Assessing the added value of linking electronic health records to improve the prediction of self-reported COVID-19 testing and diagnosis
Clark-Boucher D, Boss J, Salvatore M, Smith J, Fritsche L, Mukherjee B. Assessing the added value of linking electronic health records to improve the prediction of self-reported COVID-19 testing and diagnosis. PLOS ONE 2022, 17: e0269017. PMID: 35877617, PMCID: PMC9312965, DOI: 10.1371/journal.pone.0269017.Peer-Reviewed Original ResearchConceptsElectronic health recordsHealth recordsCOVID-19-related outcomesCOVID-19 testingSurvey respondentsSelf-reported outcomesSelf-reported dataCOVID-19 outcomesElectronic recordsSurvey dataCOVID-19Prediction modelModel contextSurveyCOVID-19 diagnosisOutcomesPredictor variablesDigital surveyData sourcesCoronavirus disease 2019RespondentsPredictorsCOVID-19 casesDiagnosisRecords