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Data Warehousing for Telehealth/Telemedicine
2001 Symposium on Applications & the Internet(Saint 2001)
San Diego, CA
January 10, 2001
Rose Cintron-Allen, MHP
Warren Sterling, PhD
Agenda
• Data Warehouse Definition• Building a Warehouse• Warehouse Uses in Telehealth/Telemedicine• National Medical Knowledge Bank (NMKB) Project• NMKB Features• Virtual Healthcare Events• Intelligent Agent-Based Active Learning Framework• Case Finder• Evidence Finder• Summary & Conclusions
What is a Data Warehouse?
Data Warehousing is a process, not a product
Source: NCR Corporation (and Teradata Corp.) Copyrights 1982-1996. All rights reserved.
It is a process for properly assembling and managing data from various
sources for the purpose of answering business questions and making
decisions that were not previously possible.
Building a Warehouse
Define Business Opportunity & ROI
Sourcing the Data
Planning and Design
Physical Implementation
Operation & Maintenance
LeverageLessons Learned &ROI Evaluation
Telehealth/Telemedicine Uses
Distance Healthcare Education
Teleradiology
Telepathology
Healthcare Informatics
Patient Medical Record
National Medical Knowledge Bank
An Advanced Technology Program Joint Venture An Advanced Technology Program Joint Venture
Allegheny-Singer Research Institute, Pittsburgh PAMillennium Healthcare Solutions, Edison NJ
NCR Corporation, Dayton OHMCP Hahnemann University, Philadelphia PAAT&T Government Markets, McLeansville NC
Sponsored by:The United States Department of CommerceNational Institute of Standards and Technology
What is It?
The National Medical Knowledge Bank is an advanced repository of specialized medical experience and knowledge, featuring easy capture of information, with massive storage and links to a vast selection of supporting resources enabling users to retrieve, collaborate, and learn, anytime and place.
NMKB Consortium Focus
Medical Videos
• Digital Content Acquisition
• Validation• Data Integrity Medical Sounds
Health Care Delivery
Initial & Continuing
Medical Education
Patient Education
Medical Texts
Medical Images
Virtual Medical Environments
ParallelObject/RelationalDatabase (TOR)
Multimedia-based medical information services three key markets.
National Medical Knowledge Bank Features
• Web-based Architecture• Targeted to healthcare practitioners• Integrated applications
– Virtual Medical Conferences– Nursing Training– Case-Based Retrieval for Diagnosis/Treatment
Determination– Disease Domain-specific Literature Search
• Offers Continuing Education credits• Designed to use an object relational database as
a scalable, parallel data warehouse
What is an Object Relational Database?
Patient Patient Account MRI Doctor Angio- Work TranscribedName Age Balance Scans Comm. gram Location Dr. Comm
Object Relational Table
Alphanumeric Attributes “Object” Columns (SDTs)
Char (n) Integer Float Image Audio Video Point Text
Account Account Balance Face Voice ATM Home Transcript Name ID Print Print tnx Location Last Call
Alphanumeric System/User Defined Functions (SDFs/UDFs)System Defined Types (SDTs)
• Integer• Character• Date• Float
• Audio• Image • Video• Geospatial• Document/Text
• Audio/Video matching; Voice Recognition• Iris Scan; Tumor Classification• Playback/Fast-forward; Retrieval• Map-overlay; Distance computations• Word-Recognition/Translation
New Data Traditional Data+
Virtual Healthcare Events:
Virtual Conferences Grand Rounds
• Asynchronous, discretionary viewing
• Lower cost option (travel, time)
• Concept searching
• CME credit, including JE/JIT
• Indexed presentation outlines for fast navigation
• Streaming video/audio with synchronized slides
Brain Attack Conference - Video with Slide Indexing
Primary Care Grand Rounds - Contents and Presentation
Intelligent Agent-based Active Learning Framework
• Delivers personalized, active education experience
• Problem-based learning
• At convenience of student schedule; can complete in multiple sessions
• Certified CNE credit
• Reusable framework; lowers production cost
• Agent technology - lesson planning; student model; tutor; ontology
• Applicable to other domains
Intelligent Agent-based Continuing Education - Activity Menu
• Patient interview video vignettes (streaming video)
• Student selects questions and orders them
• Student evaluated on question choice and order
• Patient interview video vignettes (streaming video)
• Student selects questions and orders them
• Student evaluated on question choice and order
Intelligent Agent-based Continuing Education - HPI Video Interview
Intelligent Agent-based Continuing Education – Review Patient Chart
Case Finder (Case-based Reasoning)
• Uses Case-Based Reasoning to Find “Similar” Cases
• Eases clinician’s burden of reading and recalling cases
• Saves clinician time• Web-based; works
with any ODBC database
• Matches complex data
Case Finder - Retrieval of Similar Cases
Medical Ontology
Case Finder uses the Unified Medical Language System (UMLS) with >700K concepts and 1.5M concept names– allows matching at the concept level
• cva = stroke = brain attack
– identifies relationships between concepts• embolic stroke is a kind of stroke
Evidence Finder
Evidence Finder: Query
Submit Query
Clear
Enter words or phrases, separated by commas:
glucophage
Study Study MethodMethodRandomizedTrial
Population StudyGuidelines
Review Article
Meta-Analysis
Cost BenefitAnalysisCost-Effectiveness
Key DisordersKey Disorders
Diabetes
Lipid Disorders
Stroke
Asthma
Osteoporosis
A I D S
Pneumonia
Heart Failure
Hypertension
Preop Consults
Epidemiology
Prevention
Diagnosis
Screening
Treatment
Non-pharm Rx
Outcomes
SubtopicSubtopic
Case Study
• “Essence of the essence” of recent published literature: abstracts and “pearls”
• Evidence-based; categorized by evidence quality
• Reduces need for colleague consultation
• Accessible, intuitive, relevant
• “Think with me” functionality
Evidence Finder: Results
You matched 6 out of 121 documents
Presented by James Gavin, M.D. at MCP Hahnemann University on 3/3/99 [0 CME credits]
In obese patients with poorly controlled type 2 diabetes on diet alone, use of metformin titrated to maximal dosage or fasting plasma glucose of <140 mg/dl resulted in significantly improved average glycemic control,
compared to placebo. …
1 Efficacy of metformin in patients with non-insulin-dependent diabetes mellitus.The Multicenter MetforminStudy Group
6 Minority Issues in the Management of DiabetesMellitus - Recommendations
Evidence Finder: Results
EVIDENCE BASED MEDICINE INDEXED DOCUMENT EVIDENCE BASED MEDICINE INDEXED DOCUMENT RETRIEVALRETRIEVAL
Treatment Pharmacologic (Randomized Control-Certified)
PearlIn obese patients with poorly controlled type 2 diabetes on diet alone, use of
<metformin> titrated to maximal dosage or fasting plasma glucose of <140 mg/dl resulted in significantly improved average glycemic control, compared to placebo (hemoglobin A1C 7.1% vs. 8.6%, respectively). In a second study, obese patients with poorly controlled type 2 diabetes despite maximal glyburide therapy had improved glycemic control on glyburide plus <metformin> (titrated as above) compared to those remaining on glyburide alone (hemoglobin A1C 7.1% vs. 8.7%, respectively). Patients changed from maximal glyburide to titrated dose <metformin> had minimal improvement in average glycemic control.
AbstractBACKGROUND: Sulfonylurea drugs have been the only oral therapy available for patients with non-insulin-dependent diabetes mellitus (NIDDM) in the United States. Recently, however, <metformin> has been approved for the treatment of NIDDM. …
Evidence Finder: Results
MULTIMEDIA DOCUMENT RETRIEVAL, WITH CME CREDIT, INDEXED BY PRESENTATION SEGMENT
What the Warehouse Holds
• NMKB Content Index for all current and potential content for all applications - based on Dublin Core
• Evidence-based medicine abstracts and “pearls”• All exemplar cases for CaseFinder application• Digital video and slides/images for all virtual events• All content for Active Learning Framework training modules• Unified Medical Language System ontology• Student history• User data• Potential content for the NMKB
Summary and Conclusions
• The NMKB project sponsored by NIST ATP was successfully completed
• The NMKB will support innovative interactive multimedia-enabled medical applications.
• Goal is to commercialize the NMKB or pieces of it. • The data warehouse of a commercial NMKB must be
supported by object relational database technology• Scalable growth is required as content base grows.• Parallel database operation is required for sophisticated CBR
searching and concurrent access by large numbers of users.
