2022
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
2021
Endometriosis and menopausal hormone therapy impact the hysterectomy-ovarian cancer association
Khoja L, Weber RP, Group T, Webb PM, Jordan SJ, Muthukumar A, Chang-Claude J, Fortner RT, Jensen A, Kjaer SK, Risch H, Doherty JA, Harris HR, Goodman MT, Modugno F, Moysich K, Berchuck A, Schildkraut JM, Cramer D, Terry KL, Anton-Culver H, Ziogas A, Phung MT, Hanley GE, Wu AH, Mukherjee B, McLean K, Cho K, Pike MC, Pearce CL, Lee AW. Endometriosis and menopausal hormone therapy impact the hysterectomy-ovarian cancer association. Gynecologic Oncology 2021, 164: 195-201. PMID: 34776242, PMCID: PMC9444325, DOI: 10.1016/j.ygyno.2021.10.088.Peer-Reviewed Original ResearchConceptsHistory of endometriosisOvarian cancer riskEPT useOvarian Cancer Association ConsortiumOvarian cancerInverse associationOdds ratioCancer riskCancer associationInvasive epithelial ovarian cancerHormone therapy useMenopausal hormone therapyEpithelial ovarian cancerCase-control studyConfidence intervalsSlight inverse associationWarrants further investigationHormone therapyTherapy usePooled analysisEndometriosisHysterectomyCancerTherapySelf-reported data
2012
Hypertension: Development of a prediction model to adjust self-reported hypertension prevalence at the community level
Mentz G, Schulz A, Mukherjee B, Ragunathan T, Perkins D, Israel B. Hypertension: Development of a prediction model to adjust self-reported hypertension prevalence at the community level. BMC Health Services Research 2012, 12: 312. PMID: 22967264, PMCID: PMC3483283, DOI: 10.1186/1472-6963-12-312.Peer-Reviewed Original ResearchConceptsHealthy Environments PartnershipSelf-reported hypertension prevalenceEstimates of hypertension prevalenceSelf-reported dataHypertension prevalenceNHANES sampleUrban sampleNational Health and Nutrition ExaminationSelf-reportAssessment of population healthPopulation-based interventionsSelf-reported hypertensionUnderreporting of hypertensionEstimates of hypertensionAccuracy of self-reported dataHealth care programsPrevalence of hypertensionMethodsWe analyzed dataPopulation level estimatesModerate to goodSelf-reported survey dataEthnically diverse urban samplePopulation healthCare programNutrition Examination