Internet Health Monitors: Distributed Infrastructure for Measuring Population Health

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Internet Health MonitorsDistributed
Infrastructure for Measuring Population Health
Bruce R. SchatzDepartment of Medical Information
ScienceCollege of Medicine, Institute for
Genomic Biology University of Illinois at
Urbana-Champaign schatz_at_uiuc.edu ,
www.canis.uiuc.edu
Biomedical Informatics Campus Seminar University
of Illinois at Urbana-Champaign October 7, 2005
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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!

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Health Systems

• Healthcare is THE Economic Issue
• BIGGEST item in modern societies
• Fast growing due to aging population
• Healthcare will BREAK Every Nation
• Nations go bankrupt and People die!

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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

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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

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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.

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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!

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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

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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

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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

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Measure Population Health 2

• Electronic Records for fine prediction
• Paper supports 10s of questions
• Electronic supports 100s or 1000s
• 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

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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

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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

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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

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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

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Current Prototype Status

• Theory Experiment
• Completed in LIS Healthcare Infrastructure
• Health Informatics Information Retrieval
• Practice Experiment
• On-going collaboration with Carle Hospital
• Adaptive Faceted being Developed
• Historical Databases being Analyzed
• Clinical Experiment
• Multi-Year Trial Proposal to US AHRQ
  Agency for Healthcare Research Quality

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Sample General Health Questions
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Sample Specific Health Questions

• Heart Condition

• Arthritis Condition

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Health Monitor Session
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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

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Computer-based Questionnaires

• Treat actual disease stage (dynamic)
• Computer assessment handles full-spectrum
• Database of all questions (300K)
• 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

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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

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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

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Healthcare Infrastructure

• Provider Pyramids
• Scale to Volumes for Chronic Illness
• Risk Assessment
• Automatically Determine Level of Care

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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.

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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).