2023
Patient and researcher stakeholder preferences for use of electronic health record data: a qualitative study to guide the design and development of a platform to honor patient preferences.
Morse B, Kim K, Xu Z, Matsumoto C, Schilling L, Ohno-Machado L, Mak S, Keller M. Patient and researcher stakeholder preferences for use of electronic health record data: a qualitative study to guide the design and development of a platform to honor patient preferences. Journal Of The American Medical Informatics Association 2023, 30: 1137-1149. PMID: 37141581, PMCID: PMC10198527, DOI: 10.1093/jamia/ocad058.Peer-Reviewed Original Research
2022
Evaluation of available risk scores to predict multiple cardiovascular complications for patients with type 2 diabetes mellitus using electronic health records
Ho J, Staimez L, Narayan K, Ohno-Machado L, Simpson R, Hertzberg V. Evaluation of available risk scores to predict multiple cardiovascular complications for patients with type 2 diabetes mellitus using electronic health records. Computer Methods And Programs In Biomedicine Update 2022, 3: 100087. PMID: 37332899, PMCID: PMC10274317, DOI: 10.1016/j.cmpbup.2022.100087.Peer-Reviewed Original ResearchType 2 diabetes mellitusCardiovascular risk modelsElectronic health recordsDiabetes mellitusCardiovascular risk prediction modelsHealth recordsElectronic health record dataAvailable risk scoresMultiple cardiovascular complicationsType 2 diabetesHosmer-Lemeshow goodnessHealth record dataHosmer-Lemeshow statisticRisk prediction modelCardiovascular complicationsCardiovascular outcomesCardiovascular endpointsC-statisticRisk modelRisk scoreType 2PatientsSecondary analysisImpact of raceRecord dataThe All of Us Research Program: Data quality, utility, and diversity
Ramirez A, Sulieman L, Schlueter D, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman K, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark C, Cohn E, Ohno-Machado L, Schully S, Ahmedani B, Argos M, Cronin R, O’Donnell C, Fouad M, Goldstein D, Greenland P, Hebbring S, Karlson E, Khatri P, Korf B, Smoller J, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney S, Gebo K, Denny J, Carroll R, Glazer D, Harris P, Hripcsak G, Philippakis A, Roden D, Program T, Ahmedani B, Johnson C, Ahsan H, Antoine-LaVigne D, Singleton G, Anton-Culver H, Topol E, Baca-Motes K, Steinhubl S, Wade J, Begale M, Jain P, Sutherland S, Lewis B, Korf B, Behringer M, Gharavi A, Goldstein D, Hripcsak G, Bier L, Boerwinkle E, Brilliant M, Murali N, Hebbring S, Farrar-Edwards D, Burnside E, Drezner M, Taylor A, Channamsetty V, Montalvo W, Sharma Y, Chinea C, Jenks N, Cicek M, Thibodeau S, Holmes B, Schlueter E, Collier E, Winkler J, Corcoran J, D’Addezio N, Daviglus M, Winn R, Wilkins C, Roden D, Denny J, Doheny K, Nickerson D, Eichler E, Jarvik G, Funk G, Philippakis A, Rehm H, Lennon N, Kathiresan S, Gabriel S, Gibbs R, Rico E, Glazer D, Grand J, Greenland P, Harris P, Shenkman E, Hogan W, Igho-Pemu P, Pollan C, Jorge M, Okun S, Karlson E, Smoller J, Murphy S, Ross M, Kaushal R, Winford E, Wallace F, Khatri P, Kheterpal V, Ojo A, Moreno F, Kron I, Peterson R, Menon U, Lattimore P, Leviner N, Obedin-Maliver J, Lunn M, Malik-Gagnon L, Mangravite L, Marallo A, Marroquin O, Visweswaran S, Reis S, Marshall G, McGovern P, Mignucci D, Moore J, Munoz F, Talavera G, O'Connor G, O'Donnell C, Ohno-Machado L, Orr G, Randal F, Theodorou A, Reiman E, Roxas-Murray M, Stark L, Tepp R, Zhou A, Topper S, Trousdale R, Tsao P, Weidman L, Weiss S, Wellis D, Whittle J, Wilson A, Zuchner S, Zwick M. The All of Us Research Program: Data quality, utility, and diversity. Patterns 2022, 3: 100570. PMID: 36033590, PMCID: PMC9403360, DOI: 10.1016/j.patter.2022.100570.Peer-Reviewed Original ResearchEpidemiology of atrial fibrillation in the All of Us Research Program
Alonso A, Alam A, Kamel H, Subbian V, Qian J, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Loperena-Cortes R, Mayo K, Mockrin S, Ohno-Machado L, Schully S, Ramirez A, Greenland P. Epidemiology of atrial fibrillation in the All of Us Research Program. PLOS ONE 2022, 17: e0265498. PMID: 35294480, PMCID: PMC8926244, DOI: 10.1371/journal.pone.0265498.Peer-Reviewed Original ResearchConceptsAtrial fibrillationNon-Hispanic whitesUs Research ProgramRisk factorsEpidemiology of AFIncidence of AFPresence of AFHigher body mass indexStudy of AFClinical risk factorsIncident atrial fibrillationCoronary heart diseaseBody mass indexElectronic health record dataMedical history dataMedical history surveyNon-Hispanic blacksHealth record dataAvailable EHR dataNon-Hispanic AsiansHeart failureStudy enrollmentMass indexEligible participantsMean age
2021
Pediatric data from the All of Us research program: demonstration of pediatric obesity over time
Giangreco N, Lina S, Qian J, Kuoame A, Subbian V, Boerwinkle E, Cicek M, Clark C, Cohen E, Gebo K, Loperena-Cortes R, Mayo K, Mockrin S, Ohno-Machado L, Schully S, Tatonetti N, Ramirez A. Pediatric data from the All of Us research program: demonstration of pediatric obesity over time. JAMIA Open 2021, 4: ooab112. PMID: 35155998, PMCID: PMC8827025, DOI: 10.1093/jamiaopen/ooab112.Peer-Reviewed Original ResearchPredictive 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
2020
Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers
Madhavan S, Bastarache L, Brown J, Butte A, Dorr D, Embi P, Friedman C, Johnson K, Moore J, Kohane I, Payne P, Tenenbaum J, Weiner M, Wilcox A, Ohno-Machado L. Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers. Journal Of The American Medical Informatics Association 2020, 28: 393-401. PMID: 33260207, PMCID: PMC7665546, DOI: 10.1093/jamia/ocaa287.Commentaries, Editorials and Letters
2016
iCONCUR: informed consent for clinical data and bio-sample use for research
Kim H, Bell E, Kim J, Sitapati A, Ramsdell J, Farcas C, Friedman D, Feupe S, Ohno-Machado L. iCONCUR: informed consent for clinical data and bio-sample use for research. Journal Of The American Medical Informatics Association 2016, 24: 380-387. PMID: 27589942, PMCID: PMC5391727, DOI: 10.1093/jamia/ocw115.Peer-Reviewed Original ResearchConceptsPatient preferencesClinical dataHuman immunodeficiency virus clinicInternal medicine clinicElectronic health record dataHealth record dataAcademic medical centerElectronic health recordsDe-identified dataOutpatient clinicMedicine clinicFamily historyMedical CenterInformed Consent ToolClinical settingClinicHealth recordsRecord dataInformed consent systemPatientsConsent toolRecipientsConsentE-consentParticipantsConsensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges
Amarasingham R, Audet A, Bates D, Glenn Cohen I, Entwistle M, Escobar G, Liu V, Etheredge L, Lo B, Ohno-Machado L, Ram S, Saria S, Schilling L, Shahi A, Stewart W, Steyerberg E, Xie B. Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges. Healthcare 2016, 4: 1163. PMID: 27141516, PMCID: PMC4837887, DOI: 10.13063/2327-9214.1163.Commentaries, Editorials and LettersPredictive analytics applicationsAnalytics applicationsPredictive analyticsData sharingData barriersPredictive model developmentElectronic health record dataCertification frameworkReal timeEfficient mannerModel developmentAvailable electronic health record dataHealth record dataList of recommendationsSystematic frameworkAlgorithmDiverse expertiseRecent explosionEarlier frameworkFramework