Keywords:
eHealth, Artificial Intelligence, Management, MR, CT, CAD, Cost-effectiveness, Audit and standards, Outcomes analysis, Economics, Outcomes, Education and training
Authors:
B. May; Mainz/DE
DOI:
10.26044/ecr2019/C-2083
Methods and materials
Methods and materials
Data basis
This study is based upon the analysis of RIS-data of 45 clinical imaging departments (between 2001 and 2018),
15% of which are teaching hospitals,
25% tertiary,
51% secondary and 9% primary hospitals.
Each analysis was aiming at identifying potentials for the improvement of for instance utilization of resources (staff,
modalities,
consumables),
structures,
process-management,
productivity,
technology,
order management by clinical departments,
radiological pathway management,
cost-revenue balance and outcome.
This study is focusing on the order management of clinical departments requesting radiological exams from the corresponding imaging department.
Additionally were used results from Daniel Kahneman`s “Thinking,
fast and slow”,
paperback May 10,
2012 (nobelprice for economy 2002).
Data analysis
All RIS-data have been analyzed and processed by means of MS tools to identify the spectrums of organs examined per patient and modality in the imaging department per residential treatment.