tetano
Editor, Senior Moderator
Can J Public Health. 2012 Jan-Feb;103(1):69-75.
A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients.
Barbara AM, Loeb M, Dolovich L, Brazil K, Russell ML.
Source
Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON. barbara@mcmaster.ca
Abstract
OBJECTIVE:
Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza.
METHODS:
Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions.
RESULTS:
Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values.
DISCUSSION:
The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance.
PMID:
22338332
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/22338332
A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients.
Barbara AM, Loeb M, Dolovich L, Brazil K, Russell ML.
Source
Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON. barbara@mcmaster.ca
Abstract
OBJECTIVE:
Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza.
METHODS:
Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions.
RESULTS:
Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values.
DISCUSSION:
The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance.
PMID:
22338332
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/22338332