title: Linked analysis for definition of nurse advice line syndrome groups, and comparison to encounters.
abstract: BACKGROUND
  Nurse advice call centers are a potentially important source of data for syndromic surveillance purposes. For this reason, researchers at Johns Hopkins University Applied Physics Laboratory and Kaiser Permanente of the Mid-Atlantic States (KPMAS) have been collaborating to develop methods to use this data within the ESSENCE II Syndromic Surveillance System in the National Capital Region.
  
  
  OBJECTIVE
  The objective of this report is to present a general method for finding syndrome groups in data sources that can be linked to physician encounters and to determine effective advice call syndrome groups for use with KPMAS advice data.
  
  
  METHODS
  Advice calls are linked to physician encounters and stratified by patient age. They are placed in groups according to a maximum positive predictive value criterion. The groups are evaluated by correlating the resulting syndrome time series against physician encounter data.
  
  
  RESULTS
  Potentially useful advice syndrome groups are found for respiratory, lower gastrointestinal (GI), and total GI syndromes for each age stratum.
  
  
  CONCLUSIONS
  The time series of the advice data for respiratory, lower GI, and upper GI syndromes accurately predict the physician encounter time series for the corresponding syndromes for each age stratum.
authors.affiliation: Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland 20723-6099, USA. steve.magruder@jhuapl.edu
authors.forename: Steven F
authors.initials: SF
authors.lastname: Magruder
authors.forename: J
authors.initials: J
authors.lastname: Henry
authors.forename: M
authors.initials: M
authors.lastname: Snyde
mesh_terms: D003953:Diagnosis-Related Groups; D004196:Disease Outbreaks / Q000517:prevention & control*; D015277:Hotlines; D006801:Humans; D015233:Models, Statistical; D009729:Nursing; D011159:Population Surveillance; D011237:Predictive Value of Tests; D040442:Public Health Informatics; D013689:Telephone