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Data warehousing and Data mining – an overview Dr. Suman Bhusan Bhattacharyya MBBS, ADHA, MBA Local Today we have… Electronic Medical Record Capturing Clinical Data RDBMS Alerts & Warnings • • • • • RDBMS RDBMS In house Regional Displaying data Displaying rule-based patient-specific alerts Displaying pre-set warnings Following clinical protocols Online Transactional Processing (OLTP) 2 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 3 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 4 Doing it right… Operational EMR Databases Extract Transform Load Validate [ETLV] External EMR Sources Data marts Data warehouse Metadata Repository Monitoring Administration Output 5 OLAP Server OLAP Server Output Query/Report Analysis Data mining 6 The way to go… Knowledge Data mining Evaluation & Presentation Selection & Transformation Cleaning & Integration Databases Flat Files 7 Type of Commercial packages • • • • • • • Informatica Cognos Business Objects SPSS SAS tools Epi Info with Epi Report Custom-built 8 Thank Q 9