the public health grid (phgrid): overview and value proposition john stinn deloitte consulting...
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The Public Health Grid (PHGrid): Overview and Value Proposition
John StinnDeloitte Consulting
Program Manager – PHGridNational Center for Public Health Informatics, CDC
May 19, 2009
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Overview
Public Health Challenges What is Grid Value of Grid to Public Health Our Activities Looking Ahead Q&A
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Current Challenges in Public Health
Public health data widely distributed Volume of public health data growing rapidly Many cultural, social and political impediments to data
sharing Requires a stronger economic model for long-term
financial sustainability Uniquely dynamic, complex and global in scale
– Situational awareness, population health monitoring, event detection, inventory tracking, countermeasures administration, alerting, etc .
Many redundant systems, application silos and data silos
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Current Situation and Challenges
Politics of control of data has been the primary obstacle to formation of a national system
Much existing data remains siloed at the Local/ State level – accessibility and visualization limited
Building systems non collaboratively leads to low adoption rates
LabSystem
BioSenseIntegrator
National Data FeedsHospital, DoD, VA , etc
Clinical data
Local/StateData
Local/State Health Dept
SyndromicSurveillance
CDC
BioSense AVR
BioSenseData
Warehouse
BioSenseIntegrator
BioSenseIntegrator
FacilitySystem
Medical Facilities
Local/StateData
Local/State Health Dept
ExistingCapacity(RODS,
ESSENCE, GIS, etc)
FacilitySystem
Various Integrator
Technologies
Medical Facilities
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Future Goal: Federated Architecture (Grid)
Leverage Existing Capacity
– Distribute resources and infrastructure
– Increase flexibility and scalability
Provide Local Control of data and services
– Reduces political barriers
– Address many privacy concerns
Foster Collaboration to define requirements, priorities, develop, and deploy technology
Users / Experts
Public Health Grid Standards, Services,
Guidance
Local/StateData
Local/State Health Dept
Surveillance & Informatics Capacity
Analysis / Visualization Capacity
National Data
Academic / Industry Partners
Local/StateData
CDC & Other Federal
Agencies
Scientific and Public Health Priorities
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What is a Grid?
A computing environment for sharing data and capabilities
Characteristics of a Grid– Decentralized - Allows data owners to share data and
applications while maintaining control– Interoperable – Standards-based allows different systems to
interact without costly customizations– Flexible – Allows data and applications to be recombined as
needed
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Grid Represents a…
Different way of thinking
Different way of solving problems
Collaborative approach
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Grid and Healthcare
International HealthGrid Association– 1 billion Euros
HealthGrid.US US - Federal
– National Cancer Institutes’ Cancer Bioinformatics Grid (caBIG) initiative• Launched in 2004• For cancer research community
– National Science Foundation• “Cyberinfrastructure”
– The coordinated aggregate of software and hardware and other technologies, as well as human expertise, required to support current and future discoveries in science and engineering. The challenge of Cyberinfrastructure is to integrate relevant and often disparate resources to provide a useful, usable, and enabling framework for research and discovery characterized by broad access and “end-to-end” coordination^
» ^ SBE/CISE Workshop on Cyberinfrastructure for the Social Sciences, Fran Berman, San Diego Supercomputer Center and UC San Diego
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Public Health Grid in Action
• Presentation, visualization and interactive environments
• Runs on the same grid as the computational grid
• These combined resources are used to support group-to-group interactions, large-scale distributed meetings, collaborative work sessions, seminars, lectures, tutorials, and training
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PHGrid Initiative: Purpose of Research
Determine the viability of Federated Architecture in Public Health
Establish relationships with key partners / collaborators
Determine / Inform public health programs and future public health informatics approaches
And….to move from the conceptual to the actual
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PHGrid Activities: Goals / Objectives
Provide a secure, easy-to-use technical and social infrastructure for solving public health problems
Lower barriers-to-entry through– Extremely low cost grid appliance – Simplified web services development (drag & drop) – Simplify data access and data exchange (drag & drop)
Connect public health grid to other grids, and to other data sources
Recruit local & state health departments, HIEs, academic institutions, national data sources, medical centers, international public health partners, and vendors
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Current State of PHGrid Activities: Research & Practice
Methodology– First develop hypothesis and
then perform research– Develop evidence base– Make evidence-based
decisions on the value of potential tools & resources
– Apply selected tools to both existing and novel systems
– Move systems to production– Continuous evaluation and
enhancement
Leveraging– Existing technology – An open / collaborative
development process – CDC as participant – not has
solution owner– An evidence base (not
personal preference)
Challenges– Gain expertise in the wide
variety of grid-based resources currently available
– Define the gaps between the PH and Grid domains
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The Public Health Grid(PHGrid)
Current Activities – the details…
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PHGrid Research Projects (examples)
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BioSurveillance POC: Federated Search
Primary requirements– Demonstrate the capability to share and visualize biosurveillance data:
• Within a State• Between States • Between States and CDC
– Aggregate data under control of state, share results with external users
– Combine and visualize results in the form of maps and simple analysis (e.g. Epi Curve)
Goal: Explore standards-based federated frameworks to promote distributed data stewardship, analytical access, and collaboration between participating stakeholders. Inform NCPHI and its public health and commercial partners of best practices and potential issues to this approach, and provide a foundation to evaluate existing and emerging interoperability protocols.
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RODSA-DAI
Foundation: Real Time Outbreak Detection System and Globus Grid Toolkit• RODS - ~20 production instances across US• Globus – Leading Open Source Grid Middleware; used in NCI’s
caBIG, GeonGrid
Hypothesis: Extending RODS with Globus Services allows the ability to query across installations, and visualize data from disparate / secured nodes
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RODSA-DAI Demo
http://ncphi.phgrid.net:8080/rodsadai-web/
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Poison Control Data Access & Integration
Demonstrate access and visualization of poison control call data via web services
Display data over multiple days over multiple call classifications
Combine and visualize results in the form of maps and simple charts
Goal: Research ability to augment public health situational awareness, by accessing non-clinical data sources of public health importance, based on secure web services
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Quicksilver Demo
http://ncphi.phgrid.net:8080/npdsgmaps-web/
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Aggregate Minimum Data Set
Obtain consensus on most relevant elements
Create common biosurveillance data structure aligning to AHIC / HITSP standards
Develop interfaces to existing partner biosurveillance systems
Distribute & refine using open source principles
Proposed elements– Condition– Condition classifier– Patient 3-digit ZIP– Count– Date
Goal: Facilitate multi-state public health situational awareness with simple, common data interchange service based on a subset of key biosurveillance data elements
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Research Partners: DEcIDE centers at the HMO Research Network Center for Education
and Research on Therapeutics University of Pennsylvania
Participating Health Plans: Geisinger Health System Group Health Cooperative Harvard Pilgrim Health Care HealthPartners Kaiser Permanente Colorado Kaiser Permanente Northern California
Developing a Distributed Research Network(DRN)
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DRN Project Goals and Objective
“The primary goals … are to improve public knowledge about health outcomes in time frames that are quicker than traditional research approaches; and to take advantage of the power of networks…”
-AHRQ DRN task order solicitation
Objective: to design a scalable, secure, distributed health information network—a distributed research network—to conduct population-based studies of the risks and benefits of therapeutics
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DRN Proof-of-Principle Demonstration
Build a network proof-of-principle to demonstrate selected functions of a distributed research network
– An authorized user authenticates to a central portal based on digital certificates
– A SAS program is distributed to each data owner (node); the data owner allows or denies the request for the program to run
– The SAS program is configured based on the data owner’s (node) local SAS settings
– The SAS program is executed at each node, and a standard results set is returned
– The results are aggregated and made available to the authorized user
– A log of site activity for each node is generated
Evaluate the proof-of-principle demonstration and characterize the needs, challenges, and barriers to creation of a distributed research network
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PHGrid / NHIN Interoperability
Challenges with bidirectional communication between the two environments:– Differences in the level of security of data that resides in each environment
– Differences in the core functions of each platform
Goal:– Demonstrate that the NHIN and PHGrid are complimentary and compatible
platforms for distributed services and federated data
– Demonstrate that the NHIN and PHGrid are capable of trusting data from each other
PHGrid Publisher
Test Script
NHIN CONNECT GW
Test Script
NHIN CONNECT ADAPTER
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PH-DGINet: Enabling shareable GIS services
Distributed/shared web services framework based on ESRI GIS technology
PH-DGINet allows Access to data, services and tools available within a single portal per organization
• PH-DGInet portal can be customizable to organization, role, individual
• DGInet supports discretionary service and data sharing
• PH-DGINet can be extended with simple analytical tools
Exploring service integration / interoperability with Globus stack
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Results & Lessons Learned
Results PHGrid infrastructure is readily
deployable in public health settings – over 10 nodes established
PH data can remain where it is best secured
Simple PH Analytics / SA can be supported in distributed environment
Lessons Learned PH will likely be supported by
multiple service providers
Collaboration is key to driving requirements and resolving issues
Weakest hardware or connection in a federated model can be the bottleneck for data visualization and analysis
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PHGrid Tools(HOW we do it)
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PHGrid Service Registry
http://sites.google.com/site/phgrid/Home/service-registry
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NCPHI R&D Lab
Facts: Created in 2007 Completely Separate from CDC
Network Running VMWare Virtual Environment
– ESX Servers– Virtual Center– Lab Manager
Workstations– 12 Windows– 3 Mac OS
Platforms/Servers:Desktop OS Platforms:Windows 2000, Windows XP, Windows Vista,
SUSE Linux Enterprise Desktop, and Ubuntu Desktop Edition
Server OS Platforms:Windows 2008 (beta), SUSE Linux Enterprise
Server, Red Had Enterprise Linux, and Ubuntu Server Edition
Application Servers:Microsift IIS, BEA WebLogic, Red Hat JBoss,
PHP
Database Servers:SQL Server 2000, SQL Server 2005, Oracle
(Standard Edition), MySQL
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PHGrid – In Action
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PHGrid and BioSense
The BioSense Program is migrating to a distributed architecture
– Cardea to enable BioSense data integration and access
– Globus to publish data and services
– AMDS for surveillance / situational awareness
– Grid enabled ‘Viewers’ to allow users to query, view, analyze situational awareness data
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Future
Move from Research to Pilot to Production – BioSense Program Committed to the Grid; NEDSS exploring use of AMDS as well
Engage more partners as nodes – Denver PH Explore interoperability between NHIN (and others) and Public Health
Grid architectures Expand public health use cases and adopt / build additional services Refine PH Grid Node Appliance
– Windows & Linux Versions– Simplify, simplify, simplify
Send node & services to data Refine Features, Functions, and Priorities for Situational Awareness
Services– Develop Ability to fuse and analyze data from heterogeneous data
models
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Future (cont.)
Many New and Emerging Partners: Within CDC
– CCID / Grid Computing / Pathogen Data
– Birth Defects
– Genomics / Bioinformatics
– NEDSS
– Environmental Tracking
– Cancer
Federal Agencies– ONC, FDA, EPA, NIH
International– WHO
Academia– Emory University
– Georgia Tech
– GeoVista
– OhioState
Reference Implementations– Grid Node (aka publisher) - in
operation– Quicksilver – in operation– Grid Viewer – Alpha June 15;
Operation, July 31– AMDS – Alpha available; Beta May
31; in Operation, July 31
NHIN Interoperability Testing– Mid-to-late July
Denver Pilot– Transitioning BioSense feeds to
grid– PHIN conference
Regional Collaborative / COE activities
– Ongoing
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So…How should you think about grid?
Secure….
Service Oriented Architecture (SOA)…
Ecosystem…
Community…