Digital Economy A Global Public Health Frontier

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Digital EconomyA Global Public Health Frontier

• Public Health Informatics 2008, Seattle, 19/9/08
• Iain BuchanProfessor of Public Health
  Informatics
• University of Manchester

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This Talk

• Whose eHealth? Whose Digital Economy?
• Citizen, Patient Population...top-down or
  bottom-up?
• Public eHealth RD in Northwest EnglandOpen
  Health e-Labs programme
• Crossing the Digital DivideAffordable,
  sustainable digital commodities forenterprising
  public health, globally

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What is Digital Economy RD?

• Novel design or use of technologies to help
  transform the lives of individuals, society or
  business.

Physical supply-chain
Virtual supply-chain
Nicholas Negroponte 1995 ...from processing
atoms to processing bits
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Population Health
Individual Health
Technical Innovation
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UK Health Systems Dilemma
world class commissioning
healthy choices opportunity responsibility
Societys Health-Needs
personalised care access
prevention or bust
reducing inequalities
early intervention
Self-care opportunity responsibility
Long-term
Strategy for sustainability
Short-term
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Do we choose health?
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Situational Awareness of Rising
Child-BMIExample Wirral 3-yr-olds from 1988 to
2004
0.5
0.4
0.3
0.2
0.1
Three-monthly rolling average BMI SDS
0
Actions
-0.1
Clues
-0.2
-0.3
-0.4
Mar-88
Jul-89
Nov-90
Apr-92
Aug-93
Jan-95
May-96
Sep-97
Feb-99
Jun-00
Nov-01
Mar-03
Aug-04
Month of measurement by Health Visitor
SDS standard deviation score from 1990 British
Growth Reference charts adjusts for age and sex
of the child
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Child poverty map (households with children
on benefits in 2001-3)
Wirral (0.3M), UK
Fifths of IDAC 2004 Red (light) most
deprived Red (dark) Purple Blue (dark) Blue
(light) most affluent
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BMI of 3 yr olds 1988 - 1989
Wirral (0.3M), UK
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
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BMI of 3 yr olds 1990 - 1991
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
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BMI of 3 yr olds 1992 - 1993
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
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BMI of 3 yr olds 1994 - 1995
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
13
BMI of 3 yr olds 1996 - 1997
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
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BMI of 3 yr olds 1998 - 1999
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
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BMI of 3 yr olds 2000 2001
Fifths of BMI SDS BMI fifth Red (light)
fattest Red (dark) Purple Blue (dark) Blue
(light) thinnest
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Signals Rise in BMI at 2 3 years and infant
lengthfor children born on Wirral between 1990
and 2000
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Secular trend to increasing BMIis much greater
in taller children
Source Buchan et al. 2006
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Rise in BMI and fall in cardio-respiratory
enduranceof Liverpool 10 year olds from 1998 to
2004
Data from G Stratton, Liverpool Sportlinx
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Cardio-respiratory endurance levels of Liverpool
10-yr-olds fell in all BMI groups
50
45
40
35
Shuttle runs completed (n)
30
25
20
15
98/99
99/00
00/01
01/02
02/03
03/04
School Year
Obese
Overweight
Lean
Data from G Stratton, Liverpool Sportslinx
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Type 2 diabetes incidence in a typical health
economy
1600
1400
1200
1000
800
New type 2 diabetics in Salford
600
400
200
0
1997
1999
2001
2003
2005
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...these were all signals from routinely-collected
NHS data

• Beware data-tombs...

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Digital Dust (data deposit gt use)
Finance
Research
Clinical
Public Health
Deposit
Use
NHS Partners Data Tomb
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Cloud of millions of NHS messages in the local
health economy
Organise
Structured Data
Transform Examine
Structured Data Metadata
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Clear Public Good
Unclear Public Good
Decision Objects
AuditResearch Intelligence
Depersonalise
e-Lab for adefined community
Health Records
Health Records
Local Ownership
Asset Enrichment
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What is an e-Lab?

• ...an information system bringing togetherdata,
  analytical methods and peoplefor timely,
  high-quality decision-making

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e-Lab ? Audit ? Research

• Clinical audit question is diabetes care
  picking up enough treatable anaemia in patients
  with mild kidney impairment?? Answer No? Care
  pathway improvements? Next similar e-Lab query
  made easier? Deeper research...

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Clinical (audit) questions leading to scientific
findingssupporting sustainable
healthcare-academic partnership
Anaemia at lower levels of kidney impairment than
commonly thought
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Dataset ? Digital Commodity

• Serving health communities with high-quality
  health intelligence requires metadata from local
  uses...

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Excellent research becomes a by-product
ofexcellent service development
ResearchNetworks
e-Lab
Local NHS
Research
e-Lab
Local NHS
Local NHS
e-Lab
Service development
Federation of e-Labs ? scalable sustainable
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Gene Association Studies
Which genetic variation is responsible for
disease variation
Single nucleotide polymorphisms (SNPs) Human
genome 3 billion bases ? 3 million sites of
variation
The challenges of personalised medicine outstrip
our ability to use the data from current
biotechnologies
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1)
2)
3)
NIBHI Microsoft Shared Genomicsdeveloping next
generation software
Computational free-thinking, for insights from
richly-observed health environments
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Evidence Theory
Data
Configuration
Algorithms
Knowledge Management
Visualisation
Insight
Abstract thinking
Signal
ApplicationPatient or Consumer?
...the e-Research Digital Economy
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Optimising Health Systemsin a Digital Economy

• Real-time views of health(care) enriched by local
  knowledge,and smarter predictive models

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Direct Access Services
Cardiac Surgery
Surgical Wards
Cardiology
A E Emergency Medicine
Primary Community Continuing Care
Paediatric Diabetes Specialist Nurses Doctors
Diabetes Specialist Services

Medical Wards Wards
Clinical Psychology
Receptionists and Support Workers
Rheumatology
Supporting Specialist Services
Diabetes Specialist Nurses
Services for Young People
Nephrology
On Call Service
Diabetes Care
Vascular Orthopaedic Surgery
Web Based Services
Obstetrics
Joint Diabetes Antenatal Service
High Risk Foot-care Team
Diabetologists
NHS Direct
Orthotists Footwear Specialists
Ophthalmology Laser Cataract Services
Eye Screening
Hospital Dietetics
Community Dietetics
Community Podiatry
Optometrists
Pharmacies
Specialist Vitreo- Retinal Services
Primary Care Diabetes Teams
Primary Care Diabetes Teams
Primary Care Diabetes Teams
Primary Care Diabetes Teams
Primary Care Diabetes Teams
Primary Care Diabetes Teams
Community Nurses
Nursing Homes
Call Centres
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Summarising care quality
Care improvement or case-mix change?
7
150
148
146
6
Total Cholesterol
144
Systolic BP
142
5
140
138
4
136
1993
1995
1997
1999
2001
2003
2005
2007
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Biological Risk Factors
Combined CVD Risk
CVD Patient Groups
Population Policies Behaviours
OUTPUTS
Diabetes or IGT
NON-SUDS
SUDS
Physical Activity
Unstable Angina
Chronic Angina
CHD Death
Combined CVD Risk
Obesity (BMI)
Diet
Cholesterol LDL ( HDL)
Early Heart Failure
Acute MI
From any State
Smoking
Blood Pressure
Recurrent MI
Severe Heart Failure
Non-CHD Death
MI survivors
Deprivation
Additional CVD Risk Factors
Stroke PAD etc
Developing models and software to make complex
scenarios easy to explore ? democratise
commissioning?
Outputs Population-based incidence, prevalence
Deaths prevented Life-Years Life expectancy
Costs Cost-effectiveness ratios
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Open Source ProjectsSustained by the Value they
Addthrough Crowd-Wisdom(e.g. www.opencdms.org)
Care
Service Development
Research
e-Lab Sense-Making Layer
Systems Communities Individual Citizens
Standards-basedHealth Information Systems
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Equipping citizens

• Individuals and communities harnessing digital
  economy services for feeling well and preserving
  health

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Do Nothing is Not an Option

• Markets offer more unhealthy than health products
  and services
• Healthcare is too late and inaccessiblefor
  maximum potential health gain
• Wellbeing and healthcare interventions are too
  impersonal to be fully-effective

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Re-wire the brain to resist over-malnutrition?
Burning Fat
Depositing Fat
(ketone/other) molecues on skin
Active Polymers in wristband /- other signals
data
Frequent Choices
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The Wellbeing Digital Economy is Growing
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Digital Divide

• High-cost niche technologies
• Tooling up the worried well
• Inequalities in health increase
• Isolated creativity
• Low-cost widespread, open technologies
• Affordable for most citizens and nations
• Social network leverage for citizen-led health
• Large creative pool ? rapid emergence

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Harness Digital Economies via PHI
Sense-Making
Global Creativity Understanding (motivation/owne
rship)
Open-Source Integration Analytics (state-of-the-
art)Public eHealth architectures
Health and Social Care
Wellbeing
Public Funds (Global N gt S)
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Conclusion

• Digital Economy is a public health frontier
• Novel prevention
• Citizen-driven care
• e-Epidemiology
• Risks (e.g. digital divide)
• PHI has a great opportunity to harness and shape
  the Digital Economy for global public health