Instructions: FOR EACH PATIENT SEEN AT THE EMERGENCY DEPARTMENT
1. Stamp form at top left with patient imprint card
2. Triage/registration and health care provider fill out respective sections
3. Place in drop box
Triage/Registration Complete This Section
Date of visit: f Age:
Home Zip Code:
For ¿ige (ess titan one year plââsc use "1"
Was patient in southern Manhattan (below Canal St) on Tuesday, September 11th after the attack? (cirde one) YES NO Don't Know
Health Care Provider Complete This Section
Please check the ONE PREDOMINANT syndrome from the following list that best represents the PRIMARY condition of the patient
□ None of the following
□ Smoke or dust inhalation
□ Exacerbation of underlying respiratory condition (Asthma/ COPD)
□ Anxiety reaction (including somatic complaints, insomnia)
□ Diarrhea / gastroenteritis (including vomiting or abdominal cramps)
□ Upper or lower respiratory infection WITH fever
□ Sepsis or non-traumatic shock
□ Rash WTTH fever (do NOT check unless both are present)
□ Meningitis, encephalitis, or unexplained acute encephalopathy
□ Botulism-tike syndrome (cranial nerve impairment and weakness)
□ Unexplained death with a history of fever
IF YOU HAVE ANY QUESTIONS OK MEED TO REACH THE NYC DEPARTMEOT OF HEALTH, PLEASE CALL 213^-17-2676 AMD ASK FOR THE DOCTOR ON DUTY. IF NO ONE IS AVAILABLE AT THAT NUMBER, CALL THE POISON CONTROL CENTER AT 212-761-7667.
FIGURE 3.4 Drop-in surveillance form used in September and October 2001 Hygiene, New York, NY.)
screening in a focused manner (e.g., screening of all staff in a hospital), or it may deploy screening on a wide-scale basis. The scope of the screening effort depends on the nature of the outbreak. An outbreak of meningococcal disease in a hospital wing may require screening of only a few staff to find the person harboring the bacteria in their throat or nose.
in New York City. (From the New York City Department of Health and Mental
A disease such as SARS may warrant screening of tens of thousands of people.
During the SARS outbreak of 2003, many countries screened arriving and departing air travelers by using infrared thermal imaging devices in airports tuned to detect people with fevers (Figure 3.5). Similarly, hospitals and healthcare
facilities used thermometers and questionnaires to screen people who wished to enter the facility, referring individuals with fever and respiratory illness to an isolation facility for more detailed screening. In Singapore, the government issued an electronic thermometer to every schoolchild; the child then measured his or her own temperature at school in the morning and afternoon.
As a result of the ever-expanding use of computers to collect and store clinical information, it has become possible for computers to detect cases by analyzing these data. Evans and colleagues (Evans, 1991; Evans et al., 1985,1986,1992,1998) used computers to detect patients with infectious diseases in hospitals. Khan et al. (1993,1995) demonstrated methods for automatic case finding for hospital infection control, and Jain et al. (1996) developed a tuberculosis case detector. Many organizations are creating electronic laboratory reporting systems, which automate case detection by laboratories (Effler et al., 1999; Overhage et al., 2001; Panackal et al., 2001; Hoffman et al., 2003).
Computerized case detection is most widely used at present, however, for detecting syndromes (DoD-GEIS, 2000; Lazarus et al., 2001; Lewis et al., 2002; Gesteland et al., 2003; Lombardo et al., 2003; Platt et al., 2003; Tsui et al., 2003, Espino et al., 2004; Heffernan et al., 2004; Nordin et al., 2004;Wagner et al., 2004; Yih et al., 2004; Chapman et al., 2005). A syndrome is an early presentation of illness. Almost all infectious diseases present initially as one of a small number of syndromes. Current computer-based case detection systems monitor for diarrhea, respiratory, influenza-like, rash, hemorrhagic, and paralytic syndromes.
In part, computers are widely used for detecting syndromes because of technical feasibility. Virtually all hospitals elicit a chief complaint from patients at the time that they register for service. The hospitals collect this information electronically and can provide it to a biosurveillance organization in a relatively uniform format.
Many of the above systems use techniques developed by the field of artificial intelligence to detect cases of disease (Cooper, 1989). We discuss these techniques in detail in Chapter 13.
We use the term diagnostic precision to refer to the nosological specificity of a diagnosis. For example, a physician may formulate (correctly) a relatively imprecise diagnosis of "pneumonia'' after initial evaluation of a patient; subsequently, the physician may establish a more precise diagnosis of tuberculosis based on the results of laboratory testing. Diagnostic precision is not to be confused with diagnostic accuracy, which speaking loosely refers to whether the doctor was "right.''
The range of diagnostic precision in medical practice (and biosurveillance) ranges from the very imprecise ("patient or animal is sick or dead'') through intermediate levels of precision ("patient has respiratory illness with fever''), through organism-level diagnostic precision ("patient has Mycobacterium tuberculosis"), to the ultimate level, which is quite precise ("patient has M. tuberculosis, Beijing genotype,strain W'').As we all know from personal experience with the healthcare system, there may be considerable imprecision early in the course of a diagnostic workup about the diagnosis (and even at its conclusion). In general, the level of diagnostic precision improves over time as results of diagnostic tests become available.
For many decisions about the treatment of individual patients (e.g., surgery), the precision of diagnosis must be relatively high. In biosurveillance, however, the diagnostic precision of case detection can be lower—even as low as "sick'' or "dead.'' As with medical care, the more diagnostic precision the better, although increased precision comes not only at the cost of further testing but also at a time cost due to the delay involved in waiting for results of the testing.2
The value of extremely precise case detection is that it can support detection of small or geographically diffuse outbreaks. Pulse-field gel electrophoresis (PFGE) of common pathogens now routinely matches outbreak victims separated by time and place. An outbreak that was not detected by any other method was a 2000 listeriosis outbreak: eight perinatal (three miscarriages/stillbirths) and 21 nonperinatal (median age 65) cases distributed over 10 states and seven months were only linked because of identical PFGE (PulseNet pattern numbers GX6A16.0014 by Asc1 and GX6A12.0017 by Apa1) and ribotyping (DUP-1053). A case-control study of 17 of the cases evaluating food eaten in the 30 days before illness found an association with consumption of a specific brand of deli turkey (CDC, 2000c).
The CDC National Food Borne Pathogen System serotypes every enteric isolate received to achieve the ultimate in diagnostic precision and the ability to detect very diffuse outbreaks in a nation with a population of 350 million (discussed in Chapters 5, 8).
We discuss the relationship between diagnostic precision and detectability—the smallest outbreak that a biosurveillance system can detect—later in this chapter and again in Chapter 20.
Health departments investigate individual cases of notifiable diseases for four reasons: (1) to confirm that the case meets the case definition, (2) to determine whether there are environmental or other causes of the illness that can be remediated, (3) to identify other people who may have been exposed for antibiotic prophylaxis or vaccination, and (4) to educate or isolate communicable individuals so that their infection is not transmitted to others. When resources do not allow a case investigation on every notifiable disease, a health department must decide which reported diseases to investigate. Some investigations are so important (sexually transmitted diseases, tuberculosis) that the federal government provides substantial resources to health departments to ensure that sufficient resources are available for investigation.
The investigator may use CDC disease-specific reporting forms, department-generated interview forms, or computer-generated dynamic questionnaires to collect additional disease specific information from clinicians, infection control nurses, and/or patients. The questions explore the more common sources and exposures for the disease. If appropriate, the investigator contacts exposed individuals to provide information, screening, medication, and/or vaccination as appropriate to the disease and circumstances of exposure. Case investigations of notifiable diseases are an example of the feedback loop in Figure 1.1. If an outbreak is identified as a result of the case (or the analysis of subsequent cases), the case data already collected provide investigators a base of information for characterizing the outbreak.
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