AMIA - Public Health Informatics Working Group (PHI-WG)

AMIA 2006

T22 Public Health for Informaticians
Patrick W. O'Carroll, United States Department of Health and Human Services, Washington, DC

Public health, as a social enterprise, is among the most successful human endeavors in history. Paradoxically, it is also one of the least understood and most dangerously under-funded undertakings of the modern age. Through presentations and interactive discussions, the instructor will briefly review the history of public health and the societal forces that spurred its development; clarify the relative magnitude of the contributions to human health of clinical medicine and public health; discuss and clarify the reasons why it is difficult to grasp the nature and boundaries of the profession of public health; and finally, articulate guiding principles, core functions, and time-tested approaches that define what public health really is. With this as background, participants will be engaged in a discussion of the tremendous potential for informatics to improve and transform public health, with special emphasis on several "grand challenges" currently at the forefront of the field of public health informatics.

S20 Biosurveillance Systems and Situational Awareness in Public Health: How Far Should We Go to Protect the Public from Bioterrorism?
Biosurveillance Systems and Situational Awareness in Public Health: How Far Should We Go to Protect the Public from Bioterrorism?
Margo Edmunds, The Lewin Group and Johns Hopkins University, Falls Church; John S. Parker, SAIC, McLean; John Carroll, American Institutes for Research, Concord; Chris Hass, American Institutes for Research, Concord; Shane Harris, The National Journal, Washington, DC

Biosurveillance is a cornerstone of the national strategy to detect early signs of bioterrorism and other public health threats. Surveillance systems have been an essential part of public health infrastructure for decades, and their technical, financial, and organizational challenges have been widely discussed in the public health and informatics communities. Within these communities, the development of standards-based and secure infrastructures, including compliance with PHIN guidelines, is seen as a policy priority and a public good being conducted by responsible professionals. However, surveillance is also conducted by law enforcement and intelligence agencies, with varying degrees of acceptance among policy-makers and the general public.

This multidisciplinary panel will discuss some of the broader societal implications of surveillance, including the tensions between the need for real-time information and privacy protections, the relative roles of government and the private sector, and public perceptions about threat detection. With a policy analyst as moderator, the panelists will include a retired military physician actively involved in biosurveillance system design, a software engineer who has designed secure interfaces for medical and public health professionals, a human factors researcher who has studied consumer reactions to biometrics, and a journalist who covers intelligence and homeland security.

S57 Population Health Monitoring in Regional Health Information Networks
Population Health Monitoring in Regional Health Information Networks
William B. Lober, University of Washington, Seattle; Kelly Cronin, Office of the National Coordinator for Health Information Technology, Washington; Kenneth Mandl, Children's Hospital Boston, Boston,; Farzad Mostashari, New York City Department of Health, New York; J. Marc Overhage, Regenstrief Institute, Indianapolis, IN

Information system-based, automated, syndromic surveillance for public health has become wide-spread over the past five years, albeit with very di-verse models of implementation, governance, and partnership in different jurisdictions. The accelerated pace of Regional Health Information Organization/Network development in the past year has raised questions about the optimal technical and organizational interactions between these new entities and public health. Some aspects of these interactions are being captured in AHIC and HITSP-developed Biosurveillance Use Cases. The panelists, have had early experience in automated surveillance for bioterrorism and infectious disease outbreaks, and are presently involved in Office of the National Coordinator for Health Information Technology-funded RHIO/N demonstration projects, use case development, and standards and interoperability initiatives. They will discuss the technical and organizational frameworks by which these emerging systems are being leveraged for improved population health, making use of the infrastructure, resources, and methods developed to support information system-based surveillance with the goal of more broadly improving population health and discovering new knowledge.

S76 Biosurveillance and Disaster Response
Timeliness of Emergency Department Diagnoses for Syndromic Surveillance
Debbie A. Travers, University of North Carolina, Chapel Hill, NC

Infodemiology: Tracking Flu-Related Searches on the Web for Syndromic Surveillance
Gunther Eysenbach, University of Toronto & University Health Network, Toronto

Services Oriented Architectures and Rapid Deployment of Ad-Hoc Health Surveillance Systems: Lessons from Katrina Relief Efforts
Parsa Mirhaji, University of Texas Health Science Center, Houston, Houston; S. W. Casscells, University of Texas Health Science Center, Houston, Houston; Arunkumar Srinivasan, University of Texas Health Science Center, Houston, Houston; Narendra Kunapareddy, University of Texas Health Science Center, Houston, Houston; Sean Byrne, University of Texas Health Science Center, Houston, Houston; David M. Richards, University of Texas Health Science Center, Houston, Houston; Raouf Arafat, University of Texas Health Science Center, Houston, Houston, TX

The Indiana Public Health Emergency Surveillance System: Ongoing Progress, Early Findings, and Future Directions
Shaun J. Grannis, The Regenstrief Institute, Inc., Indianapolis; Michael Wade, Indiana State Department of Health, Indianapolis; Joseph Gibson, Health and Hospital Corporation, Marion County Health Department, Indianapolis; J. M. Overhage, The Regenstrief Institute, Inc., Indianapolis, IN

S90 Semi-plenary: CDC's BioSense Real-Time Data Initiative: Improving the Nation's Emergency Preparedness
CDC's BioSense Real-Time Data Initiative: Improving the Nation's Emergency Preparedness
Barry Rhodes, Division of Emergency Preparedness and Response, CDC, Atlanta; Mike Trebatoski, Information Services, Aurora Healthcare, Milwaukee; Paul Biedrzycki, City of Milwaukee Health Department, Milwaukee; David Groves, Public Health Informatics, Science Applications International Corp., Atlanta, GA

BioSense is a national program intended to improve the nation's capabilities for disease detection, monitoring, and real-time health situational awareness, which is the ability to monitor disease over time and geography. Routine public health surveillance and investigations involve the manual reporting of cases to public health agencies and phone calls to healthcare providers for more detailed patient chart information. In public health emergencies these methods can be slow and incomplete. BioSense is a CDC-developed and hosted web-based system accessing existing data from healthcare organizations across the country. BioSense surveillance methods address the need of public health at all levels for identification, tracking, and management of rapidly spreading naturally occurring events and potential bioterrorism events using advanced algorithms for data analysis.

The BioSense Real-Time Data Initiative (BioSenseRT) will strengthen national biosurveillance efforts by emphasizing access to real-time clinically rich data from emergency departments, outpatient clinics, and other hospital settings, useful for both early event detection and health situational awareness. During an emergency event, once fully deployed, participating clinicians and local, state, and federal public health officials will have access to the same data at the same time.

AMIA 2005

T26 Public Health for Informaticians
Patrick W. O'Carroll, United States Department of Health and Human Services, Washington, DC

Public health, as a social enterprise, is among the most successful human endeavors in history. Paradoxically, it is also one of the least understood and most dangerously under-funded undertakings of the modern age. Through presentations and interactive discussions, the instructor will briefly review the history of public health and the societal forces that spurred its development; clarify the relative magnitude of the contributions to human health of clinical medicine and public health; discuss and clarify the reasons why it is difficult to grasp the nature and boundaries of the profession of public health; and finally, articulate guiding principles, core functions, and time-tested approaches that define what public health really is. With this as background, participants will be engaged in a discussion of the tremendous potential for informatics to improve and transform public health, with special emphasis on several "grand challenges" currently at the forefront of the field of public health informatics.

S03: Papers - Public Health and Biosurveillance Methods
S29: Papers - Disaster Management and Health Information Technology<br> S45: Demonstrations - Public Health Systems
S92: Papers - Public Health Informatics
S94: Panel - Modern Health Surveillance

AMIA 2003

T6 Theory and Practice of Outbreak Detection
Michael Wagner, University of Pittsburgh
Gregory Cooper, University of Pittsburgh
Per Gesteland, University of Utah
William Hogan, University of Pittsburgh
John Loonsk, Centers for Disease Control and Prevention
Andrew Moore, Carnegie Mellon University
J. Marc Overhage, Indiana University School of Medicine

Presents practical, up-to-the-minute information about methods used in real-time public health surveillance, drawing on examples from deployed systems and research.

Emerging Techniques and Concepts in Public Health and Disease Surveillance
Klaus Schafer, Compressus Inc.
Nandan Padukone, Silico Insights
Brian Jones, ScenPro
Tracee Treadwell, Centers for Disease Control and Prevention

Representatives from government and industry describe several key special projects they have been involved in that are designed to help identify the most useful and practical approaches to syndromic surveillance efforts in clinical situations.

Syndromic Surveillance: Performance and Utility
John Loonsk, Centers for Disease Control and Prevention
Kenneth Mandl, Children's Hospital Boston
J. Marc Overhage, Regenstrief Institute
Michael Wagner, University of Pittsburgh

Based on their experiences in developing and implementing information-based public health surveillance systems, panelists discuss methods to best evaluate the performance and utility of such systems and the issues and challenges involved.

Four Perspectives on Public Health Informatics Education to Develop the Public Health Information Infrastructure
Marty LaVenture, Minnesota Department of Health
Jeff Luck, University of California Los Angeles
Barbara Massoudi, Northrop Grumman Mission Systems
William Yasnoff, National Health Information Infrastructure, US Department of Health and Human Services
Moderator: Janise Richards, Centers for Disease Control and Prevention

Syndromic Surveillance: Performance and Utility-PANEL
W. B. Lober, University of Washington School of Medicine, Seattle, WA, J. W. Loonsk, Centers for Disease Control and Prevention, Atlanta, GA, K. D. Mandl, Children's Hospital Boston, Boston, MA, J. M. Overhage, Indiana University School of Medicine, Regenstrief Institute, Indianapolis, IN, and M. M. Wagner, University of Pittsburgh, Pittsburgh, PA

Public health surveillance has long been recognized as an important element of public health practice. In many communities there remains strong sense of urgency around the deployment and refinement of these systems. Based on their experiences in developing and implementing information system-based public health surveillance systems, the panelists will propose methods to evaluate the performance and utility of those systems.

S15 BioSTORM: A System for Automated Surveillance of Diverse Data Sources
M. J. O'Connor, D. L. Buckeridge, M. Choy, M. Crubezy, Z. Pincus, and M. A. Musen, Stanford University School of Medicine, Stanford, CA

Heightened concerns about bioterrorism are forcing changes to the traditional biosurveillance-model. Public health departments are under pressure to follow multiple, non-specific, pre-diagnostic indicators, often drawn from many data sources. As a result, there is a need for biosurveillance systems that can use a variety of analysis techniques to rapidly integrate and process multiple diverse data feeds using a variety of problem solving techniques to give timely analysis. To meet these requirements, we are developing a new system called BioSTORM (Biological Spatio-Temporal Outbreak Rea-soning Module).

S20 An Analytic Framework for Space-time Aberrancy Detection in Public Health Surveillance Data
D. L. Buckeridge, Palo Alto Veterans Health Care, Stanford University, M. A. Musen, Stanford University School of Medicine, P. Switzer, Stanford University, and M. Crubezy, Stanford University School of Medicine, Stanford, CA

Public health surveillance is changing in response to concerns about bioterrorism, which have increased the pressure for early detection of epidemics. Rapid detection necessitates following multiple non-specific indicators and accounting for spatial structure. No single analytic method can meet all of these requirements for all data sources and all surveillance goals. Analytic methods must be selected and configured to meet a surveillance goal, but there are no uniform criteria to guide the selection and configuration process. In this paper, we describe work towards the development of an analytic framework for space-time aberrancy detection in public health surveillance data. The framework decomposes surveillance analysis into sub-tasks and identifies knowledge that can facilitate selection of methods to accomplish sub-tasks.

S31 Emerging Techniques and Concepts in Public Health and Disease Surveillance
M. J. Hopmeier, Unconventional Concepts, Inc., Mary Esther, FL, M. Greberman, Walter Reed Army Medical Center, K. Schafer, Compressus, Inc., Washington, DC, N. Padukone, Silico Insights, Woburn, MA, B. Jones, ScenPro, Richardson, TX, and T. Treadwell, Centers for Disease Control and Prevention, Atlanta, GA

Health-care providers, clinical laboratory personnel, infection control professionals, and health departments play critical and complementary roles in monitoring, recognizing, and responding to naturally occurring illnesses and those caused by intentional release of biologic or chemical agents. The syndrome descriptions, epidemiologic clues, and laboratory recommendations discussed by this panel provide basic guidance that can be implemented immediately to improve recognition of these events.

S67 Four Perspectives on Public Health Informatics Education to Develop the Public Health Information Infrastructure-PANEL
J. Richards, Centers for Disease Control and Prevention, Atlanta, GA, M. LaVenture, Minnesota Department of Health, Minneapolis, MN, J. Luck, University of California Los Angeles School of Public Health, Los Angeles, CA, B. L. Massoudi, Northrop Grumman Mission Systems, Atlanta, GA, and W. A. Yasnoff, Department of Health and Human Services, Washington, DC

Building on the education and training focus area within the National Agenda for Public Health Informatics, this panel will present four perspectives on the informatics education. These four perspectives include academic, industry, state and federal agency viewpoints. This panel, sponsored by the Prevention and Public Health Working Group, will provide insights on informatics education for the development of a robust public health information infrastructure. It will benefit both public health professionals who wish to improve their informatics knowledge and medical informaticians wishing to learn about public health information infrastructure.

S82 Integrating Syndromic Surveillance Data Across Multiple Locations: Effects on Outbreak Detection Performance
B. Y. Reis, Children's Hospital and K. D. Mandl, Children's Hospital Boston, Harvard Medical School, Boston, MA

Syndromic surveillance systems are being deployed widely to monitor for signals of covert bioterrorist attacks. Regional systems are being established through the integration of local surveillance data across multiple facilities. We studied how different methods of data integration affect outbreak detection performance. We used a simulation relying on a semi-synthetic dataset, introducing simulated outbreaks of different sizes into historical visit data from two hospitals. In one simulation, we introduced the synthetic outbreak evenly into both hospital datasets (aggregate model). In the second, the outbreak was introduced into only one or the other of the hospital datasets (local model). We found that the aggregate model had a higher sensitivity for detecting outbreaks that were evenly distributed between the hospitals. However, for outbreaks that were localized to one facility, maintaining individual models for each location proved to be better. Given the complementary benefits offered by both approaches, the results suggest building a hybrid system that includes both individual models for each location, and an aggregate model that combines all the data. We also discuss options for multi-level signal integration hierarchies.

AMIA 2002

T22 Theory and Practice of Outbreak Detection
Michael M. Wagner, MD, PhD, Wendy Chapman, PhD, Gregory F. Cooper, MD, PhD, Jeremy Espino, MD, Per Gesteland, MD, William Hogan, MD, MS, John Loonsk, MD, and Andrew Moore, PhD

Focuses on topics in real-time public health surveillance ranging from the network level to the application level to the organizational level.

S30 Paperless in Las Vegas: Using New Technology to Report Public Health Service Data Center for Disease Control and Prevention and TRW Inc.

Presenters:
Stacie M. Greby, DVM, MPH, Epidemiologist, National Center for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, and Michael Fanning, BS, Health Care Analyst, TRW Inc., Atlanta, GA.

A key component of HIV Prevention Programs is the provision of HIV counseling, testing, and referral (CTR) services to those at increased risk for acquiring HIV. Each year over two million CTR episodes are reported from CDC-funded HIV prevention services. Data are used to monitor and evaluate prevention programs at the local, state, and federal levels. There is a significant time burden placed on counselors to complete the necessary forms. There are additional time delays to enter and report data before it can be translated into program and evaluation information. In an effort to minimize the time requirements of the current system, CDC and TRW staff developed a paperless system using a personal digital assistant (PDA). The current data form was translated to the PDA, with routine fields preset when the counselor logs onto the PDA. The system was piloted at a HIV CTR Clinic in the Clark County Health District in Las Vegas, Nevada. Benefits, limitations, and counselor impressions of the final paperless system will be discussed.

S35 Technology Transfer Track Plenary: From Public Health and Biosurveillance to Organizational Readiness

Timely Redistribution of Information for Epidemiological Surveillance and Alert: the Experience from the French Communicable Diseases Network
Alain J. Valleron, PhD INSERM & University of Paris 6 INSERM & University of Paris 6 J.J. Vidal, PhD, UCLA, Los Angeles, CA

Since 1984 the French Communicable Disease Network (FCDN) collects and analyses epidemiological information obtained online from a team of "Sentinel General Practitioners" (SGPs). It redistributes this information in the form of standardised weekly incidence estimates. These weekly estimates now appear on the Internet and are the basis for issuing alerts of influenza epidemics. We postulate that day to day estimations would be highly desirable to achieve timely detection of the actual onset of the epidemic, a need dramatically underscored by the emergence of bioterrorism. The present paper suggests the feasibility of reconstructing daily epidemiological information using local smoothing with a suitable spline function to obtain short latency alert messages.

Development and Pilot Testing of an Organizational Information Technology/Systems Innovation Readiness Scale (OITIRS)
Rita Snyder-Halpern, PhD, RN, CNAA, BC

Empirical evidence indicates that healthcare organizational readiness for new information technology/systems (IT/S) is crucial to successful innovation. Despite this evidence, limited research has been done to define innovation readiness, and develop and test metrics to measure it. This presentation reports on the third phase in a multi-phased research program focused on healthcare organizational change related to IT/S innovation. In the initial two phases, the concept of IT/S innovation readiness was explored and its sub-dimensions identified and validated. In the third phase, findings from the first two phases were used to develop and pilot test an Organizational Information Technology/Systems Innovation Readiness Scale (OITIRS) for use in healthcare settings. The specific aims of this presentation are to 1) provide background information on the development of the OITIRS, and 2) report pilot testing results that support use of the OITIRS in healthcare informatics research.

Data, Network, and Application: Technical Description of the Utah RODS Winter Olympic Biosurveillance System
Fu-Chiang Tsui, PhD University of Pittsburgh University of Pittsburgh J.U. Espino, MD, University of Pittsburgh, Pittsburgh, PA M.M. Wagner, MD, PhD, University of Pittsburgh, Pittsburgh, PA P. Gesteland, MD, University of Utah, Salt Lake, UT O. Ivanov, MD, University of Pittsburgh, Pittsburgh, PA R. Olszewski, PhD, University of Pittsburgh, Pittsburgh, PA Z. Liu, University of Pittsburgh, Pittsburgh, PA X. Zeng, MD, University of Pittsburgh, Pittsburgh, PA W.W. Chapman, PhD, University of Pittsburgh, Pittsburgh, PA W.K Wong, MS, University of Pittsburgh, Pittsburgh, PA A.W. Moore, PhD, Carnegie Mellon University, Pittsburgh, PA

Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based real-time automated biosurveillance system for Utah, the Utah Real-time Outbreak and Disease Surveillance system (Utah RODS), in six weeks using our existing Real-time Outbreak and Disease Surveillance (RODS) architecture. During the Olympics, Utah RODS received real-time HL-7 admission messages from 10 emergency departments and 20 walk-in clinics. It collected free-text chief complaints, categorized them into one of seven prodromes classes using natural language processing, and provided a web interface for real-time display of time series graphs, geographic information system output, outbreak algorithm alerts, and details of the cases. The system detected two possible outbreaks that were dismissed as the natural result of increasing rates of Influenza. Utah RODS allowed us to further understand the complexities underlying the rapid deployment of a RODS-like system.

A UML-based Meta-Framework for System Design in Public Health Informatics
Anna Orlova, PhD Johns Hopkins Bloomberg School of Public Health Johns Hopkins Bloomberg School of Public Health C.U. Lehmann, MD, The Johns Hopkins University, Baltimore, MD

The National Agenda for Public Health Informatics calls for standards in data and knowledge representation within public health, which requires a multi-level framework that links all aspects of public health. Method: The literature of public health informatics and public health informatics application were reviewed. A UML-based systems analysis was performed. Face validity of results was evaluated in analyzing the public health domain of lead poisoning. Results: The core class of the UML-based system of public health is the Public Health Domain, which is associated with multiple Problems, for which Actors provide Perspectives. Actors take Actions that define, generate, utilize and/or evaluate Data Sources. The life cycle of the domain is a sequence of activities attributed to its problems that spirals through multiple iterations and realizations within a domain. Conclusion: The proposed Public Health Informatics Meta-Framework broadens efforts in applying informatics principles to the field of public health.

S38 Panel: Building a Public Health Informatics Infrastructure for Bioterrorism Preparedness and Response Building a Public Health Informatics Infrastructure for Bioterrorism Preparedness and Response
Jeff Luck, MBA, PhD UCLA School of Public Health UCLA School of Public Health L. Brewer, RN, MPH, Tarrant County Public Health Department, Fort Worth, TX F. Eisenberg, MD, MPH, Siemens Health Services, Malvern, PA J. Loonsk, MD, Centers for Disease Control, Atlanta, GA M.M. Wagner, MD, PhD, University of Pittsburgh, Pittsburgh, PA

A robust public health informatics infrastructure is a critical component of effective bioterrorism preparedness and response. The anthrax mail attacks of last year highlighted shortcomings in the ability of existing systems to detect and respond to bioterroist threats. However, recent policy initiatives have begun to strengthen the informatics infrastructure of state and local public health departments. Public-private partnerships are also being formed to utilize data collected by clinical information systems as the foundation of integrated bioterrorism surveillance. This panel will report on informatics lessons learned from the 2001 bioterrorist attacks and discuss public and private initiatives formulated as a result. Panelists will analyze the technical and institutional challenges in creating a robust public health informatics infrastructure that requires coordination among federal agencies, state and local health departments, regional health provider networks, and individual facility clinical information systems.

S50 Surveillance - Bioterrorism

National Pharmaceutical Stockpile Drill Analysis Using XML Data Collection on Wireless Java Phones
Bryant T. Karras, MD School of Public Health & Community Medicine, University of Washington, Seattle S. Huq, MBBS, University of Washington, Seattle, WA D. Bliss, University of Washington, Seattle, WA W.B. Lober, MD, University of Washington, Seattle, WA

his study describes an informatics effort to track subjects through a National Pharmaceutical Stockpile (NPS) distribution drill. The drill took place in Seattle on 1/24/2002. Washington and the State Department of Health are among the first in the nation to stage a NPS drill testing the distribution of medications to mock patients, thereby testing the treatment capacity of the plan given a post-anthrax exposure scenario. The goal of the Public Health Informatics Group at the University of Washington (www.phig.washington.edu) was to use informatics approaches to monitor subject numbers and elapsed time. This study compares accuracy of time measurements using a mobile phone Java application to traditional paper recording in a live drill of the NPS. Pearson correlation = 1.0 in 2 of 3 stations. Differences in last station measurements can be explained by delay in recording of the exit time. We discuss development of the application itself and lessons learned. (MeSH Bioterrorism, Informatics, Public Health)

Knowledge-Based Bioterrorism Surveillance
David L. Buckeridge, MD, MSc Stanford University Stanford Medical Informatics Stanford University Stanford Medical Informatics J.K. Graham, MD, Stanford University, Stanford, CA M.J. O'Connor, MSc, Stanford University, Stanford, CA M.K. Choy, Stanford University, Stanford, CA S.W. Tu, MS, Stanford University, Stanford, CA M.A. Musen, MD PhD, Stanford University, Stanford, CA

An epidemic resulting from an act of bioterrorism could be catastrophic. However, if an epidemic can be detected and characterized early on, prompt public health intervention may mitigate its impact. Current surveillance approaches do not perform well in terms of rapid epidemic detection or epidemic monitoring. One reason for this shortcoming is their failure to bring existing knowledge and data to bear on the problem in a coherent manner. Knowledge-based methods can integrate surveillance data and knowledge, and allow for careful evaluation of problem-solving methods. This paper presents an argument for knowledge-based surveillance, describes a prototype of BioSTORM, a system for real-time epidemic surveillance, and shows an initial evaluation of this system applied to a simulated epidemic from a bioterrorism attack.

Rapid Deployment of an Electronic Disease Surveillance System in the State of Utah for the 2002 Olympic Winter Games
Per H. Gesteland, MD University of Utah University of Utah M.M. Wagner, MD, PhD, The RODS Laboratory, Pittsburgh, PA W.W. Chapman, PhD, The RODS Laboratory, Pittsburgh, PA J.U. Espino, MD, The RODS Laboratory, Pittsburgh, PA F. Tsui, PhD, The RODS Laboratory, Pittsburgh, PA R.M. Gardner, PhD, University of Utah, Salt Lake City, UT R.T. Rolfs, MD, MPH, Utah Department of Health, Salt Lake City, UT V. Dato, MD, MPH B.C. James, MD, MStat, Intermountain Health Care, Salt Lake City, UT T.J. Colecchia, JD, University of Pittsburgh, Pittsburgh, PA P.J. Haug, MD, LDS Hospital, Salt Lake City, UT

The key to minimizing the effects of an intentionally caused disease outbreak is early detection of the attack and rapid identification of the affected individuals. The Bush administration's leadership in advocating for biosurveillance systems capable of monitoring for bioterrorism attacks suggests that we should move quickly to establish a nationwide early warning biosurveillance system as a defense against this threat. The spirit of collaboration and unity inspired by the events of 9-11 and the 2002 Olympic Winter Games in Salt Lake City provided the opportunity to demonstrate how a prototypic biosurveillance system could be rapidly deployed. In seven weeks we were able to implement an automated, real-time disease outbreak detection system in the State of Utah and monitored 80,684 acute care visits occurring during a 28-day period spanning the Olympics. No trends of immediate public health concern were identified.

Evaluation of Three Classifiers of Acute Gastrointestinal Syndrome for Syndromic Surveillance
Oleg Ivanov, MD University of Pittsburgh University of Pittsburgh M.M. Wagner, MD, PhD, University of Pittsburgh, Pittsburgh, PA W.W. Chapman, PhD, University of Pittsburgh, Pittsburgh, PA R.T. Olszewski, PhD, University of Pittsburgh, Pittsburgh, PA

CD-9-coded emergency department (ED) diagnoses and free-text triage diagnoses are routinely collected data elements that have potential value for public health surveillance and early detection of epidemics. We constructed and measured performance of three classifiers for the detection of cases of acute gastrointestinal syndrome of public health significance: one used ICD-9-coded ED diagnosis as input data; the other two used free-text triage diagnosis. We measured the performance of these classifiers against the expert classification of cases based on review of ED reports. The sensitivity of the ICD-9-code classifier was 0.32, and the specificity was 0.99. The sensitivity of a na�ve Bayes classifier using triage diagnoses was 0.63, the specificity was 0.94, and the area under the ROC curve was 0.82. A bigram Bayes classifier had sensitivity 0.38, specificity 0.94, and area under the ROC of 0.69. We conclude that a naive Bayes classifier of free-text triage diagnosis data provides more sensitive and earlier detection of cases of acute gastrointestinal syndrome than either a bigram Bayes classifier or an ICD-9 code classifier. The sensitivity achieved should be sufficient for syndromic surveillance system designed to detect moderate to large epidemics.

S58 Panel: Update on LOINC and RELMA-Expanded Uses in Public Health Reporting and Bioterrorism, New Drug Submissions, Attachments, Laboratory Instrument Messages, Clinical Reports, and Dentistry Expanded Uses of LOINC
Clement J. McDonald, MD Regenstrief Institute Regenstrief Institute J.G. Suico, MD, Regenstrief Institute, Indianapolis, IN S.M. Huff, MD, 3M Health Care, Salt Lake City, UT S.J. Steindel, PhD, Centers for Disease Control and Prevention, Atlanta, GA J.B. deHaan, PhD, Unilabs SA, Geneva, Switzerland

The merging of clinical observations from many sources into one medical record or research database requires that the names and codes used for identifying the clinical observations in HL7 messages be standardized. The Logical Observation Identifier Names and Codes (LOINC) database, which now carries records for more than 30,000 different observations covering subjects ranging from laboratory results to vital signs and dental observations to ultrasound studies, provides such a standard set of codes and names. , LOINC codes are being used across a wide spectrum of applications including public health reporting, new drug applications, tumor registry communication, and medical record filing. , The panel will discuss a number of new LOINC developments including a completely new Regenstrief LOINC Mapping Assistant (RELMA) program for browsing and mapping terminology, the availability of short names and hierarchies for laboratory test names, coverage of two completely new clinical subjects-dentistry and names for dictated reports, the adoption of LOINC by the Clinical Data Interchange Standards Consortium (CDISC) for submission of new drug application data by the pharmaceutical industry, and updates on the HIPAA claims attachments and the Centers for Disease Control and Prevention (CDC's) approach to automated reporting of communicable diseases. We will also discuss the international use of LOINC including the adoption of LOINC in Germany by the Deutsches Institut f�r Normung (DIN) , and the translation of a subset of LOINC codes to German, Italian, and French for the CUMUL in Switzerland.

Tutorial 69 Panel: Informatics in Action - Applications of Geographic Information Systems (GIS) in Public Health
Authors: Dr. Vicki Hertzberg, PhD Emory University Emory University C. Hanchette, PhD, RTI International, Atlanta, GA C. Schenck-Yglesias, MHS, JHPIEGO, Baltimore, MD C.V. Lee, MD, MPH, MA, ATSDR, Atlanta, GA W. Niehaus, PhD, SRA International, Inc., Fairfax, VA

GIS are increasingly used by public health researchers and practitioners to promote the health of populations and prevention of disease, disability, and injury. Since threats to health vary over time and with geography, understanding the location of events, exposures, and availability of public health resources is critical in developing effective prevention and intervention strategies. In this panel we describe the development and application of GIS to several public health issues, exploring the challenges presented and opportunities arising as a result. We describe the use of spatial and health indicator data for targeting interventions in developing countries, illustrating the use of GIS with the Malawi Ministry of Health and Population to develop health human resource deployment and training plans. We explore the use of GIS to characterize the spatial distribution of disease in populations living around hazardous waste sites, and the utility of GIS in meeting needs in emergency events. We describe the development of an analysis platform to combine GIS with other text-mining tools such as text clustering and text summarization to enhance the understanding of geography and other key concepts in public health data. Finally, we speculate on the future impact of GIS on public health research and practice.