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Development of an Ontology-driven Medical Assistance System

Delivery of health care services is frequently compromised by information gaps posing substantial risk to patients as well as health care professionals: 72% of patient records contain wrong or inaccurate clinical information. In 16% of patient records, underreporting of clinical information impedes any appraisal of the care process at all (Püschmann 2006).

Predominantly, these deficiencies are caused by natural limitations of human performance, tense working conditions and insufficient production management in health care, all together resulting in inadequate capture and storage of clinical data. Information shortfalls especially concern past and present medical history, signs and symptoms, findings from physical exams and technical analyses, clinical assessment and decisions as well as diagnostic and therapeutic interventions and their effects. 

Consequently, patients and health care professionals are at permanent risk of suffering damage from

  • missed or delayed diagnoses,
  • inadequate or delayed delivery of causal treatment,
  • adverse events in the treatment course,
  • increase of treatment costs, e.g. due to prolonged hospital stay,
  • extended scope of liability by reversed burden of proof in medical malpractice litigation.

In order to cope with these problems, the Dusseldorf based company Medical Scapes operates in health care process organization and clinical information management. It systematically develops clinical assistance systems that guide and support health care professionals in collecting, securing and implementing clinical information during the care process. As a sound basis for its clinical assistance systems, Medical Scapes has established a modular clinical information model that contributes to reorganization of clinical processes, improved process stability and increased efficiency of basic medical activities.

Within the framework of this master thesis, it will be required 

  • to transform the existing information structure of Medical Scapes’ clinical information model  into an ontology and potentially enrich it with a medical ontology e.g. SNOMED (Systematized Nomenclature of Medicine).
  • to develop a run-time-based model-driven approach (such as known in software engineering) that allows for turning ontology terminological knowledge into Web pages suitable for capturing actual patient data. 
  • to use a RDF Triple Store for storage and retrieval of patient data.

The master thesis is intended to be written in cooperation with Medical Scapes GmbH & Co. KG, Dusseldorf.
Basic knowledge of the German language is an advantage for this master thesis.

Studienart: 
Master
Ausschreibungsdatum: 
2018