2024
3D gamma analysis between treatment plans for nominally beam‐matched medical linear accelerators using PyMedPhys
Guan F, Donahue W, Biggs S, Jennings M, Draeger E, Chen H, Wang Y, Nguyen N, Carlson D, Chen Z, Han D. 3D gamma analysis between treatment plans for nominally beam‐matched medical linear accelerators using PyMedPhys. Precision Radiation Oncology 2024, 8: 191-199. PMID: 40337454, PMCID: PMC11934910, DOI: 10.1002/pro6.1247.Peer-Reviewed Original ResearchGamma analysisGamma indexEvaluation of treatment plansPlanned dose distributionMedical linear acceleratorPass rateEfficient treatment deliveryMedian pass rateDose distributionTreatment planningLinacLinear acceleratorCalculated doseTreatment deliveryConformal radiotherapyOriginal planRadiation therapyPatient transferDisease sitesIn-house scriptsBeam modelPatientsBeamRadiotherapyAccelerationChallenges in Effective Referral of Cardiovascular Diseases in Nepal: A Qualitative Study from Health Workers’ and Patients’ Perspective
Shrestha S, Maharjan R, Bajracharya S, Jha N, Mali S, Thapa B, Suwal P, Prajapati D, Karmacharya B, Shrestha A. Challenges in Effective Referral of Cardiovascular Diseases in Nepal: A Qualitative Study from Health Workers’ and Patients’ Perspective. Cardiology Research And Practice 2024, 2024: 5583709. PMID: 38476339, PMCID: PMC10932621, DOI: 10.1155/2024/5583709.Peer-Reviewed Original ResearchReferral systemCardiovascular disease patientsCVD casesNoncommunicable diseasesCardiovascular diseaseQualitative studyBurden of noncommunicable diseasesCardiovascular disease careFactors affecting referralTertiary-level careCardiovascular disease casesOpen-ended questionsTranscribed verbatimHealth workersLack of human resourcesHealthcare professionalsPatient perspectiveFace-to-faceEffective referralInterview guideMadhesh ProvinceThematic approachTelephone interviewsPatient transferReferral strategies
2023
An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model
Charkoftaki G, Aalizadeh R, Santos-Neto A, Tan W, Davidson E, Nikolopoulou V, Wang Y, Thompson B, Furnary T, Chen Y, Wunder E, Coppi A, Schulz W, Iwasaki A, Pierce R, Cruz C, Desir G, Kaminski N, Farhadian S, Veselkov K, Datta R, Campbell M, Thomaidis N, Ko A, Thompson D, Vasiliou V. An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model. Human Genomics 2023, 17: 80. PMID: 37641126, PMCID: PMC10463861, DOI: 10.1186/s40246-023-00521-4.Peer-Reviewed Original ResearchConceptsCOVID-19 patientsDisease severityViral outbreaksFuture viral outbreaksLength of hospitalizationIntensive care unitWorse disease prognosisLife-threatening illnessEffective medical interventionsCOVID-19Clinical decision treeGlucuronic acid metabolitesNew potential biomarkersHospitalization lengthCare unitComorbidity dataSerotonin levelsDisease progressionHealthy controlsPatient outcomesDisease prognosisPatient transferPatientsHealthcare resourcesPotential biomarkers
2022
A survey of stroke‐related capabilities among a sample of US community emergency departments
Zachrison KS, Ganti L, Sharma D, Goyal P, Decker‐Palmer M, Adeoye O, Goldstein JN, Jauch EC, Lo BM, Madsen TE, Meurer W, Oostema JA, Mendez‐Hernandez C, Venkatesh AK. A survey of stroke‐related capabilities among a sample of US community emergency departments. Journal Of The American College Of Emergency Physicians Open 2022, 3: e12762. PMID: 35898236, PMCID: PMC9307290, DOI: 10.1002/emp2.12762.Peer-Reviewed Original ResearchCommunity emergency departmentsStroke care deliveryEmergency departmentStroke centersCare deliveryAcute stroke researchLarge stroke centersTransient ischemic attackQuality improvement interventionsIschemic attackStroke protocolHemorrhagic strokePatient outcomesEmergent headStroke researchPatient transferCurrent emergency departmentImprovement interventionsHospitalLarge hospitalsSmall hospitalsNeurologic consultantsConsultant availabilitySelf-reported capabilityStroke
2021
Failure Mode and Effect Analysis: Engineering Safer Neurocritical Care Transitions
Chilakamarri P, Finn EB, Sather J, Sheth KN, Matouk C, Parwani V, Ulrich A, Davis M, Pham L, Chaudhry SI, Venkatesh AK. Failure Mode and Effect Analysis: Engineering Safer Neurocritical Care Transitions. Neurocritical Care 2021, 35: 232-240. PMID: 33403581, PMCID: PMC8255326, DOI: 10.1007/s12028-020-01160-6.Peer-Reviewed Original ResearchConceptsPatient safetyInter-hospital transferEmergency department throughputIntracerebral hemorrhageAcute careSubarachnoid hemorrhageNeurocritical careCare transitionsMulti-disciplinary teamPatient transferHemorrhageSignificant reductionInterventionCareHazard analysisOutcomesRiskSafetyMultiple providersSpecific use-case examplesEvidence of successPatientsStrokeMethodsWe
2018
Ischemic Stroke Transfer Patterns in the Northeast United States
Zachrison K, Onnela J, Hernandez A, Reeves M, Camargo C, Cox M, Matsouaka R, Metlay J, Goldstein J, Schwamm L. Ischemic Stroke Transfer Patterns in the Northeast United States. Journal Of Stroke And Cerebrovascular Diseases 2018, 28: 295-304. PMID: 30389376, DOI: 10.1016/j.jstrokecerebrovasdis.2018.09.048.Peer-Reviewed Original ResearchConceptsGuidelines-Stroke registryRegional stroke systemIschemic stroke patientsHospital connectionsTissue plasminogen activatorSevere strokeMore patientsStroke patientsIS patientsReceiving HospitalPatient dischargeStroke systemsPatient transferPatientsHospitalNortheast hospitalsMost hospitalsPlasminogen activatorCareUnited StatesFurther characterizationAdmissionRegistryStrokeImplementing a Warm Handoff Between Hospital and Skilled Nursing Facility Clinicians
Campbell Britton M, Hodshon B, Chaudhry SI. Implementing a Warm Handoff Between Hospital and Skilled Nursing Facility Clinicians. Journal Of Patient Safety 2018, Publish Ahead of Print: &na;. PMID: 30095538, DOI: 10.1097/pts.0000000000000529.Peer-Reviewed Original ResearchConceptsSkilled nursing facilitiesWarm handoffsSNF cliniciansPatient transferPatient careAdvanced practice providersHospital discharge summariesSafe patient careSNF physiciansAdverse eventsHospital dischargePatient dischargePractice providersHospital cliniciansHigh riskNursing facilitiesClinician workloadDischarge summariesCliniciansPatient safetyHospitalStage 3Specific barriersStage 1Stage 2Real-Time Surveys Reveal Important Safety Risks During Interhospital Care Transitions for Neurologic Emergencies
Sather J, Rothenberg C, Finn EB, Sheth KN, Matouk C, Pham L, Parwani V, Ulrich A, Venkatesh AK. Real-Time Surveys Reveal Important Safety Risks During Interhospital Care Transitions for Neurologic Emergencies. American Journal Of Medical Quality 2018, 34: 53-58. PMID: 29987938, DOI: 10.1177/1062860618785248.Peer-Reviewed Original ResearchConceptsEmergency departmentMultidisciplinary quality improvement effortNeuroscience intensive care unitTertiary health care systemIll neurologic patientsIntensive care unitAdvanced practice providersHealth care systemQuality improvement effortsClinician typeIll patientsNeurologic emergencyCare unitCare transitionsClinical surveyNeurologic patientsPractice providersPatient transferCare systemImportant safety risksPatientsRiskReal-time surveySafety risksImprovement effortsA taxonomy and cultural analysis of intra‐hospital patient transfers
Rosenberg A, Britton M, Feder S, Minges K, Hodshon B, Chaudhry SI, Jenq GY, Emerson BL. A taxonomy and cultural analysis of intra‐hospital patient transfers. Research In Nursing & Health 2018, 41: 378-388. PMID: 29722043, PMCID: PMC8459627, DOI: 10.1002/nur.21875.Peer-Reviewed Original ResearchPatient transferMedical intensive care unitGeneral medicine floorsTertiary medical centerIntensive care unitIntra-hospital transferIntra-hospital patient transfersMedicine floorCare unitEmergency departmentPatient transitionsMedical CenterPatient assignmentRight floorHospital departmentsObservations of staffCategories of activitiesHospital culturePatientsStaffEmpty bedsDepartmentHospital
2017
Care Transitions Between Hospitals and Skilled Nursing Facilities: Perspectives of Sending and Receiving Providers
Britton MC, Ouellet GM, Minges KE, Gawel M, Hodshon B, Chaudhry SI. Care Transitions Between Hospitals and Skilled Nursing Facilities: Perspectives of Sending and Receiving Providers. The Joint Commission Journal On Quality And Patient Safety 2017, 43: 565-572. PMID: 29056176, PMCID: PMC5693352, DOI: 10.1016/j.jcjq.2017.06.004.Peer-Reviewed Original ResearchMeSH KeywordsAcademic Medical CentersAttitude of Health PersonnelCommunicationHospital AdministrationHumansInsurance, Health, ReimbursementInterviews as TopicPatient DischargePatient ReadmissionPatient TransferQualitative ResearchQuality ImprovementRisk FactorsSeverity of Illness IndexSkilled Nursing FacilitiesUnited StatesConceptsSkilled nursing facilitiesCare transitionsNursing facilitiesSNF providersPatient-level risk factorsOptimal care settingAcute medical illnessUnplanned hospital readmissionComprehensive care planCost of careHospital readmissionMedical illnessComplex patientsRisk factorsMedicare patientsCare settingsCare plansPatient complexityHealth care institutionsPatient transferPsychosocial issuesHospitalPatientsSeparate hospitalsCare institutions
2010
Electronic health records and adverse drug events after patient transfer
Boockvar K, Livote E, Goldstein N, Nebeker J, Siu A, Fried T. Electronic health records and adverse drug events after patient transfer. BMJ Quality & Safety 2010, 19: e16. PMID: 20724395, PMCID: PMC2965207, DOI: 10.1136/qshc.2009.033050.Peer-Reviewed Original ResearchConceptsAdverse drug eventsHigh-risk medication discrepanciesElectronic health recordsMedication discrepanciesSite of careDrug eventsPatient transferStructured medical record reviewNon-VA groupsNon-VA patientsVeterans Affairs patientsHealth recordsMedical record reviewGroup of patientsPairs of physiciansHospitalisation episodesMedication reviewHospital transferOverall incidenceRecord reviewClinical covariatesMedication errorsNursing homesPatientsTime of transfer
2009
Prescribing discrepancies likely to cause adverse drug events after patient transfer
Boockvar K, Liu S, Goldstein N, Nebeker J, Siu A, Fried T. Prescribing discrepancies likely to cause adverse drug events after patient transfer. BMJ Quality & Safety 2009, 18: 32. PMID: 19204129, PMCID: PMC2728360, DOI: 10.1136/qshc.2007.025957.Peer-Reviewed Original ResearchConceptsAdverse drug eventsPositive predictive valueDrug classesMedication discrepanciesDrug eventsPatient transferObserved positive predictive valueHigh positive predictive valueHigh-risk patientsHigh-risk medicationsNon-opioid analgesicsNursing home patientsSite of careCertain drug classesDrug discrepanciesOpioid analgesicsDrug prescribingMedical recordsNursing homesPatientsPredictive valueCare qualityClinician ratersAnalgesicsTypes of discrepancies
2007
Effect of Intensive Care Unit Organizational Model and Structure on Outcomes in Patients with Acute Lung Injury
Treggiari MM, Martin DP, Yanez ND, Caldwell E, Hudson LD, Rubenfeld GD. Effect of Intensive Care Unit Organizational Model and Structure on Outcomes in Patients with Acute Lung Injury. American Journal Of Respiratory And Critical Care Medicine 2007, 176: 685-690. PMID: 17556721, PMCID: PMC1994237, DOI: 10.1164/rccm.200701-165oc.Peer-Reviewed Original ResearchConceptsAcute lung injuryClosed ICUOpen ICUHospital mortalityLung injuryData support recommendationsPopulation-based cohortPatient care practicesComplete survey dataAdult ICUsCohort studyImproved mortalityIll patientsIntensive careMain endpointPatient mortalityPotential confoundersHigher physicianICUICU structurePatient transferPatientsCare practicesSelf-administered mail questionnaireNurse availability
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