2018
Analysis of treatment pathways for three chronic diseases using OMOP CDM
Zhang X, Wang L, Miao S, Xu H, Yin Y, Zhu Y, Dai Z, Shan T, Jing S, Wang J, Zhang X, Huang Z, Wang Z, Guo J, Liu Y. Analysis of treatment pathways for three chronic diseases using OMOP CDM. Journal Of Medical Systems 2018, 42: 260. PMID: 30421323, PMCID: PMC6244882, DOI: 10.1007/s10916-018-1076-5.Peer-Reviewed Original ResearchConceptsTreatment pathwaysChronic diseasesStudy of drugsClinical data repositoryClinical treatmentDifferent medical institutionsProportion of monotherapyFirst-line medicationMedical institutionsFirst Affiliated HospitalType 2 diabetesNanjing Medical UniversityDifferent treatment pathwaysMost patientsCommon medicationsAffiliated HospitalMedicationsNational guidelinesMedication informationLocal hospitalMedical UniversitySame diseaseDiseasePatientsNew drugs
2017
Evaluating the role of race and medication in protection of uterine fibroids by type 2 diabetes exposure
Velez Edwards D, Hartmann K, Wellons M, Shah A, Xu H, Edwards T. Evaluating the role of race and medication in protection of uterine fibroids by type 2 diabetes exposure. BMC Women's Health 2017, 17: 28. PMID: 28399866, PMCID: PMC5387248, DOI: 10.1186/s12905-017-0386-y.Peer-Reviewed Original ResearchConceptsT2D medicationsUF riskAnnual healthcare costsElectronic medical record algorithmCase-control studyLarge clinical populationFurther mechanistic researchBackgroundUterine fibroidsT2D diagnosisDiabetes exposureMedication typeDiabetes presenceInsulin usersUterine fibroidsInsulin treatmentProtective associationStratified analysisClinical cohortConclusionsThese dataProtective effectLarge cohortCase-control statusHealthcare costsT2DMedications
2013
Development of an ensemble resource linking MEDications to their Indications (MEDI).
Wei W, Cronin R, Xu H, Lasko T, Bastarache L, Denny J. Development of an ensemble resource linking MEDications to their Indications (MEDI). AMIA Joint Summits On Translational Science Proceedings 2013, 2013: 172. PMID: 24303333.Peer-Reviewed Original Research
2012
Optimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping
Schildcrout J, Denny J, Bowton E, Gregg W, Pulley J, Basford M, Cowan J, Xu H, Ramirez A, Crawford D, Ritchie M, Peterson J, Masys D, Wilke R, Roden D. Optimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping. Clinical Pharmacology & Therapeutics 2012, 92: 235-242. PMID: 22739144, PMCID: PMC3785311, DOI: 10.1038/clpt.2012.66.Peer-Reviewed Original ResearchConceptsVanderbilt University Medical CenterAdverse eventsPreemptive genotypingPotential adverse eventsUniversity Medical CenterHome patientsPharmacogenetic associationsMedical CenterVariant allelesMedicationsDrug outcomesPatient safetyDrug decision makingRelevant genetic variantsRoutine integrationTarget drugsGenetic variantsOutcomesFrequency of opportunitiesGenotypingSafetyPrescribingPatientsCohortPharmacogenetics
2010
An automated approach to calculating the daily dose of tacrolimus in electronic health records.
Xu H, Doan S, Birdwell K, Cowan J, Vincz A, Haas D, Basford M, Denny J. An automated approach to calculating the daily dose of tacrolimus in electronic health records. AMIA Joint Summits On Translational Science Proceedings 2010, 2010: 71-5. PMID: 21347153, PMCID: PMC3041548.Peer-Reviewed Original ResearchElectronic health recordsUnstructured clinical dataNatural language processingHealth recordsTime-consuming taskUnstructured formatClinical textLanguage processingAutomated ApproachDaily doseData setsTest casesDetailed drug informationDrug mentionsDaily dosesClinical dataMedication informationClinical researchMedication namesDrug informationInformationTacrolimusMedicationsDoseTask