1 / 9

Data warehousing and Data mining – an overview

Data warehousing and Data mining – an overview. Dr. Suman Bhusan Bhattacharyya MBBS, ADHA, MBA. Local. Electronic Medical Record. Capturing Clinical Data. RDBMS. Alerts & Warnings. RDBMS. RDBMS. In house. Regional. Displaying data Displaying rule-based patient-specific alerts

winter-zamora
Télécharger la présentation

Data warehousing and Data mining – an overview

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. Local 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) Today we have…

  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. 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. Doing it right… Operational EMR Databases ExtractTransformLoadValidate [ETLV] External EMR Sources Data marts Data warehouse Metadata Repository Monitoring Administration Output OLAP Server OLAP Server

  6. Query/Report Data mining Analysis Output

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

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

  9. Thank Q

More Related