegend im Osten und Südosten beobachtet. Die Variationen waren bei den Amputationshöhen Zeh/Zehenstrahl (SCV 11,8) und Fuß komplett & Mittel-/Vorfuß (SCV 11,7) am stärksten ausgeprägt. Schlussfolgerung Es bestehen deutliche regionale Unterschiede in den Amputationsraten. Bei peripheren Amputationshöhen ist die systematische Variation am stärksten. Insbesondere im Osten und Südosten sind regionale Cluster erkennbar, die Anhaltspunkte für einen möglichen regionalen Verbesserungsbedarf in der Versorgung liefern.

BackgroundData on long-term outcomes of hospitalized COVID-19 patients are scarce.ObjectiveTo provide a detailed account of hospitalized COVID-19 patients until 180 days after their initial hospitalization.DesignNationwide cohort study using claims data from the German Local Health Care Funds, the health insurer of one-third of the German population.SettingGermany.PatientsAdult patients hospitalized in Germany between Feb 1 and April 30, 2020 with PCR-confirmed COVID-19 and a related principal diagnosis.MeasurementsPatient characteristics and ventilation status, in-hospital, 30-, 90- and 180- day mortality measured from admission, and 180-day readmission measured from discharge. Multivariable logistic regression model of independent risk factors for 180-day mortality.ResultsOf 8679 patients (median age, 72 years), 2161 (24.9%) died during the index hospitalization. 30-day mortality was 23.9% (2073/8679), 90-day mortality 27.9% (2425/8679), and 180-day mortality 29.6% (2566/8679). The latter was 52.3% (1472/2817) for patients aged ≥ 80 years, and 53.0% for patients who had been ventilated invasively (853/1608). Risk factors for 180-day mortality included coagulopathy, BMI ≥ 40, and age. Female sex was a protective factor. Of 6235 patients discharged alive, 1668 patients were readmitted a total of 2551 times within 180 days, resulting in an overall readmission rate of 26.8%.LimitationsWe could not stratify patients by ICU treatment as it is not coded separately. Furthermore, we cannot exclude residual confounding in our analysis of risk factors nor determine causality between risk factors and long-term mortality given the observational nature of this study.ConclusionThis nationwide cohort study of hospitalized COVID-19 patients in Germany found considerable long-term mortality and readmission rates, especially among patients with coagulopathy. Close follow-up after hospital discharge may improve long-term outcome.

PurposeTo quantify the frequency and co-occurrence of new diagnoses consistent with post-sepsis morbidity, mortality, new nursing care dependency, and total healthcare costs after sepsis.MethodsPopulation-based cohort study using healthcare claims data from 23 million beneficiaries of a German health insurance provider. We included adult patients with incident hospital-treated sepsis identified by ICD-10 codes in 2013-2014. New medical, psychological and cognitive diagnoses associated with post-sepsis morbidity; mortality; dependency on nursing care; and total health care costs in survivors were assessed to 3 years after hospital discharge.ResultsAmong 116,507 sepsis patients who survived hospitalization for sepsis, 74.3% had a new medical, psychological or cognitive diagnosis in the first year after discharge. 20.6% and 3.8% had new diagnoses in two and three domains, respectively. 31.5% were newly dependent on nursing care, and 30.7% died within the first year. In the second and third year, 65.8% and 59.4% of survivors had new diagnoses, respectively. Healthcare costs totaled an average 36,585 Euro/patient in three years, including index hospitalization costs. Occurrence of new diagnoses in predefined subgroups was: 73.7% (survivors of non-severe sepsis), 75.6% (severe sepsis), 78.3% (ICU-treated sepsis), 72.8% (non-ICU treated sepsis) and 68.5% (survivors without prior diagnoses).ConclusionsNew medical, psychological and cognitive diagnoses consistent with post-sepsis morbidity are common after sepsis, including among patients with less severe sepsis, no prior diagnoses, and younger age. This calls for more efforts to elucidate the underlying mechanisms, define optimal screening for common new diagnoses, and test interventions to prevent and treat post-sepsis morbidity.Trial RegistrationDRKS00016340Take home messageThis large population-based cohort of over 100,000 survivors of hospital-treated sepsis found high rates and a broad spectrum of new diagnoses consistent with post-sepsis morbidity, frequent new nursing care dependency, and high long-term mortality 1-3 years post sepsis. Post-sepsis morbidity was not limited to the oldest survivors or those with the most severe illness, but also affected younger survivors and those without pre-existing diagnoses.

In Germany, the Diagnosis-Related Group Statistics (DRG Statistics) supply full coverage of inpatient episodes in acute care hospitals. The Research Data Centres of the Federal Statistical Office and the Statistical Offices of the Federal States provide the microdata of the DRG Statistics, namely hospital discharge files of each inpatient case, for scientific research. Hospital discharge data are generated for administrative purposes. As well as other data sources, they have specific features and characteristics, which should be considered in planning and designing research studies. A key challenge is the appropriate and sophisticated operationalization of units of analysis, targets variables, and other study variables. The methodological approach should consider, among other factors, differing coding behaviour between hospitals in order to minimize the risk of bias. This contribution shows by practical examples what should be incorporated in variable definition to ensure that the risk of bias by coding behaviour or other factors is minimized to the greatest possible degree. First of all, the features and characteristics of the German hospital discharge data are outlined. Based on the authors' experiences, basic steps and challenges in observational health services research studies are described. Examples are illustrated by our own calculations, derived from previous studies based on the microdata of the DRG Statistics. The reliability and validity of analyses based on hospital discharge data are crucially dependent on the appropriateness of variable definition. To minimize the risk of bias and misinterpretation, extensive preliminary considerations are required which involve clinical aspects, as well as the context of data collection and technical classification opportunities. Hopefully, there will be greater acceptance of research based on hospital discharge data, so that these valuable data will be used more frequently for research purposes in the future.In Deutschland ist mit der Fallpauschalenbezogenen Krankenhausstatistik (DRG-Statistik) eine Vollerhebung der Abrechnungsdaten nahezu aller akutstationären Krankenhausbehandlungsfälle verfügbar. Die Mikrodaten, d. h. die Datensätze der einzelnen Behandlungsfälle, werden von den Forschungsdatenzentren der Statistischen Ämter des Bundes und der Länder für die wissenschaftliche Nutzung bereitgestellt. Krankenhausabrechnungsdaten werden zu Abrechnungszwecken erhoben und haben – wie andere Datenquellen auch – spezifische Besonderheiten und Eigenschaften, die bei der Planung von Analysen und im Studiendesign angemessen berücksichtigt werden müssen. Eine besondere Herausforderung ist dabei die sachgerechte Operationalisierung von Analyseeinheiten, Zielgrößen und weiteren Variablen, die u. a. eine mögliche unterschiedliche Kodierpraxis in verschiedenen Krankenhäusern antizipiert und deren Auswirkungen über eine durchdachte Variablendefinition minimiert. In diesem Beitrag wird anhand von praktischen Beispielen aufgezeigt, was bei der Definition von Variablen in fallbezogenen Krankenhausabrechnungsdaten beachtet werden sollte, um das Risiko von kodierungs- oder anderweitig bedingten Verzerrungen möglichst gering zu halten. Ausgehend von den Erfahrungen der Autoren werden die wichtigsten Schritte und Herausforderungen in Bezug auf ein typisches retrospektives Beobachtungsstudiendesign in der Versorgungsforschung beschrieben. Basierend auf bereits durchgeführten Projekten auf der Grundlage der Mikrodaten der Fallpauschalenbezogenen Krankenhausstatistik (DRG-Statistik) werden Beispiele anhand eigener Berechnungen illustriert. Die Verlässlichkeit und Interpretierbarkeit von Analysen auf der Grundlage der Mikrodaten der DRG-Statistik hängt entscheidend von der sachgerechten Operationalisierung der Variablen ab. Um das Risiko von Verzerrungen und Fehlinterpretationen möglichst gering zu halten, sind umfangreiche Vorüberlegungen notwendig, die neben medizinisch-klinischen Aspekten auch den Kontext der Datenerhebung und die klassifikatorischen Möglichkeiten zur Abbildung bestimmter Sachverhalte berücksichtigen. Es ist zu hoffen, dass die Akzeptanz von Studien auf der Grundlage von Krankenhausabrechnungsdaten weiter zunimmt und der wertvolle Datenbestand der DRG-Statistik in Zukunft noch intensiver für Forschungszwecke genutzt wird.

Amputations reduce irreversibly the quality of life. Health care always aims at avoiding amputations, and the quality of such care provided nationwide should be the same. This study aims to display rates of amputations at the county level and to uncover differences in health care.Using German nationwide hospital discharge data, amputations between 2011 and 2015 were identified. Regional variation is displayed using raw and risk-standardized rates per 100,000 persons. Furthermore, the Systematic Component of Variation (SCV) was computed and Funnel Plots display the Standardized Morbidity Ratio (SMR).The median amputation rate during the observation period was 67 cases per 100,000 persons with a 6-fold variation between counties. Variation between counties remained independent of demographic differences. Higher rates got visible especially within counties in the East and Southeast. The highest systematic variation was seen in amputation heights toe/foot ray (SCV 11.8) and foot complete and mid-/forefoot (SCV 11.7).In Germany, there are significant regional variations of amputation rates at the county level. The systematic variation is strongest within peripheral amputation heights. Especially in the East and Southeast of Germany, clusters of high amputation rates give insights in the potential regional need for improvement.Amputationen vermindern irreversibel die Lebensqualität. Das Ziel vorangehender Versorgung ist stets eine Amputation zu verhindern. Diese Versorgung sollte bundesweit mit derselben Ergebnisqualität gewährleistet sein. Ziel dieser Arbeit ist es, regionale Versorgungsunterschiede sichtbar zu machen, indem Amputationsfallzahlen nach Amputationshöhen auf Kreisebene analysiert werden.In den deutschlandweiten Krankenhausabrechnungsdaten (DRG-Statistik) wurden alle Behandlungsfälle mit Amputation an der unteren Extremität zwischen 2011 und 2015 identifiziert. Auf Kreisebene wurden rohe Raten sowie alters- und geschlechtsstandardisierte Raten pro 100 000 Einwohner dargestellt. Daneben wurde die systematische Variationskomponente (SCV) zwischen den Kreisen betrachtet und das standardisierte Morbiditätsverhältnis (SMR) in Funnel Plots dargestellt.Im Beobachtungszeitraum belief sich die mediane jährliche Amputationsrate auf 67 Fälle pro 100 000 Einwohner. Auf Kreisebene variierte die rohe Rate um das 6-fache. Unabhängig von demografischen Unterschieden zeigten sich Variationen zwischen den Kreisen. Erhöhte Amputationsraten wurden überwiegend im Osten und Südosten beobachtet. Die Variationen waren bei den Amputationshöhen Zeh/Zehenstrahl (SCV 11,8) und Fuß komplettMittel-/Vorfuß (SCV 11,7) am stärksten ausgeprägt.Es bestehen deutliche regionale Unterschiede in den Amputationsraten. Bei peripheren Amputationshöhen ist die systematische Variation am stärksten. Insbesondere im Osten und Südosten sind regionale Cluster erkennbar, die Anhaltspunkte für einen möglichen regionalen Verbesserungsbedarf in der Versorgung liefern.

Hintergrund Seit der Einführung der Diagnosis related Groups (DRG) zur Vergütung akutstationärer Krankenhausleistungen wurden Anstiege der stationären Fallzahlen zur Behandlung von Erkrankungen der Wirbelsäule beobachtet. Ziel dieser Arbeit ist, diese Mengenentwicklung bevölkerungsbezogen und nach Behandlungsarten differenziert darzustellen. Material und Methode In den deutschlandweiten Krankenhausabrechnungsdaten (DRG-Statistik) wurden Behandlungsfälle mit operativer sowie nicht operativer Versorgung von Wirbelsäulenerkrankungen identifiziert. Unter Berücksichtigung der demografischen Entwicklung wurde analysiert, in welchem Umfang sich die Fallzahlen im Zeitraum von 2005 bis 2014 verändert haben und in welchen Altersgruppen und bei welchen Eingriffs- bzw. Behandlungsarten Anstiege zu verzeichnen sind. Ergebnisse Im Jahr 2014 (2005) wurden 289 000 (177 000) operativ versorgte und 463 000 (287 000) nicht operativ versorgte Behandlungsfälle identifiziert. Nach Bereinigung um demografische Faktoren wurden sowohl bei operativen als auch bei nicht operativen Behandlungen relative Fallzahlanstiege um jeweils ca. 50% beobachtet, die in höheren Altersgruppen und bei Frauen besonders ausgeprägt waren. Die Mengenentwicklung fiel je nach Art des Eingriffs bzw. der Behandlung sehr unterschiedlich aus. Bei den operativ versorgten Behandlungsfällen hat sich die Anzahl der Bandscheibenoperationen demografiebereinigt nur um + 5% erhöht während sich Wirbelkörperversteifungs- und -ersatzeingriffe, Kypho- und Vertebroplastien und alleinige Dekompressionen der Wirbelsäule mehr als verdoppelt haben. Bei den nicht operativ versorgten Behandlungsfällen wurde bei Behandlungen mit lokaler Schmerztherapie der Wirbelsäule ein demografiebereinigter Anstieg von + 142% beobachtet. Bei rein konservativen Behandlungen lag der demografiebereinigte Anstieg bei + 22%. Schlussfolgerung Welche Ursachen den nicht demografiebedingten Fallzahlanstiegen zugrunde liegen, kann diese Untersuchung nicht direkt klären. Die stratifizierte Betrachtung der Fallzahlen in den verschiedenen Untergruppen kann aber dazu beitragen, die Entwicklungen differenziert einzuordnen und damit die Diskussion um eine mögliche Über- oder Fehlversorgung zielgerichteter als bisher zu führen., Background Marked volume growth of inpatient treatments for spinal disease has been observed since diagnosis related groups (DRG) were introduced as payment for inpatient services in Germany. This study aims to analyse this increase by population and stratified by types of treatment. Material and Methods Using German nationwide hospital discharge data (DRG statistics), inpatient treatments for spinal disease with or without surgery were identified. Trends in case numbers were analysed from 2005 to 2014 with consideration of demographic changes, in order to explore which age groups and which types of treatment are affected by volume growth. Results In 2014 (2005), 289 000 (177 000) inpatient treatments with surgery and 463 000 (287 000) treatments without surgery were identified. After adjusting for demographic factors, treatments with and without surgery exhibited a relative volume growth of + 50%. This increase affected higher age groups and women, in particular. Depending on the type of treatment, very different degrees of volume growth were observed. For example, disc surgeries adjusted for demographic change increased by about + 5%, whereas spinal fusion and vertebral replacement surgeries, kypho-/vertebroplasties and decompression of the spine more than doubled. Within the non-surgically treated cases, local pain therapies of the spine increased after adjustment for demographic changes by about + 142%. The conservatively treated cases showed a demographically adjusted increase of + 22%. Conclusion Apart from demographic changes, this analysis cannot resolve the underlying causes of volume growth in treatments for spinal disease. However, the stratified analysis of various subgroups may help to classify these developments in a more differentiated manner. The results may support a more targeted debate about potential over- or misallocation of inpatient services in this area.

The mobile Food Record (mFR) is an image-based dietary assessment method for mobile devices. The study primary aim was to test the accuracy of the mFR by comparing reported energy intake (rEI) to total energy expenditure (TEE) using the doubly labeled water (DLW) method. Usability of the mFR was assessed by questionnaires before and after the study. Participants were 45 community dwelling men and women, 21–65 years. They were provided pack-out meals and snacks and encouraged to supplement with usual foods and beverages not provided. After being dosed with DLW, participants were instructed to record all eating occasions over a 7.5 days period using the mFR. Three trained analysts estimated rEI from the images sent to a secure server. rEI and TEE correlated significantly (Spearman correlation coefficient of 0.58, p < 0.0001). The mean percentage of underreporting below the lower 95% confidence interval of the ratio of rEI to TEE was 12% for men (standard deviation (SD) ± 11%) and 10% for women (SD ± 10%). The results demonstrate the accuracy of the mFR is comparable to traditional dietary records and other image-based methods. No systematic biases could be found. The mFR was received well by the participants and usability was rated as easy.