[infowar.de] Interessant: Datamining and BWC Defense

[Georg Schoefbaenker <schoefbaenker -! - aon - at>]

Infowar.de, http://userpage.fu-berlin.de/~bendrath/liste.html
-------------------------------------------------------------

Werte KollegInnen,

interessant und kam mir in den letzten Wochen schon mehrfach unter, deshalb 
jetzt auch an diese liste: Ich erkenne einen Trend im Bereich B- und 
C-Waffenverteidigung zunehmend auf data-mining  zu setzen.

Gruß

GS

http://www.the-scientist.com/yr2002/apr/bunk_p14_020429.html

The Scientist 16[9]:14, Apr. 29, 2002
NEWS
Early Warning

U.S. scientists counter bioterrorism with new electronic sentinel systems
By Steve Bunk


Stung by anthrax mailings after suicide skyjackings, the United States is 
hurrying to erect an electronic line of defense against further 
bioterrorism. At least five sophisticated biosurveillance systems are under 
development with federal funding to nonprofit and to proprietary ventures; 
two other groups already have products on the market. The goal is to 
install a national sentinel network that can detect suspicious trends in 
medical data and in illness behavior before diagnosis, to help contain a 
disease by identifying it soon after infections begin. Called syndromic 
surveillance because it tracks signs and symptoms rather than positively 
diagnosed disease, this new technology will also accelerate containment of 
naturally occurring pathogens.

The data processed by these systems range from traditional patient charts 
to such nontraditional sources as Internet health site hits, 
over-the-counter drug sales, or absences from work and school. A major 
challenge is accurate analysis of the data, which can involve complex 
statistical methods, decision-making tools, and even artificial 
intelligence. But many questions remain to be fully answered, including: 
How much time between infection and medical treatment can be saved by these 
methods; what kinds of data are the best indicators of serious disease 
outbreak; and how well will the systems cope with the problem of raising 
false alarms?

"This was solidly a research field on Sept. 10 and was considered to be a 
standard technology on Sept. 12," says Kenneth D. Mandl, an assistant 
professor of pediatrics at Harvard Medical School and research director in 
the emergency medicine division at Children's Hospital, Boston. Mandl is 
coprincipal investigator of an academic consortium developing one of the 
new biosurveillance systems. "It's actually still a research field," he 
stresses. "We should not forget that a lot of the basic science behind it 
still needs testing."

The first product to reach the marketplace was LEADERS (Lightweight 
Epidemiology Advanced Detection and Emergency Response System), developed 
by a consortium that includes EYT, an information technology company in 
Chantilly, Va. LEADERS can interrogate patient records and compare chief 
complaints with those of selected syndromes, says EYT vice president Tim 
Hannon. The system gathers data primarily through continuous feeds from the 
client hospital's information system. Two other sources are electronic 
form-based data entered by clinicians and a "heightened surveillance" mode 
that can place added emphasis on new patient information to generate alerts 
during major crowd-drawing events.

Another for-profit venture, headed by Veridian Corp. of Arlington, Va., 
will feature artificial intelligence being developed by Mark A. Musen and 
colleagues in Stanford University School of Medicine's medical informatics 
division. Veridian program manager Gene McClellan says the prototype 
system, RPHD (Real-time Population Health Detector), is due for testing 
later this year. It will routinely acquire diagnostic tests ordered, deduce 
possible reasons for them, evaluate the physician's hypothesis, and derive 
an abstraction of such information to place the patient in a syndromic 
category. The system will integrate relevant data from various patients 
during a given period. When an unusual-looking pattern emerges, the 
likelihood of an outbreak or attack can be calculated by algorithmic 
comparison of the anomalies to normal population health standards.

"No one has a magic approach to the issue of false alarms," McClellan 
allows. He adds that the consortium is continuing to cultivate multiple 
data sources in an attempt to conquer the signal-to-noise problem.

Flu Complicates Detection

Part of the reason for this problem is that many deliberately released 
pathogens?as well as others that occur naturally?manifest as flu-like 
symptoms. They can be difficult to differentiate in their early stages, not 
only from each other but from influenza itself. How to detect an upper 
respiratory infection that's not merely a runny nose is essentially a 
question of signal-to-noise. Although the new systems are expected to 
outperform traditional health surveillance methods, there is debate over 
whether signals from multiple data streams will improve detection or merely 
increase the noise.

Senior scientist Al Zelicoff at the Center for National Security and Arms 
Control of Sandia National Laboratories in Albuquerque, N. Mex., argues 
that no evidence has yet been compiled to show that nontraditional data 
streams will be useful or collectible in real time. Formerly a 
rheumatologist, Zelicoff masterminded RSVP (Rapid Syndrome Validation 
Project), which was jointly developed through Sandia, Los Alamos National 
Laboratory, the University of New Mexico, and the New Mexico Department of 
Health.1 The latter three collaborators have broken away from Sandia to 
work on their own biosurveillance product, citing discontent with RSVP's 
limited data stream and with Sandia's decision to proprietarily market the 
system.

Zelicoff is placing RSVP in groups of hospital emergency rooms in states 
across the United States and in Singapore. He dismisses the proprietary 
issue as a red herring. The question, he says, is not whether 
biosurveillance is offered under a potentially profit-making arrangement 
but whether the software will interconnect with other systems. (RSVP and 
most of the other new systems are striving for compatibility.) Zelicoff 
adds that the decision to become proprietary was based on a need to get the 
system quickly onto the market. "My fear is that someone is going to put a 
bad product out there," he explains. The health care industry won't give 
such technologies more than one chance to prove themselves, he believes.

RSVP relies on Web-based reporting by physicians of new cases that fit into 
any of six syndromes related to naturally occurring or deliberately caused 
disease, especially influenza-like illnesses. But physicians are 
notoriously bad about reporting diseases, because the current system is 
paper-bound and bureaucratic, he says. He offers a rule of thumb for any 
reporting software: "It had better be easy, cheap, fast, intuitive and, oh, 
by the way, give the doctors something back within their attention span, 
which is about two minutes."

The system gives links to geographically based information about disease 
outbreaks throughout the world, and provides details on local and regional 
health conditions. The physician enters demographic data that includes age 
range and zip code but there is no patient name or identifier number. After 
hitting a series of tabs that indicate symptoms and signs, the doctor gets 
a best-guess analysis of the case, in text and graphs, based on local 
conditions. A map tells of similar local reports in the past 30 days and 
another map offers current, comparative epidemiological information on the 
six syndromes.

"This is the Holy Grail of epidemiology: geographically based analysis of 
signs and symptoms in the population," Zelicoff declares. He adds that by 
relying on the expertise of local physicians, "We make the signal as high 
as we can and keep the noise down."

RSVP's former collaborators have different ideas about that. The system 
they're developing, called B-SAFER (Bio-Surveillance Analysis, Feedback, 
Evaluation, and Response), will integrate nontraditional data streams into 
the RSVP data such as calls to the nurse strife line, emergency room, and 
poison center. Illness behavior begins before people go to the hospital, 
comments Judith C. Brillman, associate professor of emergency medicine in 
the University of New Mexico's Health Sciences Center. Detection could be 
days or even weeks faster, she says.

A prototype of B-SAFER, set to be completed by the end of September, will 
show a photo of a person. Clinicians can click on an organ or system to get 
a pop-up menu for entering data, allowing them to report signs and symptoms 
without selecting a syndrome. "It gives all the syndromic information but 
doesn't make anybody define anything on the front end," Brillman explains. 
One response to the clinician's data will be a differential diagnosis, 
based on an analysis of the heterogeneous data.

More Systems Developing

Other systems in development that will use nontraditional data streams 
include RODS (Realtime Outbreak Detection System), led by Michael Wagner of 
the University of Pittsburgh School of Medicine's center for biomedical 
informatics, and ESSENCE II (Electronic Surveillance System for the Early 
Notification of Community-Based Epidemics), led by Joseph S. Lombardo of 
the Johns Hopkins University applied physics laboratory. Both men declined 
to be interviewed.

At Boston's Children's Hospital, Mandl and colleagues are not currently 
incorporating nontraditional data into their system, which is provisionally 
called Biosurv. It is being tested at the hospital and by another 
consortium member, Beth Israel Deaconess Hospital. The next step is to 
extend it to nine other Massachusetts hospitals, Mandl reveals.

Biosurv, which has a focus on pediatric health, works in several modes, 
including automated surveillance of ER data. Initial patient complaints and 
hospital billing diagnosis codes are used. Mandl affirms that the main 
difficulty is to understand what the data signify. Children's Hospital 
alone gets 50,000 visits annually, he notes. "To say whether you're having 
an abnormal or a normal day is not a trivial determination." Accordingly, 
the team is geographically modeling data spanning a decade to determine norms.

"I think you'll find that syndromic surveillance will be tying into 
practical applications in at least 50 different systems, one for each 
state," he predicts. That could happen within the next two or three years, 
he adds. "The problem is, how will the regional data be interfaced at the 
national level? I haven't heard the solution to that yet."
Steve Bunk

1. A. Zelicoff et al., "The Rapid Syndrome Validation Project (RSVP)," 
Journal of the American Medical Inform atics Association, 
(Suppl.):S771-S775, 2001.


Web Links
    * RSVP demo: <http://www.the-scientist.com/yr2002/ap 
r/bunk_p14_020429.html 'http://rsvp.sandia.gov/snl'>rsvp.sandia.gov/SNL
    * B-SAFER demo: <http://www.the-scientist.com/yr2002/ap 
r/bunk_p14_020429.html 'http://openemed.net'>openemed.net
    * RODS home page <http://www.the-scientist.com/yr2002/ap 
r/bunk_p14_020429.html 
'http://www.health.pitt.edu/rods'>www.health.pitt.edu/rods



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