2024
Pragmatic Trial of Messaging to Providers About Treatment of Hyperlipidemia (PROMPT-LIPID): A Randomized Clinical Trial
Shah N, Ghazi L, Yamamoto Y, Kumar S, Martin M, Simonov M, Riello Iii R, Faridi K, Ahmad T, Wilson F, Desai N. Pragmatic Trial of Messaging to Providers About Treatment of Hyperlipidemia (PROMPT-LIPID): A Randomized Clinical Trial. Circulation Cardiovascular Quality And Outcomes 2024, 17: e010335. PMID: 38634282, DOI: 10.1161/circoutcomes.123.010335.Peer-Reviewed Original ResearchElectronic health recordsElectronic health record alertsHigh-risk atherosclerotic cardiovascular diseaseLipid lowering therapyAtherosclerotic cardiovascular diseasePragmatic trialCardiovascular diseaseProportion of patientsYale New Haven HealthLDL-CSecondary outcomesPrimary outcomeInternal medicine cliniciansEHR alertUsual careHealth recordsProvider levelCluster-randomizedLDL-C managementLDL-C levelsAdverse cardiovascular eventsRandomized clinical trialsTreatment of hyperlipidemiaCliniciansCardiovascular events
2021
Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial
Wilson FP, Martin M, Yamamoto Y, Partridge C, Moreira E, Arora T, Biswas A, Feldman H, Garg AX, Greenberg JH, Hinchcliff M, Latham S, Li F, Lin H, Mansour SG, Moledina DG, Palevsky PM, Parikh CR, Simonov M, Testani J, Ugwuowo U. Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial. The BMJ 2021, 372: m4786. PMID: 33461986, PMCID: PMC8034420, DOI: 10.1136/bmj.m4786.Peer-Reviewed Original ResearchConceptsAcute kidney injuryElectronic health record alertsKidney injuryPrimary outcomeMedical recordsYale New Haven Health SystemCare practicesGlobal Outcomes creatinine criteriaLarge tertiary care centerComposite of progressionDays of randomizationReceipt of dialysisPrespecified secondary outcomesTertiary care centerPatients' medical recordsSmall community hospitalNon-teaching hospitalsElectronic health recordsCreatinine criteriaUsual careSecondary outcomesAdult inpatientsKidney diseaseClinical centersWorse outcomes
2019
A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: A descriptive modeling study
Simonov M, Ugwuowo U, Moreira E, Yamamoto Y, Biswas A, Martin M, Testani J, Wilson FP. A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: A descriptive modeling study. PLOS Medicine 2019, 16: e1002861. PMID: 31306408, PMCID: PMC6629054, DOI: 10.1371/journal.pmed.1002861.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAgedAged, 80 and overConnecticutDecision Support TechniquesElectronic Health RecordsFemaleHospital MortalityHumansInpatientsMaleMiddle AgedPatient AdmissionPredictive Value of TestsPrognosisRenal DialysisRetrospective StudiesRisk AssessmentRisk FactorsSeverity of Illness IndexTime FactorsConceptsAcute kidney injuryImminent acute kidney injuryElectronic health recordsKidney injuryHospital 1Prediction of AKIRenal replacement therapyOptimal treatment strategyLaboratory dataReceiver operator characteristic curveInternal validation setAKI occurrenceAKI severityHospitalized adultsMedical comorbiditiesOverall cohortAdverse eventsHospitalized patientsSurgical wardsSignificant morbidityReplacement therapyExternal validation data setsHospital 2Hospital 3Study hospital