Transcript From Intervention Informatics to Prevention Informatics

From Intervention Informatics to
Prevention Informatics:
Lessons & Opportunities for
Research
American Society for Information Science
and Technology
Lecture Series Award 2010
First Annual Lecture, April 11, 2011
School of Library and Information
Science, University of Kentucky
Lexington, Kentucky
Sherrilynne Fuller, MLS, PhD
Professor, Biomedical & Health Informatics
School of Medicine and
Information School (Joint)
Co-Director, Center for Public Health Informatics and
Senior Advisor, Dean, University Libraries
University of Washington, Seattle, WA
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Souce: Rear Admiral Patrick O’Carroll, Region 10 Health Administrator
Role of Medical Care in 20th
Century Public Health
Achievements*
Public Health Achievement
Due to Medical Care?
Vaccination
Indirect
Motor-vehicle safety
No
Safer workplaces
No
Control of infectious diseases
+/-
 Coronary heart disease/stroke deaths
+/-
Safer and healthier foods
No
Healthier mothers and babies
+/-
Family planning
No
Safer drinking water
No
Recognition of tobacco as health hazard
No
*Rear Admiral Patrick O’Carroll, Region X Health Administrator
Healthcare Costs Versus Results
•
•
•
How the United States compares with other O.E.C.D. (Organization
for Economic Cooperation and Development) members
A country’s wealth usually dictates how much money it spends on
health care, but spending in the United States is far beyond that of its
peer countries.
Health care spending as a percentage of gross domestic product
(2007)
New York Times – June 5, 2010
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Life Expectancy at Birth
New York Times – June 5, 2010
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Prevention Consultations
United States lags in basic preventive care, like annual checkups,
and relies heavily on expensive specialists rather than primary care
practitioners
Number of primary care visits/yearY
New York Times – June 5, 2010
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“Risky Trade”*
Global Express: “the system that
connects us across oceans, continents,
national boundaries, cultures,
languages, groups, ethnicity and trade
systems”
*Kimball AM. Risky Trade: Infectious Disease in the Era of Global Trade.
Ashgate, 2006
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Trade Routes &
Cholera Epidemics – 1892*
*Proust, A. (1892). La defense de L'Europe contre le cholera.
Paris, G. Masson.
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US Malaria Deaths, 1870
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Complexity….
“Everything about malaria is so molded
by local conditions that it becomes a
thousand epidemiological puzzles. Like
chess, it is played with a few pieces but
is capable of an infinite variety of
situations.” ….
Hackett LW. 1937. Malaria in Europe: An Ecological Study. Oxford, UK:
Oxford University Press.
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Why Are Global Prevention
Information Systems Critical?
• New viruses travel more rapidly, transforming local afflictions
into worldwide epidemics; increase in new and re-emerging
infectious diseases -- 70% of which are zoonoses
• A modern lifestyle that travels just as fast, contributing to
swelling epidemics of non-communicable diseases
• A human resources crisis directly linked to transnational labor,
economics, migration and natural disasters
• The growth of vertical (e.g. HIV/AIDS, TB, malaria) initiatives
has pushed advances for specific diseases but has also put
pressure on individual countries’ public health systems
• Preventing and responding to these threats requires rapid and
targeted exchange of accurate and detailed health information
Adapted from: AM Kimball, Risky Trade: Infectious Disease
in the Era of Global Trade. Ashgate, 2006
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Definitions
Adapted from Shortliffe, 2006 and Hersh, 2007.
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Definitions
Intervention Informatics:
– Focus:
• Individual
• Patient with injury, disease, abnormal condition
• Track: actions, procedures, diagnoses,
therapies
• Reactive – after the health problem occurs
– Lacks Context:
• Community (rural, urban, agricultural, inner city)
• Family members/relationships
• Individual (home, travel, hobbies, etc. .)
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Definitions
Prevention Informatics:
Focus:
• Individual in context: family, community, the
world
• Health & well-being of individual & populations
• Safe environment
–
–
–
–
Hospital (preventing medical errors)
Home (water & sanitation)
Work (preventing injuries)
Roads and travel conveyances
• Proactive
• Highly data-intensive and data-driven
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Core Challenge: The Data Silo Problem
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Adapted from InStedd.org SFuller 2011
New and Improved Approaches
to Old Information Challenges in
Prevention
• Classification, thesauri and ontologies
• Knowledge management
• Disease outbreak event detection and prevention
systems utilizing:
– satellite data
– news media, published reports
– crowd-sourcing
• Mobile technologies
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Classification Systems: Building
Blocks for Information Systems
What do these have in common?
• seventeenth-century mortality table whose causes of
death include "fainted in a bath," "frighted," and "itch");
• the assignment of subject headings to books in a
library;
• and the separation of machine-washable clothes from
hand-washables have in common??
All, of course, are examples of classification – upon
which information systems of all types are built.
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William Farr (1837)
“The advantages of a uniform statistical nomenclature,
however imperfect, are so obvious, that it is surprising no
attention has been paid to its enforcement in Bills of
Mortality. Each disease has, in many instances, been
denoted by three or four terms, and each term has been
applied to as many different diseases: vague, inconvenient
names have been employed, or complications have been
registered instead of primary diseases…
The nomenclature is of as much importance in this
department of inquiry as weights and measures in the
physical sciences, and should be settled without delay.”
Sources:
http://www.who.int/classifications/icd/en/HistoryOfICD.pdf
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International Classification of
Diseases (ICD9, 10….)





Inconsistency
Lack of concept permanence
Disregard for context
Language translation
Slow adaptation to new/emerging disease
terminology
Cimino JJ. Desiderata for controlled medical vocabularies in the
twenty-first century. Methods Inf Med. 1998 Nov;37(4-5):394-403
.
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Knowledge Management
Challenge
Neither the creation nor the distribution of
information resources* upon which public
health practitioners depend is managed or
presented in any systematic or
comprehensive way at the present time**
*data of all types, guidelines, research findings, maps,
policies, laws, evaluation metrics, teaching materials,
etc.
**Revere, D., A. M. Turner,… Fuller, SF. (2007). "Understanding the information
needs of public health practitioners: a literature review to inform design of an
interactive digital knowledge management system." J Biomed Inform 40(4): 41021.
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Knowledge Management
Approach
• Research workflow and information needs of
public health practitioners for decision
support
• Develop and optimize a knowledge
management system to support iterative
refinement of a set of retrieval and
information management tools for public
health practitioners
Center for Public Health Informatics University of
Washington
Center for Public Health Informatics University of Washington
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Clinical
Public Health
Information Interchange –
Research Questions
• Clinical information to support chronic and infectious disease
interventions in communities: what is the minimum data set?
• PH clinical data (e.g. immunization, disease status, relevant
community information) to electronic health record (EHR)?
• Timely approaches to people (care providers) and directory type
information interchange?
• Research finding: how to extract from the literature and present
to practitioners?
• Utilization of community health information for decision support
for individual patients?
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Disease Outbreak Detection and
Prevention Systems: Mapping
– Satellite data; airline data; nonprescription drug purchases
– News media, published reports from
local newspapers
– Internet activity -- google concepts
searches
– Citizen-reported information
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Using Satellite Data to Predict
Infectious Disease Outbreaks
Anyamba A et al Proc. Natl Acad Sci 2009:106(3):955-959
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Data Coordination – Mekong Basin
Region
Healthmap.org
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USING AIRLINE DATA TO PREDICT EMERGING INFECTIOUS
DISEASE TRANSMISSION
Biodiaspora.com
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Google Public Data Explorer Tool
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Volunteered Geographic Information
for Disaster Relief: Harnessing the Wisdom
and Power of the Public
A Case Study of the Haitian
Earthquake*
• Lack of detailed maps for emergency
response led to the use of crowd-sourced
contributions to build critical maps
*Zook, M University of Kentucky; Graham M University of Oxford;
Shelton T University of Kentucky; Gorman, S FortiusOne. World Medical & Health Policy
Vol. 2: Iss. 2, Article 2 (2010)
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MOBILE TECHNOLOGIES:
Faster and more reliable data collection and
sharing for decision making by health providers
as well as consumers
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OpenData Kit (ODK)*
• Lack of reliable infrastructure makes data
collection difficult
• Paper is still primary way data is collected
around the world
• ODK – open-source (non-proprietary) suite of
tools for using mobile devices to collect,
visualize and share data
*ODK=developed at University of Washington
http://change.washington.edu/projects/odk
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Paper-based
Systems
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OpenData Kit
(ODK) for Mobile
Data Collection
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Summary:
Research Opportunities Abound
• Improved vocabularies, thesauri and ontologies of
concepts are transforming ability to aggregate data
and information across disparate information
resources and databases
• Enhanced collection techniques and new
combinations of data and information to:
– Generate new hypothesis and approaches to preventing
infectious disease outbreaks
– Respond more rapidly to natural disasters and humancaused emergencies
– Support two-way communications with individuals
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Summary:
Research Opportunities Abound
• Opportunity to optimize timely data exchange of
critical information between clinical and public health
information systems to improve quality of response
for individual and community health
• Citizen generated information offers new means to
respond to disasters as well as offer communities of
practice to support resource-constrained
environments
• With the availability of instant communications need
to recognize and prepare for unexpected “crowd”
reactions to threats
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Resources
1. Fuller, S. (2010). "Tracking the Global Express: new
tools addressing disease threats across the world."
Epidemiology. 21(6): 769-771.
2. Proust A. La Defense de L’Europe Contre le Cholera.
Paris: Masson; 1892.
3. Kimball A. Risky Trade: Infectious Disease in the Era of
Global Trade. Aldershot, United Kingdom: Ashgate
Publishing; 2006.
4. Brown C. Emerging diseases: the global express. Vet
Pathol. 2010;47: 9–14.
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Resources
5. Chretien JP, Burkom HS, Sedyaningsih ER, et al.
Syndromic surveillance: adapting innovations to
developing settings. PLoS Med. 2008;5:e72.
6. Brownstein JS, Freifield CC, Madoff LC. Digital
disease detection—harnessing the web for public
health surveillance. N Engl J Med. 2009;360:2153–
21576..
7. Mekong Basin Disease Surveillance Network.
Available at:
http://www.mbdsoffice.com/index_2008.php.
Accessed July 31, 2010.
.
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Resources
8. Open Data Kit (ODK)—open source tools for
collecting, managing and retrieving data. Available at:
http://change.washington.edu/projects/odk.
9. GeoChat—an open source, group communications
technology. Available at: http://instedd.org/geochat.
10. Ushahidi—an open source tool for information
collection, visualization and interactive mapping.
Available at: http://www.ushahidi.com/.
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Resources
11. Yi Q, H. R., Hillringhouse EA, Sorensen SS, Oberle
MW, Fuller SS, Wallace and JC. (2008). "Integrating
open-source technologies to build low-cost
information systems for improved access to public
health data. ." Int J Health Geogr. 2008 Jun 9;7:29 7:
29-.
12. Zook M, Graham M, Shelton T, et al. Volunteered
geographic information and crowdsourcing disaster
relief: a case study of the Haitian earthquake. World
Med Health Policy. 2010;2:2. Available at:
http://www.psocommons.org/wmhp/vol2/iss2/art2
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Resources
13. US Malaria Deaths, 1870 - The Scientist - Magazine
of the Life Sciences (http://www.thescientist.com/article/display/57476/#ixzz1HBiuunjp)
14. Revere, D., A. M. Turner,… Fuller, S. (2007).
"Understanding the information needs of public
health practitioners: a literature review to inform
design of an interactive digital knowledge
management system." J Biomed Inform 40(4): 41021.
Center for Public Health Informatics University of Washington
SFuller 2011