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  • 1. Data Mining Applications In Healthcare TEPR 2004 May 21, 2004 V. “Juggy” Jagannathan VP of Research [email_address]
  • 2. Introduction
    • Provide an overview of the technologies that are relevant to the development and deployment of data mining solutions in healthcare
    Goals of today’s presentation: Allow participants to evaluate where the technology is useful
  • 3. What is Data mining? Divining knowledge from data
  • 4. .
    • Data mining
    • Uses
    • Algorithms
    • Technology
    • Applications in healthcare
    Topic Outline
  • 5. .
    • Descriptive
    Data Mining Uses
    • Predictive
      • Classification
      • Regression
      • Time-Series
      • Clustering
      • Summarization
      • Association Rules
      • Sequence Discovery
    Understand and characterize Extrapolate and forecast
  • 6. Data Mining Algorithms
    • Classification
      • Statistical
      • K-nearest neighbors
      • Decision trees
        • ID3
        • C4.5
      • Neural Networks (Self Organizing Maps)
    • Clustering
      • Hierarchical
      • Partitioned
      • Genetic
    • Association
      • Apriori Algorithm
      • If….Then rules
  • 7. Technology
    • Database Technologies
    • On-Line Analytical Processing (OLAP)
    • Visualization Technologies
    • Data scrubbing technologies
    • Natural Language Processing (NLP)
    Technology solutions Data Mining Infrastructure Technologies
  • 8. Database Technologies
    • Data warehouse vs. Data mart
    • Relational technologies
      • Oracle
      • Microsoft
    • XML-databases
      • Raining Data
    • Database
    • OLAP
    • Visualization
    • Scrubbing
    • NLP
  • 9. On-Line Analytical Processing
    • Analyze multi-dimensional data
    • N-dimensional data cubes
    • Operations
      • Roll-up
      • Drill-down
      • Slice and dice
      • Pivot
    • Database
    • OLAP
    • Visualization
    • Scrubbing
    • NLP
  • 10. Visualization
    • 2D/3D Charts
    • Topographic displays
    • Cluster displays
    • Histograms
    • Scatter plots
    • Advanced visualization (genomic data patterns)
    • http://www.ncbi.nlm.nih.gov/Tools/
    • Database
    • OLAP
    • Visualization
    • Scrubbing
    • NLP
  • 11.
    • Data cleansing
    • Filling in missing data
    • In healthcare, there is a strong need for de-identification to protect privacy
    • Database
    • OLAP
    • Visualization
    • Scrubbing
    • NLP
  • 12. De-Identification of Medical Records *
    • Names;
    • all elements of a street address, city, county, precinct, zip code, & their equivalent
    • geocodes, except for the initial three digits of a zip code for areas that contain over 20,000 people;
    • all elements of dates (except year) for dates directly related to the individual, (e.g., birth date, admission/discharge dates, date of death); and all ages over 89
    • and all elements of dates (including year) indicative of such age, except that such ages and elements may be aggregated into a single category of age 90 or older;
    • telephone numbers;
    • fax numbers;
    • e-mail addresses;
    • social security numbers;
    • medical record numbers;
    • health plan beneficiary numbers;
    • account numbers;
    • certificate/license numbers;
    • license plate numbers, vehicle identifiers and serial numbers;
    • device identifiers and serial numbers;
    • URL addresses;
    • Internet Protocol (IP) address numbers;
    • biometric identifiers, including finger and voice prints;
    • full face photographic images and comparable images;
    • any other unique identifying number except as created by IHS to re-identify information.
    * Source : Policy and Procedures for De-Identification of Protected Health Information and Subsequent Re-Identification 45 CFR 164.514(a)-(c) posted by IHS (Indian Health Services)
  • 13. Natural Language Processing
    • NLP Uses
      • translation, summarization, information extraction, document retrieval or categorization
    • NLP Approaches
      • Clustering, Classification, Linguistic analysis, knowledge-based analysis
    • NLP Companies in health care
      • A-Life
      • Language and Computing
    • Database
    • OLAP
    • Visualization
    • Scrubbing
    • NLP
  • 14. Applications in Healthcare
    • Safety and quality
    • Clinical Research
    • Financial
    • Public Health
  • 15. “To err is Human” IOM Report
    • Characterization
      • JCAHO Core Measures
      • CMS Quality measures starter set
      • Improves patient care – reactive response
    • Prediction
      • Identifying cases that can result in bad clinical outcomes and raising appropriate alarms
      • Impacts patient care – proactive response
    • Safety and Quality
    • Clinical Research
    • Financial
    • Public Health
  • 16. Quality Measures – Initial Set* *Source: http://www.cms.hhs.gov/quality/hospital/overview.pdf Oxygenation assessment Pneumococcal vaccination Pneumonia Initial antibiotic timing ACE inhibitor for left ventricular systolic dysfunction Heart Failure Left ventricular function assessment ACE Inhibitor for left ventricular systolic dysfunction Beta-Blocker at discharge Beta-Blocker at arrival Aspirin at discharge Acute Myocardial Infarction (AMI)/Heart attack Aspirin at arrival Condition Measure Starter Set of 10 Hospital Quality Measures
  • 17. Safety and Quality
    • University of Mississippi Medical Center
      • Data Warehouse Technologies to understand Medication Errors – Funded by AHRQ
      • Anonymous report data collection
      • Data mining technologies
      • Use of Neural networks and associative rule inference
  • 18. Clinical Research & Clinical Trials
    • Pharmacy and medical claims data
    • Drug efficacy and clinical trials – for example how effective is a particular drug regimen
    • Protein structure analysis
    • Genomic data mining
    • Diagnostic Imaging data research
    • Safety and Quality
    • Clinical Research
    • Financial
    • Public Health
  • 19. The bottom line on cost
    • General Utilization review – does the care provided meet accepted clinical and cost guidelines
    • Drug Utilization review
    • Outlier analysis – exceptions to treatment – analyzing treatments which cost more than the normal or less than normal.
    • Safety and Quality
    • Clinical Research
    • Financial
    • Public Health
  • 20. Data mining in public health
    • Syndromatic surveillance
    • Bio-terrorism detection
    • Communicable disease reporting (Centers for Disease Control (CDC))
    • DAWN (Drug Awareness and Warning Network)
    • Federal Drug Agency (FDA) – reporting of adverse drug events.
    • Safety and Quality
    • Clinical Research
    • Financial
    • Public Health
    Example effort: AEGIS
  • 21. Conclusion
    • Data mining
    • Uses
    • Algorithms
    • Technology
    • Applications in healthcare
    • Descriptive
    • Predictive
    • Classification
    • Clustering
    • Association rules
    • Database
    • OLAP
    • Visualization
    • Scrubbing
    • NLP
    • Safety and Quality
    • Clinical Research
    • Financial
    • Public Health
  • 22. Conclusion
    • uestions?
    Technology solutions [email_address]