2022
Simplified Machine Learning Models Can Accurately Identify High-Need High-Cost Patients With Inflammatory Bowel Disease
Nguyen N, Patel S, Gabunilas J, Qian A, Cecil A, Jairath V, Sandborn W, Ohno-Machado L, Chen P, Singh S. Simplified Machine Learning Models Can Accurately Identify High-Need High-Cost Patients With Inflammatory Bowel Disease. Clinical And Translational Gastroenterology 2022, 13: e00507. PMID: 35905414, PMCID: PMC10476830, DOI: 10.14309/ctg.0000000000000507.Peer-Reviewed Original ResearchConceptsInflammatory bowel diseaseUnplanned healthcare utilizationAdult patientsBowel diseaseHealthcare utilizationHealthcare costsLogistic regressionRetrospective cohort studyNationwide Readmissions DatabaseIdentification of patientsAdministrative claims dataHigh-cost patientsHNHC patientsCohort studyHospitalized patientsClaims dataHigh riskPatientsTraditional logistic regressionDerivation dataMean AUCIBDMean areaCharacteristic curveDisease
2021
Predictive Analytics for Glaucoma Using Data From the All of Us Research Program
Baxter S, Saseendrakumar B, Paul P, Kim J, Bonomi L, Kuo T, Loperena R, Ratsimbazafy F, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Mayo K, Mockrin S, Schully S, Ramirez A, Ohno-Machado L, Investigators A. Predictive Analytics for Glaucoma Using Data From the All of Us Research Program. American Journal Of Ophthalmology 2021, 227: 74-86. PMID: 33497675, PMCID: PMC8184631, DOI: 10.1016/j.ajo.2021.01.008.Peer-Reviewed Original ResearchConceptsGlaucoma surgeryPrimary open-angle glaucomaOphthalmic researchSingle-center cohortElectronic health record dataMultivariable logistic regressionSingle-center dataOpen-angle glaucomaHealth record dataMean ageClaims dataUs Research ProgramLogistic regressionSurgeryRecord dataOphthalmic imagingCharacteristic curveExternal validationGlaucomaCohortAUCSingle-center model