Attribut:Beschreibung-EN
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Dies ist ein Attribut des Datentyps Text.
L
the possibilities for patients to take an active role in their health care through the use of information services (patient empowerment) (e.g. e-health literacy, use of apps, internet portals, personal health records, sensor-based information systems, telemedicine/care). +
The principles of appropriate documentation and health data management (incl. the ability to set up medical coding systems). +
Classifications, terminologies and ontologies in the context of healthcare +
Nomenclatures, (controlled) vocabularies, terminologies, ontologies and taxonomies/classifications in BMHI, e.g. SNOMED CT, LOINC and for care e.g. ICNP, NANDA and NIC and NOC, LEP +
The importance of conceptual definitions for medicine in general +
Medical classifications and terminologies, their structure and field of application +
Diagnoses using the current version of the ICD-GM (International Statistical Classification of Diseases and Related Health Problems, xxRevision German Modification) for inpatient and outpatient treatment. +
Coding of steps, interventions and procedures using OPS +
The principles of the DRG-system, the information and tools required to assign a DRG, and the key figures relevant for the DRG-system, including payment system and additional revenues. +
Biomedical and medical theoretical knowledge +
Examples of the fundamentals of human functioning and life sciences (e.g. from anatomy, physiology, microbiology, genomics and clinical disciplines such as internal medicine, surgery, etc.). +
Basics of public health and health (WHO) and their evaluation exemplarily +
Basics of the nursing process, medical/nursing decision-making and diagnostic and therapeutic strategies on the example of use cases / selected clinical pictures +
The main features of the structure and organisation of health care facilities and the health care system (also in international comparison), intersectoral care and shared care +
Gene and protein databases and the corresponding search methods +
Target-oriented queries in gene and protein databases +
Simple scripts for data analyses of gene and protein data (e.g. in R, Python, Matlab) +
Data analyses of gene and protein data with the appropriate statistical measures +
The different types of data in gene and protein databases and their importance for knowledge generation +
Algorithms for searching and mapping gene and protein sequences +