@article{DotterHaugSchnelletal., author = {Dotter, Caroline and Haug, Sonja and Schnell, Rainer and Raptis, Georgios and Weber, Karsten}, title = {Sharing health data for research purposes: results of a population survey in Germany}, series = {BMC health services research}, volume = {25}, journal = {BMC health services research}, publisher = {BMC}, doi = {10.1186/s12913-025-12706-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-81622}, pages = {9}, abstract = {BACKGROUND: Increased use of health data has the potential to improve both health care and health policies. Several recent policy initiatives at the European and German legislative levels aim to increase the primary and secondary use of health data. However, little is known about general population views on health data access for research. Most studies are based on subsets defined by specific illnesses. METHODS: We commissioned a national computer-assisted dual-frame telephone survey (landline and mobile). Logit estimation models were used to identify predictors of willingness to provide access to health data to different organizations (universities in Germany, universities worldwide, German government organizations, pharmaceutical companies). RESULTS: A high willingness to share health data for research purposes is observed, depending on the specific data recipient. The willingness is highest for research at universities in Germany and German governmental organizations, and lowest regarding research by pharmaceutical companies. The main drivers for sharing health data are the level of trust in public institutions, the respondents' assessment of the seriousness and likelihood of data misuse, and the level of digital literacy. Age, gender, and level of education have small effects and do not determine the willingness to share health data for all organizations. CONCLUSION: We present evidence from a random sample of the German population. The results indicate widespread support among the population for providing access to health data for research purposes. Similar to findings in other countries, the willingness depends strongly on the recipient of the data. This paper evaluates the impact of various determinants - identified in previous qualitative and quantitative research - on the willingness of the German population to share health data. While previous studies have found that patients are generally more willing to share health data, we found that the presence of a medical precondition does not translate into respondents' unequivocal support for health data sharing. We identify privacy concerns, general trust, and digital literacy as key factors influencing the willingness to share health data. Therefore, policymakers and stakeholders need to ensure and communicate the necessary privacy protection measures to increase the willingness of the German population to share health data.}, language = {en} } @article{HeinzSchildgen, author = {Heinz, Florian and Schildgen, Johannes}, title = {Experience Report: Hey LLM, Generate SQL!}, series = {Datenbank-Spektrum}, volume = {25}, journal = {Datenbank-Spektrum}, number = {2}, publisher = {Springer}, address = {Wiesbaden}, doi = {10.1007/s13222-025-00512-w}, pages = {95 -- 101}, abstract = {Large Language Models have advanced to a resourceful tool with many applications. One particularly interesting use case is the LLM-aided generation of ad-hoc database queries and the possibility of subsequent processing of the results in a way suiting the users intents. In this article, practical ways and experiences are described on how to effectively use LLMs to map a natural-language user query to an SQL query conforming to a specific database schema and post-processing the results of this query in order to, for example, create an appealing visualization. Best results are achieved under favorable circumstances, as, for example, a clean and meaningful named database schema.}, language = {en} }