» Articles » PMID: 37079066

[BeoNet-Halle-development of A multifunctional Database for the Automated Extraction of Healthcare Data from General Practitioner and Specialist Practices]

Overview
Authors
Affiliations
Soon will be listed here.
Abstract

The Beobachtungspraxennetzwerk Halle (BeoNet-Halle) is an innovative database of outpatient care that has been collecting patient data from participating primary care and specialty practices throughout Germany since 2020 and making it available for research and care. The database is set up and maintained by the Institute of Medical Epidemiology, Biometrics and Informatics and the Institute of General Practice and Family Medicine of the Martin Luther University Halle-Wittenberg. Furthermore, the Data Integration Center of the University Medical Center Halle is involved in the project. In principle, anonymized and pseudonymized patient data from all commercially available practice management systems should flow into the databases.In this article, we describe the structure and methods of the multi-purpose database BeoNet and quantify the current data stock. The workflow of collection, transfer, and storage of broad consents is described and advantages and limitations of the database are discussed.BeoNet-Halle currently contains anonymized data of approximately 73,043 patients from five physician practices. Furthermore, it includes data from more than 2,653,437 ICD-10 diagnoses, 1,403,726 prescriptions, and 1,894,074 laboratory results. Pseudonymized data were successfully exported from 481 patients.BeoNet-Halle enables an almost seamless representation of the care provided in the participating practices. In the future, the database will map patient treatment pathways across practices and provide high-quality care data to contribute to health policy decision-making and optimization of care processes.

Citing Articles

Bias in obtaining broad consent in a German general practice? - Preliminary results from a cross-sectional study.

Moser K, Bauch F, Richter M, Brutting C, Bauer A, Vinker S J Family Med Prim Care. 2024; 13(9):4056-4065.

PMID: 39464962 PMC: 11504768. DOI: 10.4103/jfmpc.jfmpc_1957_23.


German primary care data collection projects: a scoping review.

Moser K, Massag J, Frese T, Mikolajczyk R, Christoph J, Pushpa J BMJ Open. 2024; 14(2):e074566.

PMID: 38382948 PMC: 10882319. DOI: 10.1136/bmjopen-2023-074566.

References
1.
Watt G . William Pickles lecture. General practice and the epidemiology of health and disease in families. Br J Gen Pract. 2004; 54(509):939-44. PMC: 1326114. View

2.
Bolibar B, Fina Aviles F, Morros R, Garcia-Gil M, Hermosilla E, Ramos R . [SIDIAP database: electronic clinical records in primary care as a source of information for epidemiologic research]. Med Clin (Barc). 2012; 138(14):617-21. DOI: 10.1016/j.medcli.2012.01.020. View

3.
Gentil M, Cuggia M, Fiquet L, Hagenbourger C, Le Berre T, Banatre A . Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature. BMC Med Inform Decis Mak. 2017; 17(1):139. PMC: 5613384. DOI: 10.1186/s12911-017-0538-x. View

4.
Hippisley-Cox J, Stables D, Pringle M . QRESEARCH: a new general practice database for research. Inform Prim Care. 2004; 12(1):49-50. DOI: 10.14236/jhi.v12i1.108. View

5.
Pacurariu A, Plueschke K, McGettigan P, Morales D, Slattery J, Vogl D . Electronic healthcare databases in Europe: descriptive analysis of characteristics and potential for use in medicines regulation. BMJ Open. 2018; 8(9):e023090. PMC: 6129090. DOI: 10.1136/bmjopen-2018-023090. View