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Personalized Patient Treatments

Problem:

 

Healthcare providers have difficulties determining the correct and best treatment for their patients.

Increasing need for the entire value chain to become networked, efficient and focused on improving the quality of treatments.

Strengthen position in budget negotiations with health insurers

 

 

 

Solution:

 

Health care providers can make the most up to date patient data available to medical doctors and researchers (e.g. using iPad application or mobile device) so that they can access all the data across multiple sources anytime while they’re visiting patients anywhere in or outside the hospital.

 

For example one of Europe's biggest hospital Charite (Germany) is able to collect, filter and control their data much faster with  SAP HANA and SAP Electronic Medical Record (SAP EMR) for patient care, teaching and driving research. As Martin Peuker, Vice CIO at Charité University Hospital Berlin explains “Today we analyze terabytes of data in a matter of seconds. This is of great advantage to both the executive management as well as to doctors and patients”.


Another example is the "HANA Oncolyzer": Researchers and clinicians can access data from relevant patients and analyze them at the patient's bed. In the interdisciplinary research cooperation, researchers from the Hasso Plattner Institute, Charité, and SAP formed a solution for mobile devices, which combines real-time analysis and intuitive user interface. Thus, time-consuming manual searches in distributed database systems are no longer needed. SAP HANA combines search in structured and unstructured data instantly to support daily work of physicians.

 

Benefit:

 

  • Rapid prescription of treatment in conjunction with partner institutions thus eliminating redundant treatment

  • Gather insights from patients to cost-effectively improve quality care and in turn ensure that treatments can be personalized 

  • Improve productivity of health service staff

  • Shorten waiting time for patients
  • Combined search in structured and unstructured data
  • Real-time analysis of patient data

 

Resources:

 

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