1. The Public Health Grid (PHGrid): Overview and Value Proposition John Stinn Deloitte Consulting Program Manager – PHGrid National Center for Public Health Informatics, CDC May 19, 2009

2. Overview  Public Health Challenges  What is Grid  Value of Grid to Public Health  Our Activities  Looking Ahead  Q&A

3. 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

4. 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 Lab System BioSense Integrator National Data Feeds Hospital, DoD, VA, etc Clinical data Local/ State Data Local/State Health Dept Syndromic Surveillance CDC BioSense AVR BioSense Data Warehouse BioSense Integrator BioSense Integrator Facility System Medical Facilities Local/ State Data Local/State Health Dept Existing Capacity (RODS, ESSENCE, GIS, etc) Facility System Various Integrator Technologies Medical Facilities

5. 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/ State Data Local/State Health Dept Surveillance & Informatics Capacity Analysis / Visualization Capacity National Data Academic / Industry Partners Local/ State Data CDC & Other Federal Agencies Scientific and Public Health Priorities

6. 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

7. Grid Represents a…  Different way of thinking  Different way of solving problems  Collaborative approach

8. 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

9. 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

10. 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

11. 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

12. 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

13. The Public Health Grid (PHGrid) Current Activities – the details…

14. PHGrid Research Projects (examples)

15. 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.

16. 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

17. RODSA-DAI Demo http://ncphi.phgrid.net:8080/rodsadai-web/

18. 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

20. Quicksilver Demo http://ncphi.phgrid.net:8080/npdsgmaps-web/

21. 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

23. 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)

24. 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

25. 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

26. 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

27. 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

28. 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

30. PHGrid Tools (HOW we do it)

33. PHGrid Service Registry http://sites.google.com/site/phgrid/Home/service-registry

36. 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

37. PHGrid – In Action

38. 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

39. 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

40. 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

41. So…How should you think about grid? Secure…. Service Oriented Architecture (SOA)… Ecosystem… Community…

42. Thank You! Questions? Tom Savel, MD tsavel@cdc.gov NCPHI, CDC 2009