2024
Biomedical blockchain with practical implementations and quantitative evaluations: a systematic review
Lacson R, Yu Y, Kuo T, Ohno-Machado L. Biomedical blockchain with practical implementations and quantitative evaluations: a systematic review. Journal Of The American Medical Informatics Association 2024, 31: 1423-1435. PMID: 38726710, PMCID: PMC11105130, DOI: 10.1093/jamia/ocae084.Peer-Reviewed Original ResearchConceptsElectronic health recordsSystematic reviewData sharingMedical data sharingSpeed metricsPreferred Reporting ItemsCertificate storageDecentralized InternetNetwork permissionsBlockchain platformBlockchain applicationsEvaluation metricsBiomedical domainBlockchainBiomedical data managementHealth recordsData managementData storageReporting ItemsHealth sectorQuantitative metricsMedical facilitiesMetricsTrial managementClinical trial management
2023
Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care
Chin M, Afsar-Manesh N, Bierman A, Chang C, Colón-Rodríguez C, Dullabh P, Duran D, Fair M, Hernandez-Boussard T, Hightower M, Jain A, Jordan W, Konya S, Moore R, Moore T, Rodriguez R, Shaheen G, Snyder L, Srinivasan M, Umscheid C, Ohno-Machado L. Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care. JAMA Network Open 2023, 6: e2345050. PMID: 38100101, PMCID: PMC11181958, DOI: 10.1001/jamanetworkopen.2023.45050.Peer-Reviewed Original ResearchSevere aortic stenosis detection by deep learning applied to echocardiography
Holste G, Oikonomou E, Mortazavi B, Coppi A, Faridi K, Miller E, Forrest J, McNamara R, Ohno-Machado L, Yuan N, Gupta A, Ouyang D, Krumholz H, Wang Z, Khera R. Severe aortic stenosis detection by deep learning applied to echocardiography. European Heart Journal 2023, 44: 4592-4604. PMID: 37611002, PMCID: PMC11004929, DOI: 10.1093/eurheartj/ehad456.Peer-Reviewed Original ResearchConceptsSevere aortic stenosisExamining sociodemographic correlates of opioid use, misuse, and use disorders in the All of Us Research Program.
Yeh H, Peltz-Rauchman C, Johnson C, Pawloski P, Chesla D, Waring S, Stevens A, Epstein M, Joseph C, Miller-Matero L, Gui H, Tang A, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Loperena R, Mayo K, Mockrin S, Ohno-Machado L, Schully S, Ramirez A, Qian J, Ahmedani B. Examining sociodemographic correlates of opioid use, misuse, and use disorders in the All of Us Research Program. PLOS ONE 2023, 18: e0290416. PMID: 37594966, PMCID: PMC10437856, DOI: 10.1371/journal.pone.0290416.Peer-Reviewed Original ResearchConceptsOpioid use disorderOpioid usePrescription opioidsElectronic health recordsReduced oddsDiagnosis of OUDSociodemographic characteristicsPrevalence of OUDNonmedical useLifetime opioid useEHR dataNon-Hispanic white participantsImportant clinical informationNon-medical useLifetime prevalenceStreet opioidsHigher oddsOpioidsClinical informationUse disordersUs Research ProgramSociodemographic correlatesLogistic regressionPrevalenceHealth recordsFamily and personal history of cancer in the All of Us research program for precision medicine
Bruce L, Paul P, Kim K, Kim J, Keegan T, Hiatt R, Ohno-Machado L, Investigators O. Family and personal history of cancer in the All of Us research program for precision medicine. PLOS ONE 2023, 18: e0288496. PMID: 37459328, PMCID: PMC10351738, DOI: 10.1371/journal.pone.0288496.Peer-Reviewed Original ResearchCommon and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program
Wang X, Ryu J, Kim J, Ramirez A, Mayo K, Condon H, Vaitinadin N, Ohno-Machado L, Talavera G, Ellinor P, Lubitz S, Choi S. Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program. Journal Of Human Genetics 2023, 68: 565-570. PMID: 37072623, PMCID: PMC10524735, DOI: 10.1038/s10038-023-01147-z.Peer-Reviewed Original ResearchConceptsDiverse human populationsGenomic dataGene-based burden testsWhole genome sequencesRare variant analysisHuman populationQuantitative traitsBurden testsRare lossLociComplex diseasesGenetic associationVariant analysisFunction variantsCardiometabolic traitsRare variantsTraitsBiomedical researchGIGYF1VariantsNPR2ACANSequencePopulationLDLRSimulating complex patient populations with hierarchical learning effects to support methods development for post-market surveillance
Davis S, Ssemaganda H, Koola J, Mao J, Westerman D, Speroff T, Govindarajulu U, Ramsay C, Sedrakyan A, Ohno-Machado L, Resnic F, Matheny M. Simulating complex patient populations with hierarchical learning effects to support methods development for post-market surveillance. BMC Medical Research Methodology 2023, 23: 89. PMID: 37041457, PMCID: PMC10088292, DOI: 10.1186/s12874-023-01913-9.Peer-Reviewed Original ResearchConceptsSynthetic datasetsData characteristicsFeature distributionGround truthMIMIC-III dataReal-world dataData generation processComplex simulation studiesData relationshipsUser definitionSmall datasetsSimulation requirementsCorrelated featuresWorld dataCustomizable optionsReal-world complexitySynthetic patientsNew algorithmDatasetGeneration processLearningAlgorithmData simulation techniquesLearning effectGeneralizable frameworkBlockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions
Kuo T, Pham A, Edelson M, Kim J, Chan J, Gupta Y, Ohno-Machado L, Anderson D, Balacha C, Bath T, Baxter S, Becker-Pennrich A, Bell D, Bernstam E, Ngan C, Day M, Doctor J, DuVall S, El-Kareh R, Florian R, Follett R, Geisler B, Ghigi A, Gottlieb A, Hinske L, Hu Z, Ir D, Jiang X, Kim K, Kim J, Knight T, Koola J, Kuo T, Lee N, Mansmann U, Matheny M, Meeker D, Mou Z, Neumann L, Nguyen N, Nick A, Ohno-Machado L, Park E, Paul P, Pletcher M, Post K, Rieder C, Scherer C, Schilling L, Soares A, SooHoo S, Soysal E, Steven C, Tep B, Toy B, Wang B, Wu Z, Xu H, Yong C, Zheng K, Zhou Y, Zucker R. Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions. Journal Of The American Medical Informatics Association 2023, 30: 1167-1178. PMID: 36916740, PMCID: PMC10198529, DOI: 10.1093/jamia/ocad049.Peer-Reviewed Original ResearchConceptsFederated data analysisUser activity logsSmart contract deploymentRun-time efficiencyData analysis systemData analysis activitiesActivity logsData discoveryQuerying timeBlockchain systemBlockchain technologyNetwork transactionsCOVID-19 data analysisMultiple institutionsLow deploymentBlockchainGitHub repositoryMultiple nodesLarge networksQueriesAnalysis activitiesHigh availabilityLanguage codeBaseline solutionData analysisA hierarchical strategy to minimize privacy risk when linking “De-identified” data in biomedical research consortia
Ohno-Machado L, Jiang X, Kuo T, Tao S, Chen L, Ram P, Zhang G, Xu H. A hierarchical strategy to minimize privacy risk when linking “De-identified” data in biomedical research consortia. Journal Of Biomedical Informatics 2023, 139: 104322. PMID: 36806328, PMCID: PMC10975485, DOI: 10.1016/j.jbi.2023.104322.Peer-Reviewed Original ResearchConceptsPrivacy of individualsAppropriate privacy protectionData-driven modelsPrivacy protectionPrivacy risksData Coordination CenterData hubData repositoryHierarchical strategyPrivacyBiomedical discoveryData setsRecord linkageData Coordinating CenterRepositoryComplex strategiesCoordination centerTechnologyTechniqueDataPartiesSetHierarchy
2022
Achieving a Representative Sample of Asian Americans in Biomedical Research Through Community-Based Approaches: Comparing Demographic Data in the All of Us Research Program With the American Community Survey
Randal F, Lozano P, Qi S, Maene C, Shah S, Mo Y, Ratsimbazafy F, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Loperena R, Mayo K, Mockrin S, Ohno-Machado L, Schully S, Ramirez A, Aschebrook-Kilfoy B, Ahsan H, Lam H, Kim K. Achieving a Representative Sample of Asian Americans in Biomedical Research Through Community-Based Approaches: Comparing Demographic Data in the All of Us Research Program With the American Community Survey. Journal Of Transcultural Nursing 2022, 34: 59-67. PMID: 36398985, DOI: 10.1177/10436596221130796.Peer-Reviewed Original ResearchInvestigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort
Nagar S, Pemu P, Qian J, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Loperena R, Mayo K, Mockrin S, Ohno-Machado L, Ramirez A, Schully S, Able A, Green A, Zuchner S, Jordan I, Meller R. Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort. Scientific Reports 2022, 12: 19797. PMID: 36396674, PMCID: PMC9672061, DOI: 10.1038/s41598-022-23353-z.Peer-Reviewed Original ResearchConceptsAssociation of hypertensionPrevalence of dementiaType 2 diabetesRisk factorsUS populationRace/ethnicityHigh prevalenceLarge observational cohort studyMultivariable logistic regression modelRisk factor modificationObservational cohort studyT2D risk factorsInvestigation of hypertensionAssociation of T2DOdds of dementiaRace/ethnicity groupsAssociation of sexCross-sectional analysisLogistic regression modelsWorld Health OrganizationElectronic health recordsConcurrent hypertensionModifiable comorbiditiesCohort studyFinal cohortComparative Safety and Effectiveness of Biologic Therapy for Crohn’s Disease: A CA-IBD Cohort Study
Singh S, Kim J, Luo J, Paul P, Rudrapatna V, Park S, Zheng K, Syal G, Ha C, Fleshner P, McGovern D, Sauk J, Limketkai B, Dulai P, Boland B, Eisenstein S, Ramamoorthy S, Melmed G, Mahadevan U, Sandborn W, Ohno-Machado L. Comparative Safety and Effectiveness of Biologic Therapy for Crohn’s Disease: A CA-IBD Cohort Study. Clinical Gastroenterology And Hepatology 2022, 21: 2359-2369.e5. PMID: 36343846, DOI: 10.1016/j.cgh.2022.10.029.Peer-Reviewed Original ResearchConceptsTNF-α antagonistsRisk of hospitalizationUstekinumab-treated patientsCrohn's diseaseSerious infectionsLower riskMulticenter cohortInflammatory bowel disease-related surgeryTumor necrosis factor α antagonistsNecrosis factor α antagonistsDisease-related surgeryHigher comorbidity burdenVedolizumab-treated patientsNew biologic agentsPropensity-score matchingComorbidity burdenCause hospitalizationAdult patientsBiologic therapyCohort studyPrior hospitalizationBiologic agentsΑ antagonistsBiologic classesComparative safetyConcordance of SARS-CoV-2 Antibody Results during a Period of Low Prevalence
Miller C, Althoff K, Schlueter D, Anton-Culver H, Chen Q, Garbett S, Ratsimbazafy F, Thomsen I, Karlson E, Cicek M, Pinto L, Malin B, Ohno-Machado L, Williams C, Goldstein D, Kouame A, Ramirez A, Gebo K, Schully S. Concordance of SARS-CoV-2 Antibody Results during a Period of Low Prevalence. MSphere 2022, 7: e00257-22. PMID: 36173112, PMCID: PMC9599436, DOI: 10.1128/msphere.00257-22.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 antibody concentrationsLow prevalenceVaccine availabilitySARS-CoV-2 enzyme-linked immunosorbent assayFalse positivityLow SARS-CoV-2 prevalenceSARS-CoV-2 IgG assaysSARS-CoV-2 IgG testSARS-CoV-2 IgG antibodiesSevere acute respiratory syndrome coronavirus 2Coronavirus disease 2019 prevalenceAcute respiratory syndrome coronavirus 2Antibody concentrationsSARS-CoV-2 testDifferent antigensRespiratory syndrome coronavirus 2SARS-CoV-2 prevalenceSyndrome coronavirus 2SARS-CoV-2 pandemicConcordant positive resultsConcordant negative resultsEnzyme-linked immunosorbent assayPositive resultsFuture pandemic preparednessConcordance of resultsAn Overview of Cancer in the First 315,000 All of Us Participants
Aschebrook-Kilfoy B, Zakin P, Craver A, Shah S, Kibriya M, Stepniak E, Ramirez A, Clark C, Cohn E, Ohno-Machado L, Cicek M, Boerwinkle E, Schully S, Mockrin S, Gebo K, Mayo K, Ratsimbazafy F, Sanders A, Shah R, Argos M, Ho J, Kim K, Daviglus M, Greenland P, Ahsan H, . An Overview of Cancer in the First 315,000 All of Us Participants. PLOS ONE 2022, 17: e0272522. PMID: 36048778, PMCID: PMC9436122, DOI: 10.1371/journal.pone.0272522.Peer-Reviewed Original ResearchEffect of Obesity on Risk of Hospitalization, Surgery, and Serious Infection in Biologic-Treated Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study
Gu P, Luo J, Kim J, Paul P, Limketkai B, Sauk J, Park S, Parekh N, Zheng K, Rudrapatna V, Syal G, Ha C, McGovern D, Melmed G, Fleshner P, Eisenstein S, Ramamoorthy S, Dulai P, Boland B, Grunvald E, Mahadevan U, Ohno-Machado L, Sandborn W, Singh S. Effect of Obesity on Risk of Hospitalization, Surgery, and Serious Infection in Biologic-Treated Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study. The American Journal Of Gastroenterology 2022, 117: 1639-1647. PMID: 35973139, DOI: 10.14309/ajg.0000000000001855.Peer-Reviewed Original ResearchConceptsInflammatory bowel diseaseBiologic-treated patientsRisk of hospitalizationBody mass indexNormal body mass indexSerious infectionsBiologic agentsBowel diseaseCox proportional hazards analysisWorld Health Organization classificationEffect of obesityProportional hazards analysisElectronic health recordsCause hospitalizationVisceral obesityAdult patientsBaseline demographicsBiologic initiationBiologic therapyCohort studyEndoscopic outcomesMass indexOrganization classificationTreatment characteristicsStratified analysisSimplified 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 curveDiseaseEffectiveness and Safety of Biologic Therapy in Hispanic Vs Non-Hispanic Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study
Nguyen N, Luo J, Paul P, Kim J, Syal G, Ha C, Rudrapatna V, Park S, Parekh N, Zheng K, Sauk J, Limketkai B, Fleshner P, Eisenstein S, Ramamoorthy S, Melmed G, Dulai P, Boland B, Mahadevan U, Sandborn W, Ohno-Machado L, McGovern D, Singh S. Effectiveness and Safety of Biologic Therapy in Hispanic Vs Non-Hispanic Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study. Clinical Gastroenterology And Hepatology 2022, 21: 173-181.e5. PMID: 35644340, PMCID: PMC9701245, DOI: 10.1016/j.cgh.2022.05.008.Peer-Reviewed Original ResearchConceptsInflammatory bowel diseaseNon-Hispanic patientsBiologic-treated patientsHispanic patientsSerious infectionsBiologic therapyBowel diseasePropensity score-matched cohortBurden of inflammationRisk of hospitalizationHigh ratePropensity-score matchingCause hospitalizationAdult patientsBiologic initiationCohort studyBiologic agentsMedication useHigh burdenHigh riskHospitalizationPatientsSurvival analysisSurgeryAbstractTextInclusion of social determinants of health improves sepsis readmission prediction models
Amrollahi F, Shashikumar S, Meier A, Ohno-Machado L, Nemati S, Wardi G. Inclusion of social determinants of health improves sepsis readmission prediction models. Journal Of The American Medical Informatics Association 2022, 29: 1263-1270. PMID: 35511233, PMCID: PMC9196687, DOI: 10.1093/jamia/ocac060.Peer-Reviewed Original ResearchConceptsUnplanned readmissionSepsis patientsReadmission modelsClinical/laboratory featuresSocial determinantsUnplanned hospital readmissionHigh-risk patientsObjective clinical dataLow predictive valueReadmission prediction modelsSepsis readmissionsLaboratory featuresSepsis casesHospital readmissionPredictive factorsClinical dataReadmissionHigh riskPredictive valueSDH factorsMedical carePatientsDemographic featuresLarger studyProgram cohortA research agenda to support the development and implementation of genomics-based clinical informatics tools and resources
Wiley K, Findley L, Goldrich M, Rakhra-Burris T, Stevens A, Williams P, Bult C, Chisholm R, Deverka P, Ginsburg G, Green E, Jarvik G, Mensah G, Ramos E, Relling M, Roden D, Rowley R, Alterovitz G, Aronson S, Bastarache L, Cimino J, Crowgey E, Del Fiol G, Freimuth R, Hoffman M, Jeff J, Johnson K, Kawamoto K, Madhavan S, Mendonca E, Ohno-Machado L, Pratap S, Taylor C, Ritchie M, Walton N, Weng C, Zayas-Cabán T, Manolio T, Williams M. A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources. Journal Of The American Medical Informatics Association 2022, 29: 1342-1349. PMID: 35485600, PMCID: PMC9277642, DOI: 10.1093/jamia/ocac057.Peer-Reviewed Original ResearchCodesigning a community-based participatory research project to assess tribal perspectives on privacy and health data sharing: A report from the Strong Heart Study
Triplett C, Fletcher B, Taitingfong R, Zhang Y, Ali T, Ohno-Machado L, Bloss C. Codesigning a community-based participatory research project to assess tribal perspectives on privacy and health data sharing: A report from the Strong Heart Study. Journal Of The American Medical Informatics Association 2022, 29: 1120-1127. PMID: 35349678, PMCID: PMC9093024, DOI: 10.1093/jamia/ocac038.Peer-Reviewed Original Research