DIMACS Subgroup on Adverse Event/Disease Reporting, Surveillance, and Analysis
DIMACS Working Group on Adverse Event/Disease Reporting, Surveillance, and Analysis II
Overview of Uses for Public Health Surveillance
Abstract: Public health surveillance is the ongoing, systematic collection, analysis, and interpretation of health-related data essential to the planning, implementation, and evaluation of public health practice. This presentation will address how public health surveillance supports assessment by estimating the magnitude of public health problems, describing the natural history of a disease, determining the distribution and spread of illness, detecting outbreaks, stimulating research, evaluating public health practice, monitoring changes in disease agents, detecting changes in health practices, and facilitating planning. With increased interest for public health surveillance to detect outbreaks, non-traditional data sources are being explored and performance priorities for surveillance systems are being modified. This presentation will highlight changing demands on public health surveillance and current research needs.
Bio: Dr. Daniel M. Sosin is the Director of the Division of Public Health Surveillance and Informatics in the Epidemiology Program Office (EPO), at the Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia.
He began his career at CDC in 1986 as an Epidemic Intelligence Service (EIS) Officer in the U.S. Public Health Service assigned to the Kentucky Department for Health Services in Frankfort, Kentucky. He served as a CDC Preventive Medicine Resident in the Division of Injury Epidemiology and Control in 1988-89. He supervised state-based EIS Officers as a Section Chief in EPO from 1989-1994 and then returned to the National Center for Injury Prevention and Control (NCIPC) to study traumatic brain injury (TBI) and develop longitudinal surveillance of TBI. Dr. Sosin's scientific investigations include numerous epidemiologic investigations of TBI, including those resulting from motorcycle and bicycle crashes, adolescent risk behaviors, and a range of outbreak investigations. He later served as the Associate Director for Science in NCIPC where he coordinated national injury surveillance and extramural research activities, spearheading their new research agenda and a variety of research policies.
Dr. Sosin is board certified in preventive medicine and internal medicine. He received his B.S. in biology from the University of Michigan; his M.D. from Yale University School of Medicine; and his M.P.H. in Epidemiology from the University of Washington School of Public Health.
As Director, Dr. Sosin has responsibilities in planning, managing and evaluating Division programs of National Electronic Telecommunications System for Surveillance, the National Notifiable Disease Surveillance System, 122 Cities Mortality Reporting System, the Public Health Informatics Fellowship Program, the Assessment Initiative, CDC WONDER and web-access to CDC data sets, Epi Info, and the Medical Examiner and Coroner Information Sharing Program. He also serves as a senior advisor for surveillance policy, research, and program direction. Dr. Sosin currently serves as a Clinical Assistant Professor of Medicine at Emory University. He serves as a scientific reviewer for various medical journals. Professional memberships include the American College of Physicians (Fellow), the American College of Preventive Medicine, the American Medical Association, and the Commissioned Officers Association - U.S. Public Health Service.
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David Walker, CDC
Overview of the Information Systems Currently Available to Public
Health Researchers
Abstract: There are a large number of data sources available for public
health surveillance and research. Active and passive health surveillance
systems allow researchers the opportunity to monitor the incidents of
specific diseases or preventative measures on a nationwide scale, while
health-related administrative databases from health providers or commercial
entities can provide monitoring of a broad range of health issues within a
specific population. Information from these varying data systems may be
integrated to provide researchers with more enhanced signal detection,
disease monitoring, and analytical capabilities than single data systems can
provide. This presentation will provide a broad overview of the various
types of reporting systems available to public health researchers, and
discuss generally how information form differing systems may be integrated
for research purposes.
Bio: David Walker holds an MPH in Biostatistics from the University of
Oklahoma. He is a Public Health Analyst with the Centers for Disease Control
and Prevention, currently serving as the Deputy Branch Chief of the
Statistical Analysis Branch of the National Immunization Program. His
primary area of focus is the data management of large, national data systems
employed to monitor vaccine preventable disease and vaccine safety issues.
He has served as the Acting Activity Chief of the Systems Operations and
Design Activity of NIP, been involved in the NEDSS Operational Workgroup for
three years.
An Introduction to Multiple Systems Estimation for Estimating a
Count of Adverse Events
Abstract: This talk will provide an overview of multiple systems
estimation (i.e., multiple capture-recapture) by presenting the basic
capture-recapture model, outlining the assumptions of this model, and
discussing different modeling techniques for data for which these
assumptions are inappropriate. A portion of Exhibit 67 in the trial of
Slobodon Milosevic, mainly the analysis of ethnic Albanian deaths in
Kosovo between March and June of 1999, will be used as an example of these
modeling techniques.
Bio: Jana Asher received a Master's Degree in Statistics from Carnegie
Mellon University in 1999 and worked at the U.S. Census Bureau for the
next 18 months in the Small Area Income and Poverty Estimates Program
and the Planning, Research, and Evaluation Division. She returned to
Carnegie Mellon in August of 2000 to pursue a Ph.D. in Statistics under
the guidance of Steve Fienberg. Since then, she has worked on several
projects for the Science and Human Rights Program of the American
Association for the Advancement of Science, and she was recently a
co-author of a study that was presented as evidence by the prosecution in
the trial of Slobodan Milosevic at The Hague. Jana was honored over the
summer with a Special Achievement Award from the Social Statistics Section
of the American Statistical Association for her contributions to the
field, and she received the Edward C. Bryant Scholarship in August of this
year for outstanding work as a survey statistics graduate student.
Periodic Reporting of Post-licensure Safety Data to FDA by Pharmaceutical Firms:
Relation to "Datamining"
Bio: Dr. Miles Braun is the Director of the Division of Epidemiology at the
Center for Biologics Evaluation and Research. He has been with CBER
for seven years. The mission of the Division of Epidemiology is to
rapidly detect and rigorously research safety problems for licensed
biologic products and to facilitate regulatory, risk communication and
risk management strategies to mitigate these problems. Before coming
to FDA, Dr. Braun was Senior Research Investigator in the Epidemiology
and Biostatistics [intramural] Program at the National Cancer
Institute, NIH. He is a graduate of the Masters in Public Health
Program at John Hopkins and of the Preventive Medicine Residency
Program at the Centers for Disease Control, where he also served as an
Epidemic Intelligence Service Officer. He has worked in Public Health
at the local, state, federal and international levels. He has
authored and co-authored more than 60 scientific publications. He
currently represents FDA on post-marketing issues within the
International Conference on Harmonization (ICH) and on the MedDRA
Management Board. He has served as a member of subcommittees of the
Advisory Committee on Immunization Practices of the Centers for
Disease Control, and has presented to that body on the safety of the
anthrax vaccine. He is also a member of the Board of Directors of the
International Society of Pharmacoepidemiology and serves as FDA
liaison and steering committee member for the Agency for Healthcare
Research and Quality's Centers for Education and Research on
Therapeutics.
Some Problems and Challenges with Our Current Reporting Systems, Data
Sources and Approaches: Lessons from the HIV/AIDS Epidemic
Bio: Dr. Meade Morgan began his career in 1979 working for the CDC Hospital
Infections Program as a statistician for the national Study of the
Efficacy of Nosocomial Infection Control (SENIC) project. Several
years later he became involved with AIDS research as a consultant on
the statistical analyses of data related to the epidemiologic
investigations of the initial cluster of reported cases. In 1984 he
was selected as the Chief of the newly formed Statistics and Data
Management Branch in the AIDS Program within the CDC Division of Viral
Diseases. During his 16-year tenure with the AIDS Program, which
eventually became the Division of HIV/AIDS Prevention, he developed
the computerized information system that is still in use by state and
local health departments for surveillance of HIV and AIDS infection in
the United States. In 1986 he published one of the first statistical
models projecting the future course of the AIDS epidemic.
Dr. Morgan has supported international efforts to develop robust and
reliable information systems for HIV and AIDS surveillance and
research for over a decade. Most recently he has been working with
the GAP staff in India to create a computerized information system for
the care of HIV and TB patients in the Government Hospital of Thoracic
Medicine, near the city of Chennai.
Dr. Morgan received his bachelor of science degree in mathematics and
his doctorate in biometry and statistics from Emory University in
Atlanta.
Farzad Mostashari, Assistant Commissioner, Division of Epidemiology, NYC DOHMH
Syndromic Surveillance- The New York City Experience, with some Lessons from the National Syndromic Surveillance Conference
Bio: Dr. Mostashari's area of expertise is non-traditional disease
surveillance and outbreak detection. He did his graduate training at
the Harvard School of Public Health and Yale Medical School, internal
medicine residency at Mass General Hospital, and completed the CDC's
Epidemic Intelligence Service. He was a lead investigator in the
outbreaks of West Nile Virus and anthrax in NYC. He is a fellow of
the New York Academy of Medicine's Center for Urban Epidemiologic
Studies, a Clinical Assistant Professor at Weil Cornell Medical
College, and an Assistant Commissioner at the NYC Department of
Health. He served as Chair of the 2002 National Syndromic
Surveillance Conference.
The "Homeland Security - Public Health" Challenge:
Connecting and Integrating the Sources and the Players with the Applications
Abstract: "All phases of counterterrorism efforts require that large amounts of
information from many sources be acquired, integrated, and interpreted. Given
the range of data sources and data types, the volume of information each source
provides, and the difficulty of analyzing partial information from single
sources, the timely and insightful use of these inputs is very difficult. Thus,
information fusion and management techniques promise to play a central role in
the future prevention, detection, and remediation of terrorist acts. Unlike
some other sectors of national importance, information technology is a sector
in which the federal government has little leverage."
[From: Making the Nation Safer: The Role of Science and Technology in
Countering Terrorism (Summer 2002) Committee on Science and Technology for
Countering Terrorism, National Research Council
Complex and Interdependent Systems: A systems approach is especially necessary
for understanding the potential impacts of multiple attacks occurring
simultaneously, such as a chemical attack combined with a cyberattack on first
responder communications and designed to increase confusion and interfere with
the response. The required range of expertise is very broad. Information about
threats must come from communities knowledgeable about chemical, biological,
nuclear weapons, and information warfare, while vulnerability analysis will
depend on information about critical infrastructures such as the electric-power
grid, telecommunications, gas and oil, banking and finance, transportation,
water supply, public health services, emergency services, and other major
systems. Currently, there is a large volume of information collected and
analyzed by the U.S. intelligence community and in industry that is relevant to
assessing terrorist threats and system vulnerabilities. However, to maximize
the usefulness of these data and increase the ability to cross-reference and
analyze them efficiently, counterterrorism -related databases will have to be
identified and metadata standards for integrating diverse sets of data
established.
Bio: Dr. Kun is an Information technology consultant in the healthcare, public
health and scientific computing arenas. He graduated from the Merchant Marine
Academy in Uruguay, and holds a BSEE, MSEE and Ph.D. in Biomedical Engineering
degrees all from UCLA. He is the IEEE-USA MTPC, Chairman of the Bioterrorism
WG currently engaged in advising (on IT Infrastructure for Terrorism, on
E-Government, and Homeland / Cybersecurity) the US Congress and the Executive
Branch. He has an extensive background on Medical Informatics, which includes
14 years with IBM; Director of Medical Systems Technology and Strategic
Planning at Cedars-Sinai Medical Center in L A; Senior Information Technology
(IT) Advisor for the Agency for Health Care Policy and Research (AHCPR) and a
Distinguished Fellow at the CDC (Senior Computer Scientist for the Health Alert
Network and later the Acting Chief Information Technology Officer (CITO) for
the National Immunization Program (NIP)). As an adjunct faculty in the
Department of Biostatistics at the Rollins School of Public Health at Emory
University he wrote the syllabus and taught in the new curricula of Public
Health Informatics the following courses: Database Management Systems (Fall
2001) and Artificial Intelligence (Spring 2002).
From 1991 he was a Senior Scientist and an Adjunct Professor of Internal
Medicine at UTMB Galveston, School of Medicine, and since 1997 a Research
Professor of Medical Informatics and Information Technology at CIMIC / Rutgers
University in NJ where he is also a member of the Advisory Board. He is in the
Advisory Board for Children's Hospital at Harvard/MIT on their Bioterrorism
efforts and is a member of AMIA's: Bioterrorism Response Team, Public Policy
Committee and Chair of the Telehealth SIG. In the past 20 years Dr. Kun has
written a large number of articles and has lectured on medical and public
health informatics, IT and biomedical engineering in over 50 countries. Dr.
Kun is an elected Fellow of the American Institute for Medical and Biological
Engineering (AIMBE) and has been an invited speaker for the World Bank, the
Pan-American Health Organization, the World Health Organization, the European
Investment Bank and the Inter-American Development Bank.
Some highlights include: Formulated the IT vision for AHCPR (1996-97-98); Lead
staff for HPCC program and Telehealth (Chair Security, Privacy and
Confidentiality WG). DHHS Security of Health Data/Communications team for
HIPAA 1996. Co-author of the Reports to the Congress on Telemedicine and on
HIPAA Security.
July of 1997 invited speaker to the White House. Represented DHHS Secretary
Shalala at a Pan American Forum of Health Care Ministers in Mexico 1997. As
Acting CITO, formulated the future IT vision for the NIP at the CDC (10/2000).
1987-1993: IEEE Health Care Engineering Policy Committee (HCEPC) Chairman of
the Electronic Medical Record (EMR) and High Performance Computers and
Communications (HPCC) Subcommittee. Chosen in 1988 to be an expert witness to
Congress on the area of HPCC.
Overview: use of non-reported/administrative data for surveillance (ER data, pharmacy data, 911 call data, Harvard pilgrim, etc.)
Sean Hennessy, University of Pennsylvania
Pharmacoepidemiology: Goals and Methods
Abstract:
Pharmacoepidemiology represents the dynamic interface between clinical
pharmacology, pharmacotherapeutics, epidemiology and statistics. It is the
primary scienctific discipline underlying postmarketing drug surveillance
(PMS). PMS is an essential enterprise in ensuring the safety of the public.
This presentation will review the principal research methods used in
pharmacoepidemiologic studies in the context of a unifying conceptual
framework.
Bio:
Sean Hennessy, PharmD, PhD is an Assistant Professor of Epidemiology and
Pharmacology at the University of Pennsylvania School of Medicine.
Dr. Hennessy's primary field of interest is pharmacoepidemiology, which is
the study of the use and effects of medications in populations. Dr. Hennessy's
research in this area has been funded by the Agency for Healthcare Research
and Quality, the National Institutes of Health, pharmaceutical companies, and
private foundations. Examples of recently completed studies include venous
thromboembolism associated with 3rd generation oral contraceptives, cardiac
arrest associated with QT-prolonging antipsychotic drugs, and the
effectiveness of drug utilization review programs.
In addition to his research, Dr. Hennessy teaches clinical epidemiology to
medical and graduate students, and directs a clinical program at Penn
designed to improve outpatient medication use.
FDA's Adverse Event Reporting System and the Use of Quantitative Methods for Screening
Abstract: One of the major sources of information on adverse events associated
with marketed medical products is FDA's adverse event reporting
system. This system collects several hundred thousand reports per year
according to a structured format, though the quality of the data often
cannot be enforced as well as one would like. This talk will describe
the system, and various quantitative approaches to evaluating data,
associations, signals, suspicions, etc. that were developed or
considered over the years. Recently, data mining strategies have been
applied to the data base and some of these applications will be
discussed as well as a perspective on future enhancements [Anello and
O'Neill ; Chapter 'Postmarketing Surveillance of New Drugs and
Assessment of Risk', Encylopedia of Biostatistics, p 353-361;, John
Wiley, 2000.
Bio: Dr. O'Neill is the Director of the Office of Biostatistics (OB) in the
Center for Drug Evaluation and Research (CDER), Food and Drug
Administration. The OB comprises approximately 90 staff members, and
consists of three Divisions of Biometrics and the Quantitative Methods
and Research Staff. The Office provides biostatistical and scientific
computational support to all programs of CDER, including the
pre-market application review of clinical trials, of pre-clinical
animal carcinogenicity studies, of chemistry stability /expiration
setting studies, of experimental and observational studies in post
marketing safety assessment, of generic drug
bioequivalence/bioavailability studies; and IND advice on the design
and methodological issues associated with analysis of clinical trials,
and mathematical modeling in pharmacokinetics and pharmacodynamic
studies. Prior to October, 1998 he was Director of the Office of
Epidemiology and Biostatistics responsible for the post-market safety
surveillance of new drugs which deals with the receipt and analysis of
adverse event reports from health providers and the epidemiology
program which evaluates industry safety data and studies, and reviews
and designs observational studies to follow-up and evaluate drug
safety concerns.
Dr. O'Neill holds an A.B. degree in mathematics from the College of
the Holy Cross, and a Ph.D. in mathematical statistics and biometry
from Catholic University of America and began his FDA career in the
Division of Biometrics in 1971 as a statistical reviewer of New Drug
Applications in the Bureau of Drugs. He has held successively more
responsible positions in the former Division of Biometrics, including
Group Leader, Branch Chief, Deputy Director, and Director, a position
he held for ten years before assuming his role as Office Director.
In 1989-1990, Dr. O'Neill held a visiting professorship at the
Department of Research, University Medical School, Basel, Switzerland
where he developed and presented numerous lectures and created a
course series titled Topics in Therapy Evaluation and Review (TITER)
for European pharmaceutical scientists. This course became the basis
for the degree granting program European Course in Pharmaceutical
Medicine, a joint consortium between the University of Basel,
University of Freiburg, Germany and University of Strasbourg, France.
He has published articles in the biostatistical, epidemiology and
medical literature, is a fellow of the American Statistical
Association, a member of several professional societies and a past
Member of the Board of Directors of the Society for Clinical Trials.
Surveillance methods for birth defects and developmental
disabilities-understanding the limitations of different approaches
Bio: Coleen A. Boyle, Ph.D., M.S. - Associate Director for Science and
Public Health, National Center for Birth Defects and Developmental
Disabilities, Centers for Disease Control and Prevention, Atlanta, GA
Dr. Boyle received her MS in biostatistics and PhD in epidemiology
from the University of Pittsburgh School of Public Health and
completed postdoctoral training in epidemiologic methods at Yale
University. Dr. Boyle joined the Division of Birth Defects and
Developmental Disabilities, in 1988, first as Section Chief and later
as Branch Chief and Division Director. Her interest and expertise is
in the epidemiology and prevention of developmental disabilities,
including mental retardation, cerebral palsy, sensory impairments and
autism. Dr. Boyle has recently been appointed as the Associate
Director for Science and Public Health, for the newly formed National
Center on Birth Defects and Developmental Disabilities. She is the
recipient of the CDC Charles C. Shepard Award for scientific
excellence and has authored or coauthored more than 70 scientific
publications.
NEDSS in detail
Abstract:
The CDC's National Disease Surveillance System (NEDSS) is a nation-wide,
open-systems technology, standards-based, distributed architecture for the
collection, analysis and management of disease surveillance data. NEDSS
has a critical role to play in the nation's public health monitoring process
in general and in the monitoring for potential bioterrorism events. NEDSS
will be described from the perspectives of mission objectives, strategic
information architecture and tactical software engineering.
Bio:
Dr. Joseph A. Reid is the Associate Director For Science in the Information
Resources Management Office of the CDC. He has broad responsibilities in
the design and implementation of agency-level IT solutions at the CDC. Dr.
Reid is currently leading the technical implementation of the NEDSS system.
His other responsibilites include enterprise information security and IT
contract management.
Lab data? Clinical data? Over-the-counter data?
Abstract: Gil will discuss the processes and methods, as well as the challenges, barriers
and possibilities for clinical data collection, integration, and normalization
for use as a tool for disease surveillance, BioTerrorism detection, and adverse
events reporting. Following the discussion, Gil and Tim Ellis will provide a
live demonstration of the Health Data System designed specifically for clinical
data collection, normalization and de-identification.
Bio: Gil Delgado, Emergint's founder and CEO, has led teams of professionals
that have developed nationally recognized disease surveillance and research
systems for Universities, the U.S. Department of Defense and the Centers for
Disease Control and Prevention. He founded Emergint specifically to provide
the tools, technologies and services to support better clinical research and
disease surveillance. Prior to founding Emergint, Gil was instrumental in
building several Companies and Divisions, all supporting healthcare research.
Thomas Balzer, Quintiles/Verispan
Using Electronic Healthcare Reimbursement Claims to Detect Local,
Regional, and National Infectious Disease Outbreaks
(Joel R. Greenspan, MD; Thomas Balzer, PhD)
Abstract:
Background: Quintiles Transnational, Inc., collects a daily electronic
stream of standardized, real-time, de-identified, patient-centric
healthcare information from all parts of the U.S. Accumulating this data
flow since 1998 has yielded the world's largest and most complete data
warehouse of electronic healthcare information on >150 million unique
patients.
Methods: We used this data warehouse to detect the ``footprints'' of three
known infectious disease outbreaks investigated by CDC during 2001. The
outbreaks included a shigellosis outbreak in a large Midwestern city, a
sustained bacterial meningitis outbreak in a multi-county region, and a
national outbreak of histoplasmosis among American college students
returning from Mexico. We used both traditional approaches (specific
ICD-9 codes) and non-traditional approaches (ICD-9 codes for syndromes,
CPT codes for medical procedures, and NDC codes for prescriptions) to
assess the signals generated in the healthcare system by these outbreaks.
Results: All three outbreaks were detectable using the Quintiles data
warehouse.
The first data warehouse signal of unusual shigella activity in the target
city occurred on July 11, 2001, and the local health department could have
been notified as early as July 12. Using surveillance of enteric disease
syndromes (enteritis, infectious diarrhea, and diarrhea) among children
<10 years old yielded an initial signal that was both larger and
detectable earlier (by approximately 1 week) than signals from shigella
ICD-9 codes alone. Not only could syndromic surveillance have identified
the known shigella outbreak earlier, but this approach also detected two
additional large outbreaks of enteric illness in children in this
community during 2000 and 2001 that were previously unknown to the local
health department.
Quintiles detected a small cluster of meningococcal disease among persons
<30 years old in NE Ohio that occurred during the time of the known
outbreak. We also found a large unexpected signal generated by
meningococcal vaccinations among middle and high school students in the
same area. This suggests that surveillance of medical procedures can
complement the search for rare events such as meningococcal meningitis.
The Quintiles data yielded a bimodal epidemic curve of histoplasmosis
cases among persons ages 15 to 24 years during Spring 2001 in states
considered non-endemic for histoplasmosis. This pattern matched the
bimodal pattern of the known outbreak, and the location of cases matched
the location of known outbreak-related cases. We also found a much larger
and earlier signal generated by prescriptions for ketoconazole (a common
treatment for histoplasmosis) among persons 18 to 24 years in
histoplasmosis non-endemic states. This suggests that surveillance of
selected prescription drugs can augment traditional case finding and
outbreak detection methods especially for multi-state outbreaks.
Conclusion: Very large convenience samples of standardized electronic
healthcare claims data can augment traditional case finding and outbreak
detection methods for state and local health departments. Health
departments can use these data to greatly expand the scope of their
surveillance efforts for bioterrorism, other infectious disease outbreaks,
and other public health threats and emergencies. Further evaluation of
this approach at the local health department level is necessary to
document the usefulness of electronic healthcare claims for public health
purposes.
Bio: Dr. Balzer is the Senior Vice President and Chief Scientific Officer of
Verispan, LLC., a new informatics joint venture of Quintiles Transnational
and McKesson Corporation. He came to that role from Quintiles when the
Scott-Levin, SMG, Synergy, and Amaxis business units were merged with
McKesson's Kelly-Waldron unit to form Verispan. At Quintiles Informatics,
he had responsibility for Sales, Marketing, and Custom Solutions for
clients in the pharmaceutical and medical/surgical segments.
Prior to joining Quintiles in 2001, Dr. Balzer was the Senior VP,
Pharmaceutical Services of NDC Health, a leading provider of healthcare
information to the pharmaceutical industry. From 1992 - 1998 he was a
Manager and Principal with ZS Associates, a global consulting firm
specializing in pharmaceutical sales and marketing solutions. He led
strategic projects for customers in over 25 countries. Prior to his ZS
experience, he was a partner in a Salt Lake City-based consulting firm
serving the airline and public utility industries.
Dr. Balzer served for over 20 years in the US Army in a variety of command
and staff positions throughout the world, including command of a field
artillery unit in Vietnam. His final assignment was as Chief of
conventional analyses and wargaming for the Department of Defense at the
Pentagon and project manager for the simulations used to evaluate
scenarios throughout the world.
Dr. Balzer has a Ph.D. in Operations Research from the University of New
South Wales (Australia), a Master of Science from the University of
Southern California, an MBA from Central Michigan University, and a BA
with distinction from Park College.
The Bioterrorism Preparedness and Response Program, Early Aberration
Reporting System (EARS)
Bio: Lori Hutwagner, received her masters degree from the Georgia Institute
of Technology in 1989. She joined the CDC in 1990 with the National
Center for Infectious Diseases where she worked on aberration
detection methods for Salmonella isolates. She has recently completed
work with the Epidemiology Program Office where she applied aberration
detection methods to the Nationally Notifiable Disease Surveillance
System. In 1999 she began working with the Bioterrorism Preparedness
and Response Program on developing aberration detection methods for
their national ``drop in surveillance'' system and has started
implementing these methods in various local sites through the US.
Owen Devine, CDC
Bayesian Methods for Monitoring Public Health Surveillance Data
Abstract:
Using Bayesian methods to interpret maps of observed measures of disease
risk is becoming common, both as an approach to smooth these maps and to
develop etiologic hypotheses. Bayesian methods, however, are less frequently
used as a means of monitoring temporally referenced health surveillance
data. In this talk, I will review the applicability of these types of
approaches as tools for identification of aberrant events in spatially
and/or temporally referenced health surveillance data. In particular, I will
focus on the practicality of using this type of complex approach in ongoing
monitoring activities, identifying appropriate loss functions, and a
comparison with less complex frequentist approaches.
Bio: Owen Devine is Chief of the Statistics and Data Management Branch in CDC's
Division of STD Prevention. In this capacity, he has worked extensively on
the development and practical use of Bayesian and frequentist tools for
monitoring health surveillance data.
Martin Kulldorff, University of Connecticut
A Tree-Based Scan Statistic for Database Disease Surveillance,
(Authors: Martin Kulldorff, Zixing Fang, Stephen J Walsh)
Abstract: Many databases exist by which it is possible to study the
relationship between health events and various potential risk factors. Among
these databases, some have variables that naturally form a hierarchical tree
structure, such as pharmaceutical drugs and occupations. It is of great
interest to use such databases for surveillance purposes in order to detect
unsuspected relationships to disease risk. We propose a tree-based scan
statistic, by which the surveillance can be conducted with a minimum of prior
assumptions about the group of occupations/drugs that increase risk, and which
adjusts for the multiple testing inherent in the many potential combinations.
The method is illustrated using data from the National Center for Health
Statistics Multiple Cause of Death Database, looking at the relationship
between occupation and death from silicosis.
Methods for Capture-Recapture Estimates of the Number of Pertussis
Cases in New York State When Individuals Are Not Uniquely Identifiable
Authors: Philip J. Smith, PhD, Betsy Cadwell, MS; Andrew L. Baughman, PhD; Kristine M. Bisgard, MD.
Abstract:
Introduction: With the introduction and widespread use of a whole cell
pertussis-containing vaccine, pertussis cases declined to a historic
low in 1976. In the early 1980s the number of reported pertussis cases
began to increase. This increase raised questions about the
effectiveness of disease control programs. This paper describes
statistical methods for estimating number of pertussis
hospitalizations in New York State (NYS) during the years 1992-1995
using special capture-recapture methodology. These methods accounted
for the nonuniqueness of personal identifiers on administrative lists
available for the analysis.
Methods: Data obtained between 1992 and 1995 from the National
Electronic Telecommunications System for Surveillance (NETSS) and the
Health Care Information Association (HCIA) database were used to
identify individuals who had been hospitalized with
pertussis. Individuals on each database were identified and matched to
the other database according to their gender, state, year of illness,
and birth month/birth year pair. A mathematical formula was developed
for the capture-recapture estimator of the number of pertussis
hospitalizations that accounted for potential nonuniqueness of
individual identifiers. This estimator was found to require more
computational power than is currently available with a modern high
speed personal computer. A two-stage bootstrap procedure was developed
to simulate the estimator and its precision.
Results: There were 310 individuals on the NETSS database and 633
individuals on the HCIA database. On the NETSS database, there were
242 individuals that could have been matched to more than one
individual on the NCIA database. On the HCIA database there were 480
individuals that could potentially be matched to at least 1 person on
the NETSS database. The two-stage bootstrap procedure that accounts
for nonuniqueness of these matches yielded an estimate of 1,518
pertussis hospitalizations (95 percentile interval: [1,414, 1,634]) in
NYS.
Conclusion: Epidemiologic and demographic applications of the
capture-recapture method customarily devote considerable resources to
ascertaining exact matches from cases in available administrative
lists. Often, matches in these are putative, and made purposively to
deliberately obtain a conservative underestimate of the size of the
population of interest. Results from our study show that these ad hoc
procedures are unnecessary and that reasonable estimates can be
obtained that account for both uncertainty attributable to sampling
variation as well as uncertainty resulting from nonunique identifiers.
Bio: Philip J. Smith is a mathematical statistician in the National
Immunization Program at the Centers for Disease Control and Prevention
in Atlanta, Georgia.
Data mining methods: Applications, problems and opportunities in the public sector
Abstract: While data mining methods continue to evolve there continues
to be a broad spectrum of application and understanding of these
methods. The presenter will briefly cover some public sector data
access, transformation, distribution and mining applications in the
areas of disease and adverse event reporting and surveillance. Brief
attention will be given to problems encountered, creative problem
solving and future opportunities as well as efforts to standardize
data mining model deployment with Predictive Modeling Markup Language
(PMML).
Bio: John Stultz is part of the Public Sector Group of SAS working as a
Systems Engineer specializing in data mining. John has his Masters of
Public Health from Tulane University School of Public Health and
Tropical Medicine specializing in epidemiology. John has consulted
with various health care companies, universities, and public sector
entities including the Centers for Disease Control, the Centers for
Medicaid and Medicare Services, United States Army Research Institute
for Environmental Medicine, the Veteran's Administration, the Indian
Health Service, and the University of Colorado Health Sciences Center.
Datamining in the Vaccine Adverse Event Reporting System (VAERS) to Enhance Vaccine Safety Monitoring at the Food and Drug Administration (FDA)
(Robert Ball, Dale Burwen, M. Miles Braun, Center for Biologics Evaluation and Research, FDA, Rockville, MD)
Abstract:
Intro: VAERS is operated collaboratively by the FDA and the CDC to
monitor the safety of vaccines after licensure and receives 10 to 14
thousand reports per year. Passive surveillance systems such as VAERS
are subject to many limitations, notably under-reporting and the lack
of adequate denominator data to determine incidence rates. Because of
these limitations, it is usually not possible to determine causal
associations between vaccines and adverse events from VAERS reports.
The traditional approach to signal detection involves initial manual
screening of reports, followed by more in-depth review to identify
unexpected patterns in age, gender, dose number, and time to onset, or
substantial numbers of "positive rechallenge" reports. To improve the
efficiency of signal detection, the FDA VAERS group has been exploring
2 datamining techniques: a Bayesian method (Dumouchel) and
Proportional Reporting Ratios (PRR) (Evans).
Methods: The first stage of this exploration demonstrated that
retrospective application of the Bayesian method identified
intussusception as a notable adverse event after the introduction of
Rotavirus vaccine. Subsequently, we have tested a user-friendly
implementation of the Bayesian method and used PRR in routine
surveillance work.
Results: Several key concepts have been demonstrated through
exploratory analyses with these methods. Comparison of the observed
patterns of vaccine-event pairs for pneumococcal, meningococcal, and
influenza vaccines illustrate the ability of these methods to capture
in a graphical "snapshot" the differences in reported adverse events
after these vaccines. The influence of age and gender, and
potentially other variables, on the magnitude of the association and
ranking of vaccine-event pairs was demonstrated using anthrax vaccine.
Multi-dimensional associations such as the occurrence of two or three
particular symptoms following receipt of a vaccine were explored.
Challenges in interpretation and operationalization were
encountered.
Summary: Both methodological and practical issues have been
encountered that bear on the potential usefulness of datamining.
Methodological issues include proper application of each method,
understanding differences between the methods and their advantages and
disadvantages, and the use of datamining as an analytic tool vs. an
automated screening tool. Practical issues include the need for
personnel training, substantial computing resources, and integration
into the usual work process. Datamining methods hold promise to
improve the efficiency of vaccine safety surveillance, but numerous
methodological and practical issues need to be resolved before
datamining can fulfill that promise.
Dumouchel W. Bayesian data mining in large frequency tables, with an
application to the FDA spontaneous reporting system. American
Statistician 1999;53:177-190.
Evans SW, Waller PC, Davis S. Use of proportional reporting ratios for
signal generation from spontaneous adverse drug reaction
reports. Pharmacoepidemiol Drug Saf 2001;10:483-486.
Bio: Robert Ball is Chief of the Vaccine Safety Branch in the Office of
Biostatistics and Epidemiology, Center for Biologics Evaluation and
Research, FDA. Dr. Ball received his BS degree in Mathematics and MD
degree from Georgetown University. He completed his Internal Medicine
internship at the US Naval Hospital Bethesda and his MPH and residency
in Occupational and Environmental Medicine at the Uniformed Services
University of the Health Sciences. In addition, he received the ScM
degree in Infectious Disease Epidemiology and Vaccine Science and
Policy from Johns Hopkins School of Public Health. He is Board
Certified in Public Health and General Preventive Medicine and
Occupational Medicine.
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Document last modified on October 11, 2002.