Syndrome

An expanded ambulatory health record, the Comprehensive Ambulatory Patient Encounter Record (CAPER) will provide multiple types of data for use in DoD ESSENCE. A new type of data not previously available is the Reason for Visit (ROV), a free-text field analogous to the Chief Complaint (CC). Intake personnel ask patients why they have come to the clinic and record their responses. Traditionally, the text should reflect the patient's actual statement. In reality the staff often "translates" the statement and adds jargon. Text parsing maps key words or phrases to specific syndromes. Challenges exist given the vagaries of the English language and local idiomatic usage. Still, CC analysis by text parsing has been successful in civilian settings [1]. However, it was necessary to modify the parsing to reflect the characteristics of CAPER data and of the covered population. For example, consider the Shock/Coma syndrome. Loss of consciousness is relatively common in military settings due to prolonged standing, exertion in hot weather with dehydration, etc., whereas the main concern is shock/coma due to infectious causes. To reduce false positive mappings the parser now excludes terms such as syncope, fainting, electric shock, road march, parade formation, immunization, blood draw, diabetes, hypoglycemic, etc.

Objective

Rather than rely on diagnostic codes as the core data source for alert detection, this project sought to develop a Chief Complaint (CC) text parser to use in the U.S. Department of Defense (DoD) version of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE), thereby providing an alternate evidence source. A secondary objective was to compare the diagnostic and CC data sources for complementarity.

Particularly in resource-poor settings, syndromic surveillance has been proposed as a feasible solution to the challenges in meeting the new disease surveillance requirements included in the World Health Organization's International Health Regulations (2005).

Objective

The aim of this study is to demonstrate how syndromic surveillance systems are working in low-resource settings while identifying the key best practices and considerations.

This project was established through the Border Infectious Disease Surveillance (BIDS) program in Arizona (AZ) to monitor infecting respiratory pathogens among hospitalized patients with Severe Acute Respiratory Infections (SARI) in the AZ border region from September 2010 to the present.

Objective

To present the epidemiology, clinical aspects, and laboratory results of AZ SARI case patients and to describe respiratory viruses in the AZ border region.

Electronic  Health  Record  (EHR)  data  offers  the  researcher a potentially rich source of data for tracking disease  syndromes. Procedures  performed  on  the  patient, medications prescribed (not necessarily filled by  the  patient),  and  reason  for  visit  are  just  some  characteristics of the patient encounter that are available  through  an  EHR  that  can  be  used  to  define  surveillance  syndromes.    Since  procedures  have  not  been used frequently in defining syndromes, encounter  level  procedures  data,  extracted  from  the  EHR  of  a   large   local   primary   care   practice   with   about   200,000 patient encounters per year was used to identify  procedures  associated  with  an  established  respiratory syndrome.

Objective

To investigate the utility of different sources of patient encounter information, particularly in the primary care setting, that can be used to characterize surveillance syndromes, such as respiratory or flu.