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Leeds Teaching Hospitals Study Accident, ER Trends with Big Data

Leeds Teaching Hospitals Study Accident, ER Trends with Big Data

Using big data technologies to analyze doctors’ notes helps to plan resources and spot under billing

Leeds Teaching Hospitals identified an opportunity to be proactive in planning its care by analyzing the data it held on patients. By aggregating and making sense of the unstructured notes written on patients’ records, it was able to identify trends in injuries and conditions that patients present, and spot billing discrepancies that could be leaking funds.

Challenges
• Data capture. Make it easier for clinicians and administrators to capture data at the point of admission and throughout the patient care cycle.
• Data analysis. Use natural language processing to make sense of unstructured care notes, and combine them with structured care data for analysis.

Solutions
• Big data. The data from Symphony software was processed in a data center using software from Two10degrees to analyze its text content and turn unstructured data into structured data.
• Simple queries. The team at Leeds Teaching Hospitals used its existing SQL* skills to analyze the data stored in its data warehouse, powered by the Intel® Xeon® processor E5 family.

Read the full Leeds Teaching Hospitals Study Accident, ER Trends with Big Data Case Study.

Leeds Teaching Hospitals Study Accident, ER Trends with Big Data

Using big data technologies to analyze doctors’ notes helps to plan resources and spot under billing

Leeds Teaching Hospitals identified an opportunity to be proactive in planning its care by analyzing the data it held on patients. By aggregating and making sense of the unstructured notes written on patients’ records, it was able to identify trends in injuries and conditions that patients present, and spot billing discrepancies that could be leaking funds.

Challenges
• Data capture. Make it easier for clinicians and administrators to capture data at the point of admission and throughout the patient care cycle.
• Data analysis. Use natural language processing to make sense of unstructured care notes, and combine them with structured care data for analysis.

Solutions
• Big data. The data from Symphony software was processed in a data center using software from Two10degrees to analyze its text content and turn unstructured data into structured data.
• Simple queries. The team at Leeds Teaching Hospitals used its existing SQL* skills to analyze the data stored in its data warehouse, powered by the Intel® Xeon® processor E5 family.

Read the full Leeds Teaching Hospitals Study Accident, ER Trends with Big Data Case Study.

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