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Hintergrund: Patient:innensicherheit nimmt als ethischer Grundpfeiler medizinischen Handelns sowie als Gut öffentlichen Interesses eine Schlüsselposition in der Gesundheitsversorgung ein. Die Patient:innensicherheit der stationären Akutversorgung soll unter anderem durch legislativ verbindliche Qualitätssicherung und -indikatoren sowie mittels Durchsetzung leistungsberechtigender Mindestfallmengen bei komplexen medizinischen Fällen gewährt und kontinuierlich verbessert werden. Medizinische Fälle unterscheiden sich in ihrer Komplexität im Hinblick auf Alter, Geschlecht und Komorbiditäten. Das stationäre Versorgungssetting unterscheidet sich beispielsweise im Aufnahmezeitpunkt und Aufnahmeanlass, durchgeführter (chirurgischer) Prozedur und der Anzahl an der Versorgung beteiligten Stationen. Stationäre Versorger selbst weisen Unterschiede unter anderem hinsichtlich Versorgungsfähigkeit und -auftrag, Trägerschaft, Bettengröße, Personalschlüssel und -qualifikation sowie Fallmenge auf. Fallindividuell werden in der Qualitätssicherung und in Fallmenge-Outcome-Analysen die Risiko-faktoren Alter, Geschlecht und Komorbiditäten statistisch berücksichtigt, jedoch nicht das rahmengebende Versorgungs- oder Versorgersetting. Fragestellung / Hypothese: Das Ziel dieser Dissertation war es, den Einfluss von Versorger- und Versorgungs-variablen auf multiple Patient:innensicherheitsoutcomes mehrerer stationär behandelter Indikationen unter Nutzung unterschiedlicher Daten und Methoden zu analysieren. Für den stationären Versorgungskontext steht der Aufnahmeanlass als Surrogatvariable für die Akuität des Falls (Forschungsziel 1) im Fokus. Für die stationären Versorger sollte aufgrund der legislativen Implikation der Einfluss der Fallmenge untersucht werden (Forschungsziel 2). Aus diesen zwei Forschungszielen wurden drei Einzelfrage-stellungen abgeleitet, analysiert und im Rahmen von drei Publikationen beantwortet: (1) Ist das Geburtsoutcome bei Niedrigrisiko-Geburten mit der Fallmenge de

Objectives Studies analysing colorectal resections usually focus on a specific outcome (eg, mortality) and/or specific risk factors at the individual (eg, comorbidities) or hospital (eg, volume) level. Comprehensive evidence across different patient safety outcomes, risk factors and patient groups is still scarce. Therefore the aim of this analysis was to investigate consistent relationships between multiple patient safety outcomes, healthcare and hospital risk factors in colorectal resection cases. Design Cross-sectional study. Setting German inpatient routine care data of colorectal resections between 2016 and 2018. Participants We analysed 54 168 colon resection and 20 395 rectum resection cases treated in German hospitals. The German Inpatient Quality Indicators were used to define colon resections and rectum resections transparently. Primary outcome measures Additionally to in-hospital death, postoperative respiratory failure, renal failure and postoperative wound infections we included multiple patient safety outcomes as primary outcomes/dependent variables for our analysis. Healthcare (eg, weekend surgery), hospital (eg, volume) and case (eg, age) characteristics served as independent covariates in a multilevel logistic regression model. The estimated regression coefficients were transferred into ORs. Results Weekend surgery, emergency admissions and transfers from other hospitals were significantly associated (ORs ranged from 1.1 to 2.6) with poor patient safety outcome (ie, death, renal failure, postoperative respiratory failure) in colon resections and rectum resections. Hospital characteristics showed heterogeneous effects. In colon resections hospital volume was associated with insignificant or adverse associations (postoperative wound infections: OR 1.168 (95% CI 1.030 to 1.325)) to multiple patient safety outcomes. In rectum resections hospital volume was protectively associated with death, renal failure and postoperative respiratory failure (ORs range

Background Although clinical peer review is a well-established instrument for improving quality of care, clinical effectiveness is unclear. Methods In a pragmatic cluster randomised controlled trial, we randomly assigned 60 German Initiative Qualitätsmedizin member hospitals with the highest mortality rates in ventilated patients in 2016 to intervention and control groups. The primary outcome was hospital mortality rate in patients ventilated fore more than 24 hours. Clinical peer review was conducted in intervention group hospitals only. We assessed the impact of clinical peer review on mortality using a difference-in-difference approach by applying weighted least squares (WLS) regression to changes in age-adjusted and sex-adjusted standardised mortality ratios (SMRs) 1 year before and 1 year after treatment. Recommendations for improvement from clinical peer review and hospital survey data were used for impact and process analysis. Results We analysed 12 058 and 13 016 patients ventilated fore more than 24 hours in the intervention and control hospitals within the 1-year observation period. In-hospital mortality rates and SMRs were 40.6% and 1.23 in intervention group and 41.9% and 1.28 in control group hospitals in the preintervention period, respectively. The groups showed similar hospital (bed size, ownership) and patient (age, sex, mortality, main indications) characteristics. WLS regression did not yield a significant difference between intervention and control groups regarding changes in SMRs (estimate=0.04, 95% CI= −0.05 to 0.13, p=0.38). Mortality remained high in both groups (intervention: 41.8%, control: 42.1%). Impact and process analysis indicated few perceived outcome improvements or implemented process improvements following the introduction of clinical peer review. Conclusions This study did not provide evidence for reductions in mortality in patients ventilated for more than 24 hours due to clinical peer review. A stronger focus on identification o

As of late 2019, the COVID-19 pandemic has been a challenge to health care systems worldwide. Rapidly rising local COVID-19 incidence rates, result in demand for high hospital and intensive care bed capacities on short notice. A detailed up-to-date regional surveillance of the dynamics of the pandemic, precise prediction of required inpatient capacities of care as well as a centralized coordination of the distribution of regional patient fluxes is needed to ensure optimal patient care. In March 2020, the German federal state of Saxony established three COVID-19 coordination centers located at each of its maximum care hospitals, namely the University Hospitals Dresden and Leipzig and the hospital Chemnitz. Each center has coordinated inpatient care facilities for the three regions East, Northwest and Southwest Saxony with 36, 18 and 29 hospital sites, respectively. Fed by daily data flows from local public health authorities capturing the dynamics of the pandemic as well as daily reports on regional inpatient care capacities, we established the information and prognosis tool DISPENSE. It provides a regional overview of the current pandemic situation combined with daily prognoses for up to seven days as well as outlooks for up to 14 days of bed requirements. The prognosis precision varies from 21% and 38% to 12% and 15% relative errors in normal ward and ICU bed demand, respectively, depending on the considered time period. The deployment of DISPENSE has had a major positive impact to stay alert for the second wave of the COVID-19 pandemic and to allocate resources as needed. The application of a mathematical model to forecast required bed capacities enabled concerted actions for patient allocation and strategic planning. The ad-hoc implementation of these tools substantiates the need of a detailed data basis that enables appropriate responses, both on regional scales in terms of clinic resource planning and on larger scales concerning political reactions to pandemic