1. Data warehousing and Data mining – an overview Dr. Suman Bhusan Bhattacharyya MBBS, ADHA, MBA

2. 2 Today we have… Electronic Medical Record Capturing Clinical Data RDBMS Alerts & Warnings Displaying data Displaying rule-based patient-specific alerts Displaying pre-set warnings Following clinical protocols Online Transactional Processing (OLTP) In house Regional Local

3. 3 Requirements of tomorrow Use clinical data to –Support Evidence based medicine –Perform Outcomes Analysis Confirm existing clinical “facts” Refine clinical guidelines/protocols Find hidden knowledge patterns

4. 4 Necessity of these requirements Evaluation of stored data may lead to discovery of trends and patterns that would enhance the understanding of disease progression and management Insurance companies of the future will clinically assess a person for the most likely risks for a specified period and then calculate the premium for health insurance

5. 5 Doing it right… Output Extract Transform Load Validate [ETLV] Operational EMR Databases External EMR Sources Metadata Repository OLAP Server MonitoringAdministration Data warehouse Data marts

6. 6 Output Data mining Analysis Query/Report

7. 7 The way to go… Selection & Transformation Data mining Knowledge Flat Files Cleaning & Integration Evaluation & Presentation Databases

8. 8 Type of Commercial packages Informatica Cognos Business Objects SPSS SAS tools Epi Info with Epi Report Custom-built

9. 9 Thank Q