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Purpose Patients with rare diseases often undergo a long diagnostic odyssey. However, there is little empirical evidence on the cost incurred during the diagnostic pathway for patients with suspected rare diseases. This study provides a comprehensive analysis of healthcare costs and utilization during the diagnostic pathway for a heterogeneous sample of patients with suspected rare diseases but unclear diagnosis. Methods Using claims data from five German statutory health insurance organizations for the years 2014–2019, we analyzed costs and healthcare utilization of 1,243 patients (aged 0 to 82 years) with suspected rare diseases referred to a rare disease center. A control cohort was assigned using 1:75 exact matching on age, sex and place of residence. Results In the years prior to referral to an expert center, healthcare utilization of patients with suspected rare diseases was, on average, substantially and significantly higher compared to a matched control cohort during the same observation period – e.g. in terms of the number of hospitalizations (3.1 (95%CI: 2.9–3.4) vs. 0.5 (95%CI: 0.5–0.5)), different diagnoses (50.0 (95%CI: 48.1–51.9) vs. 26.4 (95%CI: 26.2–26.5)), different active substances prescribed (12.7 (95%CI: 12.2–13.3) vs. 8.2 (95%CI: 8.2–8.3)) and the number of genetic tests (14.7 (95%CI: 12.6–16.7) vs. 0.3 (95%CI: 0.3–0.3)). We found evidence of heterogeneity in utilization by age and sex. On average, direct costs (inpatient, outpatient and prescription drug costs) of patients with suspected rare diseases during the diagnostic pathway were 7.6-fold higher than the costs of matched controls (€26,999 (95%CI: €23,751 − 30,247) vs. €3,561 (95% CI: € 3,455-3,667)). Inpatient costs were the main cost component, accounting for 62.5% of total costs. Conclusions The diagnostic odyssey of patients with suspected rare diseases is associated with extensive healthcare utilization and high cost. Against this background, new ways to shorten the diagnostic journey have a high potential to decrease the financial burden related to rare diseases.

Background The Perinatal Center of the University Hospital Carl Gustav Carus Dresden has initiated the telemedical healthcare network “SAFE BIRTH” to coordinate and improve specialized care in non-metropolitan regions for pregnant women and newborns. The network incorporates five intervention bundles (IB): (1) Multi-professional, inter-disciplinary prenatal care plan; (2) Neonatal resuscitation; (3) Neonatal antibiotic stewardship; (4) Inter-facility transfer of premature and sick newborns; (5) Psycho-social support for parents. We evaluate if the network improves care close to home for pregnant women, premature and sick newborns. Methods To evaluate the complex healthcare intervention “SAFE BIRTH” we will conduct a cluster-randomized controlled stepped-wedge trial in five prenatal medical outpatient offices and eight non-metropolitan hospitals in Saxony, Germany. The offices and hospitals will be randomly allocated to five respectively eight sequential steps over a 30-month period to implement the telemedical IB. We define one specific primary process outcome for each IB (for instance IB#1: “ Proportion of patients with inclusion criterion IB#1 who have a prenatal care plan and psychosocial counseling within one week” ). We estimated a separate multilevel logistic regression model for each primary process outcome using the intervention status as a regressor (control or intervention group). Across all IB, a total of 1,541 and 1,417 pregnant women or newborns need to be included in the intervention and control group, respectively, for a power above 80% for small to medium intervention effects for all five hypothesis tests. Additionally, we will assess job satisfaction and sense of safety of health professionals caring for newborns (questionnaire survey) and we will assess families’ satisfaction, resilience, quality of life and depressive, anxiety and stress symptoms (questionnaire surveys). We will also evaluate the cost-effectiveness of ”SAFE BIRTH” (statutory health insurance routine data, process data) and barriers to its implementation (semi-structured interviews). We use multilevel regression models adjusting for relevant confounders (e.g. socioeconomic status, age, place of residence), as well as descriptive analyses and qualitative content analyses. Discussion If the telemedical healthcare network “SAFE BIRTH” proves to be effective and cost-efficient, strategies for its translation into routine care should be developed. Trial registration German clinical trials register. DRKS-ID: DRKS00031482.

To obtain a more complete understanding of the persisting gender earnings gap in Germany, this paper investigates both the cross-sectional and biographical dimension of gender inequalities. Using an Oaxaca Blinder decomposition, we show that the gender gap in annual earnings is largely driven by women’s lower work experience and intensive margin of labor supply. Based on a dynamic microsimulation model, we then estimate how gender differences accumulate over work lives to account for the biographical dimension of the gender gap. We observe an average gender lifetime earnings gap of 51.5 percent for birth cohorts 1964-1972. We show that this unadjusted gender lifetime earnings gap increases strongly with the number of children, ranging from 17.8 percent for childless women to 68.0 percent for women with three or more children. However, using a counterfactual analysis we find that the adjusted gender lifetime earnings gap of 10 percent differs only slightly by women’s family background.

To obtain a more complete understanding of the persisting gender earnings gap in Germany, this paper investigates both the cross-sectional and biographical dimension of gender inequalities. Using an Oaxaca Blinder decomposition, we show that the gender gap in annual earnings is largely driven by women's lower work experience and intensive margin of labor supply. Based on a dynamic microsimulation model, we then estimate how gender differences accumulate over work lives to account for the biographical dimension of the gender gap. We observe an average gender lifetime earnings gap of 51.5 percent for birth cohorts 1964-1972. We show that this unadjusted gender lifetime earnings gap increases strongly with the number of children, ranging from 17.8 percent for childless women to 68.0 percent for women with three or more children. However, using a counterfactual analysis we find that the adjusted gender lifetime earnings gap of 10 percent differs only slightly by women's family background.

Ungleichheitsstudien basieren in der Regel auf Daten zu Jahres- oder Monatseinkommen, um die Verteilung ökonomischer Ressourcen zu einem bestimmten Zeitpunkt im Querschnitt einer Bevölkerung zu bestimmen. Analysen auf Jahres- oder Monatsquerschnitten können jedoch ein unvollständiges Bild liefern, da sie oft nur erwerbstätige Individuen betrachten und sich die individuellen Positionen in der Einkommensverteilung über das Erwerbsleben einer Person ändern. Ein umfassenderes Bild bieten Lebenserwerbseinkommen. Die Analyse von Lebenserwerbseinkommen setzen Informationen über vollständige Erwerbsbiografien voraus. Informationen, die wenn überhaupt nur für spezielle Bevölkerungsgruppen in Form von administrativen Daten der Sozialversicherung vorliegen. Um eine geeignete Datengrundlage zur Analyse von Lebenserwerbseinkommen der gesamten Bevölkerung zu schaffen, nutzen wir eine dynamische Mikrosimulation auf Basis des Sozioökonomischen Panels um vollständige Erwerbsbiografien für die Kohorten 1964 bis 1985 bis ins Jahr 2045 zu konstruieren. Wir können zeigen, dass sich der Unterschied zwischen den Lebenserwerbseinkommen Gering- und Hochqualifizierter Männer in Preisen von 2015 auf über eine Million Euro beläuft, Geringqualifizierte verdiene im Lauf ihres Lebens nur knapp 40 Prozent des Erwerbseinkommens eines Hochqualifizierten. Gleichzeitig finden wir, dass zwischen 1981 und 1985 geborene Frauen im Durchschnitt über den Lebensverlauf hinweg nur rund 55 Prozent der Erwerbseinkommen der Männer verdienen.