TABLE 1—

Possible Sources and Utility of Health Indicator Surveillance Data

Type of Data	Data Source	Pros	Cons and Confounders
Typical health surveillance	Reportable diseases	Specificity of diagnoses; limited to diseases of interest	Relies on passive reporting; limited to specific diseases—may not detect new emerging infections; not timely
	Laboratory-based surveillance	Specificity of diagnoses	Often relies on passive reporting; may be limited to specific diseases; not timely
	Specific disease surveillance (e.g., influenza)	Follow trends for specific diseases	Limited to the disease in question; not timely
Existing health data not normally used for surveillance	Diagnostic information for inpatients and outpatients	Reflects incidence of disease in general population	Nonspecific—may be difficult to document definitive information; may not be accurate
	Intensive care unit admissions	Best indicator of rare events (e.g., West Nile virus)	Will not capture milder cases
	Prescription and over-the-counter pharmacy sales	Reflects symptomatology most broadly	Subject to promotions/sales; nonspecific
	Clinical laboratory submissions	Ordered by clinicians; reflects illness patterns	May not be ordered for all (or most) patients
	Medicare or Medicaid claims	Ease of data capture	Problems with timeliness and accuracy; not broadly representative
	Acute diagnoses in nursing home populations	Reported by medical personnel; immobile population with limited exposure possibilities	Immobility reduces exposure potential; not broadly representative; may not be automated
	Ambulance call chief complaints	Many communities with timely access to data	Nonspecific
	Radiology test ordering and results	Ordered by clinicians; may reflect working diagnosis	Not ordered for all (or most) patients; multiple reasons for radiological tests
	Poison information calls	Timeliness	May not be related to infectious diseases
	Medical advice call-in	Occurs very early in disease outbreak	May be difficult to categorize
	Emergency room use	Ease of calculation	Does not reflect accurate cause of increased patient visits
	Internet hits for medical information	Large database with relatively easy access to information	May be difficult to determine geographic location
	Medical examiner/mortality surveillance	May capture severe diseases	Not timely
Non–health data sources	Road and transit usage	Captures many segments of the population	Changes may be difficult to interpret
	Entertainment venue usage	May reflect behavior early in illness	May be difficult to collect data; may not reflect expected behavior patterns of ill people
	Weather data	Usually readily available	May not be associated with illness patterns
	Vector data	Allows knowledge of potential for spread of vector-borne diseases	May not be associated with illness patterns
	School and work absenteeism	May occur earlier than visits to clinician	May be absent for nonmedical reasons; data often not automated