Since the year 2000, prospective dental students at Innsbruck Medical University, Innsbruck, Austria, have undergone both theoretical and practical preadmission exams, called the Dental Admission Test (DAT). The aim of this investigation was to assess the suitability and outcome of this selection practice. Five classes from 2001 to 2005 (N=97; forty-three female, fifty-four male) were retrospectively reviewed. DAT results were compared with student performance, gender, ability to graduate on time, and dropout rates. Furthermore, the influence of a previous medical degree was evaluated. The t-test was used to analyze correlations between the results of the DAT and the following: gender, students who graduated on time, and students who had previously completed a medical degree. Pearson's correlation coefficient (r) was applied to analyze correlations among test scores, age, and students' performance during the first clinical year. Students graduating on time were noted to have significantly better DAT results; students with a previous medical degree showed significantly better grades during their first clinical year. The difference between the performance of male and female applicants on the DAT was not significant. Correlation was found between DAT results and dental school performance (r=-0.462). We conclude that the DAT may reduce dropout rates by excluding applicants unlikely to be successful in practical courses and that DAT scores are a reliable tool to predict student performance during the first clinical year of dental school in Innsbruck.

(1) Background: The Austrian supply of COVID-19 vaccine is limited for now. We aim to provide evidence-based guidance to the authorities in order to minimize COVID-19-related hospitalizations and deaths in Austria. (2) Methods: We used a dynamic agent-based population model to compare different vaccination strategies targeted to the elderly (65 ≥ years), middle aged (45–64 years), younger (15–44 years), vulnerable (risk of severe disease due to comorbidities), and healthcare workers (HCW). First, outcomes were optimized for an initially available vaccine batch for 200,000 individuals. Second, stepwise optimization was performed deriving a prioritization sequence for 2.45 million individuals, maximizing the reduction in total hospitalizations and deaths compared to no vaccination. We considered sterilizing and non-sterilizing immunity, assuming a 70% effectiveness. (3) Results: Maximum reduction of hospitalizations and deaths was achieved by starting vaccination with the elderly and vulnerable followed by middle-aged, HCW, and younger individuals. Optimizations for vaccinating 2.45 million individuals yielded the same prioritization and avoided approximately one third of deaths and hospitalizations. Starting vaccination with HCW leads to slightly smaller reductions but maximizes occupational safety. (4) Conclusion: To minimize COVID-19-related hospitalizations and deaths, our study shows that elderly and vulnerable persons should be prioritized for vaccination until further vaccines are available.

Objectives: To inform allocation decisions in any healthcare system, robust cost data are indispensable. Nevertheless, recommendations on the most appropriate valuation approaches vary or are nonexistent, and no internationally accepted gold standard exists. This costing analysis exercise aims to assess the impact and implications of different calculation methods and sources based on the unit cost of general practitioner (GP) consultations in Austria.Methods: Six costing methods for unit cost calculation were explored, following 3 Austrian methodological approaches (AT-1, AT-2, AT-3) and 3 approaches applied in 3 other European countries (Germany, The Netherlands, United Kingdom). Drawing on Austrian data, mean unit costs per GP consultation were calculated in euros for 2015.Results: Mean unit costs ranged from V15.6 to V42.6 based on the German top-down costing approach (DE) and the Austrian Physicians' Chamber's price recommendations (AT-3), respectively. The mean unit cost was estimated at V18.9 based on Austrian economic evaluations (AT-1) and V17.9 based on health insurance payment tariffs (AT-2). The Dutch top-down (NL) and the UK bottom-up approaches (UK) yielded higher estimates (NL: V25.3, UK: V29.8). Overall variation reached 173%.Conclusions: Our study is the first to systematically investigate the impact of differing calculation methods on unit cost estimates. It shows large variations with potential impact on the conclusions in an economic evaluation. Although different methodological choices may be justified by the adopted study perspective, different costing approaches introduce variation in cross-study/cross-country cost estimates, leading to decreased confidence in data quality in economic evaluations.

No abstract

Real-world data (RWD) collected in routine health care processes and transformed to real-world evidence have become increasingly interesting within the research and medical communities to enhance medical research and support regulatory decision-making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which qualities RWD must meet in order to be acceptable for decision-making within regulatory or routine clinical decision support. In the absence of guidelines defining the quality standards for RWD, an overview and first recommendations for quality criteria for RWD in pharmaceutical research and health care decision-making is needed in Austria. An Austrian multistakeholder expert group led by Gesellschaft für Pharmazeutische Medizin (Austrian Society for Pharmaceutical Medicine) met regularly; reviewed and discussed guidelines, frameworks, use cases, or viewpoints; and agreed unanimously on a set of quality criteria for RWD. This consensus statement was derived from the quality criteria for RWD to be used more effectively for medical research purposes beyond the registry-based studies discussed in the European Medicines Agency guideline for registry-based studies. This paper summarizes the recommendations for the quality criteria of RWD, which represents a minimum set of requirements. In order to future-proof registry-based studies, RWD should follow high-quality standards and be subjected to the quality assurance measures needed to underpin data quality. Furthermore, specific RWD quality aspects for individual use cases (eg, medical or pharmacoeconomic research), market authorization processes, or postmarket authorization phases have yet to be elaborated.