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Health Works Collective > eHealth > The Learning Healthcare System and Order Sets
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The Learning Healthcare System and Order Sets

sharpjw1
sharpjw1
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Learning Healthcare System
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One of the most powerful concepts in changing healthcare is the Learning Healthcare System explained in most detail in this Institute of Medicine report. The concept of using evidence from research to rapidly into practice in a virtuous cycle. But how exactly to operationalize this  concept?

One of the most powerful concepts in changing healthcare is the Learning Healthcare System explained in most detail in this Institute of Medicine report. The concept of using evidence from research to rapidly into practice in a virtuous cycle. But how exactly to operationalize this  concept?

Two recent examples are beginning to move along this path in utilizing data to develop customized order sets. One is IBM Watson working with Memorial Sloan Kettering Cancer Center. Using its powerful natural language processing (NLP), Watson is able to match patient data including complex genomics with the wide array of order sets available for different types of cancer. “ The medical center has about 2,000 order sets it can pull from when choosing a cancer treatment.” And data on millions of patients. Finding patterns that match requires the speed and logic of the Watson engine.

A second example uses existing medical knowledge and updates it as published and then converts these into order sets for a procedure-based EMR system. With their combination of the knowledge of current practices in tools like Up-To-Date and an EMR called Provation, they are now combining these products to enable the regular updating of order sets in the EMR including integration with comprehensive EMRs. This demonstrates the last mile of clinical decision support and evidence-based medicine. Bringing the latest discoveries to EMR order sets through an integrated solutions.

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Looking forward to more solutions that fulfill the vision of the Learning Healthcare System.

Learning Healthcare System

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