BeoNet-Halle—development of a multifunctional database for the automated extraction of healthcare data from general practitioner and specialist practices

Moser, Konstantin; Mikolajczyk, Rafael; Bauer, Alexander; Tiller, Daniel; Christoph, Jan; Purschke, Oliver; Lückmann, Sara Lena; Frese, Thomas

doi:10.1007/s00103-023-03691-7

Cited by 4 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RADARplus (Routine Anonymised Data for Advanced Health Services Research plus) aims to develop the infrastructure and technologies, including electronic consent management due to the German data protection regulations, and collects data from seven practices including 100 pseudonymous cases 21. BeoNet-Halle is the most recent database and includes anonymised as well as linked pseudonymised data sets from general practices and other types of practices in Germany 26. The database includes 71 911 anonymised and 471 pseudonymised data sets from five practices in Saxony-Anhalt region.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

German primary care data collection projects: a scoping review

Moser,

Massag,

Frese

et al. 2024

BMJ Open

Self Cite

View full text Add to dashboard Cite

BackgroundThe widespread use of electronic health records (EHRs) has led to a growing number of large routine primary care data collection projects globally, making these records a valuable resource for health services and epidemiological and clinical research. This scoping review aims to comprehensively assess and compare strengths and limitations of all German primary care data collection projects and relevant research publications that extract data directly from practice management systems (PMS).MethodsA literature search was conducted in the electronic databases in May 2021 and in June 2022. The search string included terms related to general practice, routine data, and Germany. The retrieved studies were classified as applied studies and methodological studies, and categorised by type of research, subject area, sample of publications, disease category, or main medication analysed.ResultsA total of 962 references were identified, with 241 studies included from six German projects in which databases are populated by EHRs from PMS. The projects exhibited significant heterogeneity in terms of size, data collection methods, and variables collected. The majority of the applied studies (n = 205, 85%) originated from one database with a primary focus on pharmacoepidemiological topics (n = 127, 52%) including prescription patterns (n = 68, 28%) and studies about treatment outcomes, compliance, and treatment effectiveness (n = 34, 14%). Epidemiological studies (n = 77, 32%) mainly focused on incidence and prevalence studies (n = 41, 17%) and risk and comorbidity analysis studies (n = 31, 12%). Only 10% (n = 23) of studies were in the field of health services research, such as hospitalisation.ConclusionThe development and durability of primary care data collection projects in Germany is hindered by insufficient public funding, technical issues of data extraction, and strict data protection regulations. There is a need for further research and collaboration to improve the usability of EHRs for health services and research.

show abstract

Section: Resultsmentioning

confidence: 99%

“… 21 BeoNet-Halle is the most recent database and includes anonymised as well as linked pseudonymised data sets from general practices and other types of practices in Germany. 26 The database includes 71 911 anonymised and 471 pseudonymised data sets from five practices in Saxony-Anhalt region.…”

Section: Resultsmentioning

confidence: 99%

German primary care data collection projects: a scoping review

Moser,

Massag,

Frese

et al. 2024

BMJ Open

Self Cite

View full text Add to dashboard Cite

show abstract

“…In glycoinformatics, which is a field of informatics that deals with the acquisition, analysis, and interpretation of information about glycans, data set interoperability was realized by structuring data sets and using a SPARQL database (Egorova and Toukach, 2018). A similar benefit of databases was described in Moser et al (2023). By linking structured data in the field of medical technology, relevant information can be exchanged between different actors in a secure and timely way, thus avoiding delays in medical treatment.…”

Section: Technical Background Of Data Managementmentioning

confidence: 99%

Information reuse of nondestructive evaluation (NDE) data sets

Leinenbach,

Stumm,

Krieg

et al. 2024

J. Sens. Sens. Syst.

View full text Add to dashboard Cite

Abstract. To achieve added value from data spaces and data sets in general, an essential condition is to ensure the high quality of the stored information and its continuous availability. Nondestructive evaluation (NDE) processes represent an information source with potential for reuse. These provide essential information for the evaluation and characterization of materials and components. This information, along with others such as process parameters, is a valuable resource for data-driven added value, e.g., for process optimization or as training data for artificial intelligence (AI) applications. However, this use requires the continuous availability of NDE data sets as well as their structuring and readability. This paper describes the steps necessary to realize an NDE data cycle from the generation of information to the reuse of data.

show abstract