Excessive length of Stay Healthcare IEP Demonstration (Combinned_Intelligent_Event_Processor_Demonstration_v1.0.pdf)
Preview
As a healthcare enterprise looks after patients, information is gathered about various events that take place. A stream of HL7 messages broadcast by enterprise systems can be intercepted and processed to derive all sorts of interesting information.
The solution developed in this walkthrough deals with Excessive Length of Stay. Statistical average expected length of stay is typically available for different kinds of conditions. A significant variation from the average length of stay may indicate complications, treatment errors, infections and other kinds of issues that the hospital needs to investigate.
The Intelligent Event Processor is used to calculate the continuously updated average length of stay over a period of time and use it to compare against each event’s length of stay. It passes, to the downstream component, all events where the length of stay exceeds the average by 1 ½ times and ignores all others.
The solution developed in this walkthrough deals with Excessive Length of Stay. Statistical average expected length of stay is typically available for different kinds of conditions. A significant variation from the average length of stay may indicate complications, treatment errors, infections and other kinds of issues that the hospital needs to investigate.
The Intelligent Event Processor is used to calculate the continuously updated average length of stay over a period of time and use it to compare against each event’s length of stay. It passes, to the downstream component, all events where the length of stay exceeds the average by 1 ½ times and ignores all others.
About This Media
| Contributor: | Michael.Czapski-Sun |
| Size: | 2.5 MB |
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| Content type: | application/pdf |
| Uploaded at: | 2009-09-16 22:57 |
| Last update at: | 2009-09-16 23:03 |
