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Viable Health Systems from Distributed Computing Systems

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... B. Schatz, PhD, at www.canis.uiuc.edu under Publications under ... prototypes and view analysis at www.canis.uiuc.edu under MedSpace at bottom of web page. ... – PowerPoint PPT presentation

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Title: Viable Health Systems from Distributed Computing Systems


1
Viable Health Systems fromDistributed Computing
Systems
Bruce R. SchatzDepartment of Medical Information
ScienceCollege of Medicine, Institute for
Genomic Biology University of Illinois at
Urbana-Champaign schatz_at_uiuc.edu ,
www.med.uiuc.edu/MedInfoSci
6th Symposium Understanding Complex
Systems University of Illinois at
Urbana-Champaign May 15, 2006
2
Health Systems
  • Healthcare is THE Societal Issue
  • BIGGEST item in modern economies
  • Fast growing due to aging population
  • Healthcare will BREAK Every Nation
  • Nations go bankrupt and People die!

3
Complex Systems
  • Organizational Problem
  • Top-down Central Medicine
  • Diagnose Diseases and Treatment Cures
  • Technological Solution
  • Bottom-up Distributed Health
  • Measure Features and Cluster Persons

4
The Fundamental Cause 1
  • Medicine versus Health
  • Cure Sick in BIG Hospital
  • Maintain Wellness in small Clinic
  • Recent Rise of Chronic Illness
  • No cure with drugs surgery
  • only manage with diet exercise

5
The Fundamental Cause 2
  • Health Systems now for Acute Illness
  • Hospitals are Profitable Business but
  • Clinics are supported by Government
  • Systems cannot handle Chronic Illness
  • Chronic Illness now dominates Costs and Systems
    cannot handle Volume

6
Viable Health Systems
  • Emergent Properties of
  • Population Health
  • No Diagnosis and No Treatment but
  • Similar People and Similar Progress
  • Viable Health System is
  • Adaptive Complex System

7
The Viable Solution 1
  • Independent Clinics are Doomed
  • 1990s America -- small Clinics failed
  • when Government support reduced.
  • Health Systems start HMOs
  • Health Maintenance Organizations
  • 2000s America HMOs all failing.
  • 2000s Japan small Clinics will fail
  • when Government support reduced.

8
The Viable Solution 2
  • Need Complete Provider Pyramids
  • High Level for High Quality at High Cost
  • Low Level for Low Quality at Low Cost
  • Handle Volume by Pushing Cases Down
  • Bottom Levels handle MOST CASES
  • Viable Healthcare Infrastructure
  • Hospitals with Doctors for Surgery, Clinics with
    Nurse for Drugs, Homes with Patients for nearly
    all Health Interactions!

9
Healthcare Infrastructure
  • Infrastructure is the Whole System
  • Hospital, Clinic, Home
  • Doctors, Nurses, Brochures, Internet
  • NO Viable Model for Health System
  • Too much Cost! Too Much Volume!

10
Health Informatics
  • Need New Viable Infrastructure
  • Health Information Technology
  • Provides Support for Patients in Homes
  • Creates Bottom of Pyramid to Offload
  • Informatics can Solve this Problem
  • Patients themselves create population health
    database via informatics that automatically
    routes healthcare

11
Connecting for Health (UK)
  • National Health Service
  • https//www.healthspace.nhs.uk/index.asp
  • HealthSpace is a secure place on the internet
    where you can store all your personal health
    information. Please use the links below to find
    out more.
  • Personal details
  • Health details Track your health online. Keep a
    record of all your medications.
  • Library

12
Informatics Technologies
  • Measure Population Health
  • Adaptive Question Asking of Quality of Life
    Questionnaires
  • Answers for Individuals creates Database for the
    Population
  • Manage Population Health
  • Structured Health Vectors from normalized patient
    records
  • Statistical Information Retrieval cluster
    patients into care cohorts

13
Measure Population Health 1
  • Quality of Life Questionnaires
  • Self-Assessment directly by Patients
  • General Status questions, e.g. SF-36
  • Specific Disease questions, e.g.
  • Arthritis Can you walk without pain?
  • Heart Disease Do your ankles swell?
  • QoL correctly does coarse prediction
  • VA Heart Study SF-12 better than surgeon about
    patient survival

14
Measure Population Health 2
  • Electronic Records for fine prediction
  • Paper supports 10s of questions
  • Electronic supports 1000s of questions
  • Adaptive Question Asking
  • Choose questions by weighted treewalk
  • Each session asks 10s of questions customized to
    particular condition
  • Generate Population Database
  • Daily individual records from all homes

15
Manage Population Health
  • Structured Health Vectors
  • Patient answers Questions daily
  • Average scores generate Health Vector
  • Elements of Vector are Meaningful
  • Cluster Patient Cohorts
  • Normalize Vectors for Similar Clusters
  • Weight Question Groups Medically
  • Route Care into Pyramid using Clusters to
    Determine Cohorts

16
Theory Experiment
  • Questionnaire from Merged QoL
  • 120 questions from 20 questionnaires
  • General plus some Specific questions
  • Simple Clusters do coarse prediction
  • Students simulate sick or well patients
  • K-means with random seeds does correct clustering
    from actual health monitor sessions with 100
    answers

17
Practice Experiment
  • Practical Risk Assessment Possible?
  • Need 4 Cohort Clusters correctly predicted
    hospital, clinic, telephone, home
  • Is 120 questions (10more) enough?
  • What Clusters can do fine prediction?
  • Use Historical Database of Real Patients
    answering Paper QoL Questionnaires
  • Agglomerative with complete link always
    consistent but always correct? May need
    appropriate structured vector weighting

18
Clinical Experiment
  • Real Patients in Real Settings
  • 1000 senior patients with heart disease
  • Use in Medicare Coordinated Care
  • Telephone Interface via voice response
  • Determine Care Levels automatically
  • Demonstrate Feasible Technologies
  • Adaptive Question Asking with Faceted Category
    Classification
  • Statistical Cohort Clustering with Structured
    Vector Weighting

19
Current Prototype Status
  • Theory Experiment
  • Completed in LIS Healthcare Infrastructure
  • Practice Experiment
  • On-going collaboration with Carle Hospital
  • Clinical Experiment
  • Health Systems Research Center hosts
  • AHRQ proposals for Heart Failure trial
  • Smaller trial for Breast Cancer to leverage Mills
    Breast Cancer Institute
  • Seed monies from Carle and from NCSA

20
Sample General Health Questions
21
Sample Specific Health Questions
  • Heart Condition

  • Arthritis Condition

22
Health Monitor Session
23
Beyond Screening
  • Why are Some People Healthy? (R. Evans)
  • Major categories are disease, health care,
    health function, genetic endowment, physical
    environment, social environment, individual
    response, behavior, well-being, prosperity.
  • Healthy People 2010
  • 467 objectives in 28 focus areas
  • www.health.gov/healthypeople
  • Measure Full-Spectrum Health Status
  • Detailed QoL in each detailed category

24
Computer-based Questionnaires
  • Treat actual disease stage (dynamic)
  • Computer assessment handles full-spectrum
  • Database of all questions (30K)
  • Individual session asks only 30 questions
  • Tree-walking Categories by Breadth-First
  • Treat actual patient status (adaptive)
  • MOS knows this the problem (McHorney)
  • GRE as the paradigm
  • Session answers determine questions
  • Historical answers determine questions

25
Population Management
  • Possible to Monitor Whole Populations
  • Daily Monitors, Full Spectrum of Features
  • Internet Software handles Questionnaires
  • Cohort Clusters supplement Diagnoses
  • Daily Feature Record for each Individual
  • Detailed Databases for whole Population
  • Analyze Clusters of Similar Patients
  • Cohort Switching drive Treatments
  • Manage Expectations with Actual Cases
  • Improve Health by Switching Cohorts

26
Getting from Here to There
  • Develop Full-spectrum Questionnaire
  • Merge existing Quality of Life instruments
  • Encode knowledge from Medical Professionals
  • Develop Dynamic Adaptive Administration
  • Software to handle Interactive Sessions
  • Software to build Individual History
  • Software to build Population Database
  • Develop Cohort Similarity Clustering
  • Algorithms for Statistical Feature Matching
  • Lifestyle Coaching via Cohort Switching
  • Deploy Test (10) to Trial (1000) Population

27
Health Systems via Computer Systems
  • Provider Pyramids
  • Scale to Volumes for Chronic Illness
  • Risk Assessment
  • Automatically Determine Level of Care

28
Further Information
  • Papers
  • See articles on Internet Health Monitors and on
    Monitoring Population Health by R. Berlin, MD,
    and B. Schatz, PhD, at www.canis.uiuc.edu under
    Publications under Papers.
  • Demos
  • Try prototypes and view analysis at
    www.canis.uiuc.edu under MedSpace at bottom of
    web page.

29
Further Reading
  • Richard Berlin and Bruce Schatz (2001)
  • Population Monitoring of Quality of Life for
    Congestive Heart Failure, Congestive Heart
    Failure, 7(1)13-21 (Jan/Feb 2001).
  • Colleen McHorney (1997)
  • Generic Health Measurement Past Accomplishments
    and a Measurement Paradigm for the 21st Century,
    Annuals Internal Medicine,127743-750.
  • R. Evans, M. Barer, T. Marmor (eds)
  • Why are some People Healthy and Others Not?
  • The Determinants of Health of Populations
  • (New York Aldine de Gruyter, 1990).
  • G. Rose, The Strategy of Preventive Medicine
  • (Oxford University Press, 1992).
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