<p>We evaluated the comparability of influenza-related events self-reported by research participants and their outpatient medical records using data collected from the Hutterite Influenza Prevention Trial. We also explored the implications of using data on influenza symptoms from both data sources, independently and in combination, as predictors of laboratory-confirmed influenza. Self-report of influenza symptoms, physician-diagnosed otitis media and antibiotics prescribed at outpatient consultations was collected from trial participants. Similar data were also collected by fax requests for medical record information to the medical facilities. We found lower rates of self-reported prevalence for fever, sore throat, earache and otitis media and higher rates of antibiotic prescriptions compared to the medical records. Total agreements between self-report and medical report of symptoms varied between 61% and 88%. Negative agreement was considerably higher than positive agreement for each symptom, except cough. Self report of otitis media was a very specific measure (93%), but had lower sensitivity (47%). Positive predictive value was moderate at 64% but negative predictive value was good at 86%. Self-reported antibiotic prescription was a highly sensitive measure (98%), but had low specificity (50%). Positive predictive value was high at 91% but negative predictive value was modest at 65%. Fever (on its own) and combined with cough and/or sore throat were highly correlated with laboratory-confirmed influenza for all data sources. The ILI surveillance definition of fever and sore throat, based on combined symptoms by both medical records and self report, was the best predictor laboratory confirmed influenza.</p> / Doctor of Philosophy (PhD)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/9931 |
Date | 10 1900 |
Creators | Barbara, Angela M. |
Contributors | Loeb, Mark B., Dolovich, Lisa, Brazil, Kevin, Health Research Methodology |
Source Sets | McMaster University |
Detected Language | English |
Type | dissertation |
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