Intelligent CIO APAC Issue 25 - Page 59

CASE STUDY
This translates into significant productivity gains , cost savings and optimized bed resources across the hospital cluster .
One of the hospital ’ s new tools reads emergency physicians ’ notes and makes predictions of diagnoses . For example , using the platform ’ s predictions , physicians can understand whether or not a patient is likely to have appendicitis . These are not the only tools at the hospital ’ s disposal .
Dr . Ngiam said : “ Our 30-day readmission prediction is based on a neural network that helps us determine the risk or readmission within 30 days of discharge from an acute hospital .”
About National University Health System ( NUHS )
As a leading academic health system in Singapore , the National University Health System ( NUHS ) offers full-spectrum community and acute care to the western part of the country . Each year , the health system attends to more than one million patients across three acute hospitals , two community hospitals , three national specialty centers , seven primary care clinics and four academic institutions .
Looking to the future , NUHS is interested in adopting TIBCO ModelOps capabilities in the next transformation phase as well as expanding its predictive analytics capabilities to have real-time sensing of resource availability .
“ Our state-of-the-art ENDEAVOUR AI platform drives smarter , better and more effective healthcare in Singapore ,” said Dr . Ngiam . “ Using TIBCO , we hotdeploy , manage and govern various models .
AI-informed processes in a more scalable , containerized way .”
With these TIBCO capabilities , NUHS intends to develop and deploy cutting-edge healthcare AI and automation , including enhanced clinical workflow automation , operational optimization , value-driven outcomes , precision medicine , AI driven image workflows and integration with EMR systems .
“ We are also very excited to be an early trialist of TIBCO ModelOps software . We expect it will accelerate the deployment of safe and effective
Dr . Ngiam concludes : “ We look forward to broader collaboration with TIBCO , and to use AI tools to better meet the healthcare challenges of the future .” p
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