2023
Natural Language Processing — A Surveillance Stepping Stone to Identify Child Abuse
Shum M, Hsiao A, Teng W, Asnes A, Amrhein J, Tiyyagura G. Natural Language Processing — A Surveillance Stepping Stone to Identify Child Abuse. Academic Pediatrics 2023, 24: 92-96. PMID: 37652162, PMCID: PMC10840716, DOI: 10.1016/j.acap.2023.08.015.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsChildChild AbuseDecision Support Systems, ClinicalElectronic Health RecordsEmergency Service, HospitalHumansNatural Language ProcessingConceptsClinical guidelinesClinical decision support toolSignificant demographic differencesED providersProvider notesInsurance statusGeneral EDsClinical careAbuse evaluationsED typeChild protective servicesChild abuseInjuryAppropriate evaluationChild physical abuseNLP algorithmDemographic differencesPhysical abuseAdherenceDemographic variablesProtective servicesNatural language processing algorithmAbuseReal-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications
Sangal R, Rothenberg C, Hawk K, D'Onofrio G, Hsiao A, Solad Y, Venkatesh A. Real-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications. The Joint Commission Journal On Quality And Patient Safety 2023, 49: 239-246. PMID: 36914528, DOI: 10.1016/j.jcjq.2023.01.013.Peer-Reviewed Original ResearchMeSH KeywordsAnalgesics, OpioidElectronic Health RecordsEmergency Service, HospitalHospitalsHumansPractice Patterns, Physicians'Retrospective StudiesConceptsOpioid prescribingED visitsElectronic health recordsOpioid prescriptionsEmergency department opioid prescriptionsAnalgesia prescriptionOpioid stewardshipOpioid medicationsSecondary outcomesPrimary outcomePreintervention periodInterruptive alertsCommon interventionPrescribingAlert fatigueElectronic prescribingPrevious interventionsHospital systemObservational evaluationHealth recordsVisitsStewardship policiesInterventionOutcomesPrescription
2021
Development and Validation of a Natural Language Processing Tool to Identify Injuries in Infants Associated With Abuse
Tiyyagura G, Asnes AG, Leventhal JM, Shapiro ED, Auerbach M, Teng W, Powers E, Thomas A, Lindberg DM, McClelland J, Kutryb C, Polzin T, Daughtridge K, Sevin V, Hsiao AL. Development and Validation of a Natural Language Processing Tool to Identify Injuries in Infants Associated With Abuse. Academic Pediatrics 2021, 22: 981-988. PMID: 34780997, PMCID: PMC9095755, DOI: 10.1016/j.acap.2021.11.004.Peer-Reviewed Original ResearchAlgorithmsChildChild AbuseElectronic Health RecordsHumansInfantNatural Language ProcessingSensitivity and SpecificityDisparities in Accessing and Reading Open Notes in the Emergency Department Upon Implementation of the 21st Century CURES Act
Sangal RB, Powers E, Rothenberg C, Ndumele C, Ulrich A, Hsiao A, Venkatesh AK. Disparities in Accessing and Reading Open Notes in the Emergency Department Upon Implementation of the 21st Century CURES Act. Annals Of Emergency Medicine 2021, 78: 593-598. PMID: 34353651, DOI: 10.1016/j.annemergmed.2021.06.014.Peer-Reviewed Original ResearchConceptsProportion of patientsPatient portal accessEmergency departmentOpen notesClinical notesPortal accessPublic insuranceUrgent care centersCentury Cures ActDifferent patient demographicsSingle health systemPatient demographicsPrimary outcomeCures ActPatient utilizationPatient visitsCare centerObservational studyPatientsDigital health toolsAge 18Health systemHealth toolsUnique barriersNon-English speakersEarly identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules
Shung D, Tsay C, Laine L, Chang D, Li F, Thomas P, Partridge C, Simonov M, Hsiao A, Tay JK, Taylor A. Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules. Journal Of Gastroenterology And Hepatology 2021, 36: 1590-1597. PMID: 33105045, DOI: 10.1111/jgh.15313.Peer-Reviewed Original ResearchConceptsNatural language processingElectronic health recordsLanguage processingNLP algorithmSystematized NomenclatureReal timeAcute gastrointestinal bleedingBidirectional Encoder RepresentationsDecision rulesEHR-based phenotyping algorithmsGastrointestinal bleedingRisk stratification scoresEncoder RepresentationsData elementsPhenotyping algorithmStratification scoresHealth recordsAlgorithmPhenotyping of patientsEmergency department patientsTime of presentationRisk stratification modelED reviewDeploymentExternal validation
2019
A randomized trial of decision support for tobacco dependence treatment in an inpatient electronic medical record: clinical results
Bernstein SL, Weiss J, DeWitt M, Tetrault JM, Hsiao AL, Dziura J, Sussman S, Miller T, Carpenter K, O’Connor P, Toll B. A randomized trial of decision support for tobacco dependence treatment in an inpatient electronic medical record: clinical results. Implementation Science 2019, 14: 8. PMID: 30670043, PMCID: PMC6343239, DOI: 10.1186/s13012-019-0856-8.Peer-Reviewed Original ResearchConceptsPatient's primary care providerPrimary care providersTobacco treatment medicationsElectronic health recordsTobacco use disorderQuit ratesTreatment medicationsProblem listCare providersUse disordersOne-year quit ratesState tobacco quitlineTobacco quit ratesPrescription of medicationsTobacco dependence treatmentProcess of careSingle hospital systemElectronic medical recordsInpatient electronic medical recordPatient's problem listSustained quittingAdult patientsControl patientsCurrent smokingHospitalized smokers
2017
Design and implementation of decision support for tobacco dependence treatment in an inpatient electronic medical record: a randomized trial
Bernstein SL, Rosner J, DeWitt M, Tetrault J, Hsiao AL, Dziura J, Sussman S, O'Connor P, Toll B. Design and implementation of decision support for tobacco dependence treatment in an inpatient electronic medical record: a randomized trial. Translational Behavioral Medicine 2017, 7: 185-195. PMID: 28194729, PMCID: PMC5526813, DOI: 10.1007/s13142-017-0470-8.Peer-Reviewed Original ResearchMeSH KeywordsDecision Support Systems, ClinicalElectronic Health RecordsHospitalizationHumansInpatientsPhysiciansSmokersSmokingSmoking CessationTreatment OutcomeUser-Computer InterfaceConceptsPatient's primary care providerTobacco dependence treatmentTobacco treatment medicationsElectronic health recordsPrimary care providersState Smokers' QuitlineTobacco use disorderDependence treatmentTreatment medicationsIntervention physiciansProblem listUse disordersOrder setsState tobacco quitlineCluster-randomized trialLong-term cessationElectronic medical recordsInpatient electronic medical recordPatient's problem listSmokers resultsAdult patientsHospital dischargeHospitalized smokersElectronic alertsTobacco treatmentDevelopment and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record
Rothman MJ, Tepas JJ, Nowalk AJ, Levin JE, Rimar JM, Marchetti A, Hsiao AL. Development and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record. Journal Of Biomedical Informatics 2017, 66: 180-193. PMID: 28057565, DOI: 10.1016/j.jbi.2016.12.013.Peer-Reviewed Original ResearchConceptsUnplanned ICU transfersPediatric Rothman IndexElectronic medical recordsRothman IndexICU transferPediatric RiskClinical statusPediatric hospitalHospitalized childrenMedical recordsPRI scoresPatient's conditionMortality dataPost-discharge mortalityPatient's clinical statusMortality odds ratioHospital mortalityInpatient visitsPatient ageAdult mortality dataClinical variablesOdds ratioClinical dataPhysiologic deteriorationPatient acuity
2014
Using a Scripted Data Entry Process to Transfer Legacy Immunization Data While Transitioning Between Electronic Medical Record Systems
Michel J, Hsiao A, Fenick A. Using a Scripted Data Entry Process to Transfer Legacy Immunization Data While Transitioning Between Electronic Medical Record Systems. Applied Clinical Informatics 2014, 05: 284-298. PMID: 24734139, PMCID: PMC3974261, DOI: 10.4338/aci-2013-11-ra-0096.Peer-Reviewed Original ResearchConceptsElectronic medical recordsImmunization dataSystem's electronic medical recordHealth systemAppropriate patient careManual chart reviewManual chart abstractionElectronic medical record systemChart abstractionChart reviewMedical record systemMedical recordsClinical careData entryPatient careImmunizationPatient dataHealthcare facilitiesProcess evaluationRecord systemManual data entry
2013
Automated analysis of electronic medical record data reflects the pathophysiology of operative complications
Tepas JJ, Rimar JM, Hsiao AL, Nussbaum MS. Automated analysis of electronic medical record data reflects the pathophysiology of operative complications. Surgery 2013, 154: 918-926. PMID: 24074431, DOI: 10.1016/j.surg.2013.07.014.Peer-Reviewed Original ResearchMeSH KeywordsAutomationColonElectronic Health RecordsHealth Care CostsHumansLength of StayPostoperative ComplicationsRetrospective StudiesSepsisConceptsElectronic medical recordsNumber of complicationsRothman IndexPostoperative complicationsColorectal proceduresPhysiologic dysfunctionDischarge International ClassificationElectronic medical record dataOrgan system dysfunctionPresence of sepsisIncidence of complicationsDirect costsMedical record dataDuration of stayRepeated-measures analysisPerioperative complicationsPostoperative sepsisOperative complicationsOperative patientsOrgan dysfunctionOverall incidencePreoperative counselingPhysiologic assessmentNursing observationsPatient cohort