2023
Estimated reimbursement impact of COVID‐19 on emergency physicians
Venkatesh A, Janke A, Koski‐Vacirca R, Rothenberg C, Parwani V, Granovsky M, Burke L, Li S, Pines J. Estimated reimbursement impact of COVID‐19 on emergency physicians. Academic Emergency Medicine 2023, 30: 636-643. PMID: 36820470, DOI: 10.1111/acem.14700.Peer-Reviewed Original ResearchConceptsNationwide Emergency Department SampleED visitsEmergency physiciansSecondary analysisCOVID-19Acute care utilizationEmergency Department SampleEmergency Department registryCOVID-19 pandemicHealth care servicesEmergency department sitesReimbursement impactCare utilizationBilling codesInsurance payerDepartment registryPrimary analysisCare servicesPhysiciansReimbursement lossHealth careStudy sampleVisitsPandemic-related lossReimbursement
2022
Clinical characteristics, treatment and outcomes of patients with spontaneous renal artery dissections
Dicks AB, Elgendy IY, Thondapu V, Ghoshhajra B, Waller HD, Rubio M, Schainfeld RM, Weinberg I. Clinical characteristics, treatment and outcomes of patients with spontaneous renal artery dissections. Journal Of Nephrology 2022, 36: 377-384. PMID: 36178591, DOI: 10.1007/s40620-022-01444-4.Peer-Reviewed Original ResearchConceptsSpontaneous renal artery dissectionRenal artery dissectionArtery dissectionMedical therapyNatural historyOutcomes of patientsTertiary care centerTime of diagnosisAbsence of symptomsConclusionMost patientsBaseline characteristicsClinical characteristicsMost patientsPatient demographicsRenal functionSymptomatic patientsMedical chartsRetrospective reviewBenign courseClinical presentationTherapy utilizationResultsA totalMedical historyCare centerBilling codesPenetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia, Bipolar Disorder, and Depression Among Adults in the US Veterans Affairs Health Care System
Bigdeli TB, Voloudakis G, Barr PB, Gorman BR, Genovese G, Peterson RE, Burstein DE, Velicu VI, Li Y, Gupta R, Mattheisen M, Tomasi S, Rajeevan N, Sayward F, Radhakrishnan K, Natarajan S, Malhotra AK, Shi Y, Zhao H, Kosten TR, Concato J, O’Leary T, Przygodzki R, Gleason T, Pyarajan S, Brophy M, Huang GD, Muralidhar S, Gaziano JM, Aslan M, Fanous AH, Harvey PD, Roussos P, Aslan M, Antonelli M, de Asis M, Bauer M, Brophy M, Concato J, Cunningham F, Freedman R, Gaziano M, Gleason T, Harvey P, Huang G, Kelsoe J, Kosten T, Lehner T, Lohr J, Marder S, Miller P, O Leary T, Patterson T, Peduzzi P, Przygodski R, Siever L, Sklar P, Strakowski S, Zhao H, Fanous A, Farwell W, Malhorta A, Mane S, Palacios P, Bigdeli T, Corsey M, Zaluda L, Johnson J, Sueiro M, Cavaliere D, Jeanpaul V, Maffucci A, Mancini L, Deen J, Muldoon G, Whitbourne S, Canive J, Adamson L, Calais L, Fuldauer G, Kushner R, Toney G, Lackey M, Mank A, Mahdavi N, Villarreal G, Muly E, Amin F, Dent M, Wold J, Fischer B, Elliott A, Felix C, Gill G, Parker P, Logan C, McAlpine J, DeLisi L, Reece S, Hammer M, Agbor-Tabie D, Goodson W, Aslam M, Grainger M, Richtand N, Rybalsky A, Al Jurdi R, Boeckman E, Natividad T, Smith D, Stewart M, Torres S, Zhao Z, Mayeda A, Green A, Hofstetter J, Ngombu S, Scott M, Strasburger A, Sumner J, Paschall G, Mucciarelli J, Owen R, Theus S, Tompkins D, Potkin S, Reist C, Novin M, Khalaghizadeh S, Douyon R, Kumar N, Martinez B, Sponheim S, Bender T, Lucas H, Lyon A, Marggraf M, Sorensen L, Surerus C, Sison C, Amato J, Johnson D, Pagan-Howard N, Adler L, Alerpin S, Leon T, Mattocks K, Araeva N, Sullivan J, Suppes T, Bratcher K, Drag L, Fischer E, Fujitani L, Gill S, Grimm D, Hoblyn J, Nguyen T, Nikolaev E, Shere L, Relova R, Vicencio A, Yip M, Hurford I, Acheampong S, Carfagno G, Haas G, Appelt C, Brown E, Chakraborty B, Kelly E, Klima G, Steinhauer S, Hurley R, Belle R, Eknoyan D, Johnson K, Lamotte J, Granholm E, Bradshaw K, Holden J, Jones R, Le T, Molina I, Peyton M, Ruiz I, Sally L, Tapp A, Devroy S, Jain V, Kilzieh N, Maus L, Miller K, Pope H, Wood A, Meyer E, Givens P, Hicks P, Justice S, McNair K, Pena J, Tharp D, Davis L, Ban M, Cheatum L, Darr P, Grayson W, Munford J, Whitfield B, Wilson E, Melnikoff S, Schwartz B, Tureson M, D Souza D, Forselius K, Ranganathan M, Rispoli L, Sather M, Colling C, Haakenson C, Kruegar D, Muralidhar S, Ramoni R, Breeling J, Chang K, O Donnell C, Tsao P, Moser J, Brewer J, Warren S, Argyres D, Stevens B, Humphries D, Do N, Shayan S, Nguyen X, Pyarajan S, Cho K, Hauser E, Sun Y, Wilson P, McArdle R, Dellitalia L, Harley J, Whittle J. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia, Bipolar Disorder, and Depression Among Adults in the US Veterans Affairs Health Care System. JAMA Psychiatry 2022, 79: 1092-1101. PMID: 36103194, PMCID: PMC9475441, DOI: 10.1001/jamapsychiatry.2022.2742.Peer-Reviewed Original ResearchDiagnosis of schizophreniaPolygenic risk scoresBipolar disorderHealth care systemElectronic health recordsBilling codesRisk scoreUS Veterans Affairs Health Care SystemClinical InterviewVeterans Health Administration health care systemVeterans Affairs Health Care SystemDisorder-specific genetic factorsVeterans Health Administration electronic health recordsCare systemICD-9/10 codesMajor depression polygenic risk scoresSerious mental illnessEuropean ancestryDepression polygenic risk scoresPhysical health problemsAfrican ancestryUS veteransMajor depressionMillion Veteran ProgramMAIN OUTCOMEAnkle- and Toe-Brachial Index for Peripheral Artery Disease Identification: Unlocking Clinical Data Through Novel Methods
Friberg JE, Qazi AH, Boyle B, Franciscus C, Vaughan-Sarrazin M, Westerman D, Patterson OV, Parr SK, Matheny ME, Arya S, Smolderen KG, Lund BC, Gobbel GT, Girotra S. Ankle- and Toe-Brachial Index for Peripheral Artery Disease Identification: Unlocking Clinical Data Through Novel Methods. Circulation Cardiovascular Interventions 2022, 15: e011092. PMID: 35176872, PMCID: PMC10807980, DOI: 10.1161/circinterventions.121.011092.Peer-Reviewed Original ResearchConceptsPeripheral artery diseaseAnkle-brachial indexToe-brachial indexElectronic health recordsABI testingVeterans Affairs electronic health recordsHealth recordsStructured chart reviewVeterans Affairs facilitiesPositive predictive valuePAD patientsChart reviewArtery diseaseClinical dataClinical impactHigh prevalenceBilling codesSeparate cohortPredictive valuePatientsClinical expertsPAD researchRandom sampleLateralityReport
2021
Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research
Chandler P, Clark C, Zhou G, Noel N, Achilike C, Mendez L, Ramirez A, Loperena-Cortes R, Mayo K, Cohn E, Ohno-Machado L, Boerwinkle E, Cicek M, Qian J, Schully S, Ratsimbazafy F, Mockrin S, Gebo K, Dedier J, Murphy S, Smoller J, Karlson E. Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research. Scientific Reports 2021, 11: 12849. PMID: 34158555, PMCID: PMC8219813, DOI: 10.1038/s41598-021-92143-w.Peer-Reviewed Original ResearchConceptsPrevalence of hypertensionHTN prevalenceUs Research ProgramMajor public health concernBlood pressure medicationsPopulation-based studyNutrition Examination SurveyBlood pressure measurementsPopulation-based surveyEHR dataPatient measurementsPublic health concernAntihypertensive medicationsEHR cohortHTN medicationsHypertension prevalenceCrude prevalenceHypertension casesHypertension treatmentExamination SurveyNational HealthHypertensionBilling codesMedicationsCohort
2020
Reliability of International Classification of Disease-9 Versus International Classification of Disease-10 Coding for Proximal Femur Fractures at a Level 1 Trauma Center.
Schneble CA, Natoli RM, Schonlau DL, Reed RL, Kempton LB. Reliability of International Classification of Disease-9 Versus International Classification of Disease-10 Coding for Proximal Femur Fractures at a Level 1 Trauma Center. Journal Of The American Academy Of Orthopaedic Surgeons 2020, 28: 29-36. PMID: 30969187, DOI: 10.5435/jaaos-d-17-00874.Peer-Reviewed Original ResearchConceptsProximal femur fracturesFemur fracturesICD-9International ClassificationICD-10Level 1 trauma centerDiseases-10 codingMedical record codingTrauma centerBilling codesLevel IBilling recordsICD codesMedicaid ServicesSignificant differencesPhysiciansFracturesIntercoder reliabilityLack reliability
2019
Comparison of Clinical Trials and Administrative Claims to Identify Stroke Among Patients Undergoing Aortic Valve Replacement
Strom JB, Zhao Y, Faridi KF, Tamez H, Butala NM, Valsdottir LR, Curtis J, Brennan JM, Shen C, Boulware M, Popma JJ, Yeh RW. Comparison of Clinical Trials and Administrative Claims to Identify Stroke Among Patients Undergoing Aortic Valve Replacement. Circulation Cardiovascular Interventions 2019, 12: e008231. PMID: 31694411, PMCID: PMC7212938, DOI: 10.1161/circinterventions.119.008231.Peer-Reviewed Original ResearchMeSH KeywordsAdministrative Claims, HealthcareAgedAged, 80 and overAortic ValveAortic Valve StenosisBrain IschemiaClinical Trials as TopicDatabases, FactualFemaleHeart Valve Prosthesis ImplantationHumansIschemic Attack, TransientMaleMedicareRisk AssessmentRisk FactorsStrokeTime FactorsTranscatheter Aortic Valve ReplacementTreatment OutcomeUnited StatesConceptsNegative predictive valueAortic valve replacementCerebrovascular eventsInternational ClassificationPositive predictive valuePredictive valueValve replacementNinth RevisionClinical trialsTenth RevisionBilling codesKaplan-Meier estimatesMedicare inpatient claimsSURTAVI trialClinical event adjudicationDevastating complicationIschemic strokeNeurological eventsCerebrovascular diseaseBilling claimsInpatient claimsEvent adjudicationAdministrative claimsHigh riskTrial participantsIdentifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record–Based Computable Phenotype Derivation and Validation Study
Chartash D, Paek H, Dziura JD, Ross BK, Nogee DP, Boccio E, Hines C, Schott AM, Jeffery MM, Patel MD, Platts-Mills TF, Ahmed O, Brandt C, Couturier K, Melnick E. Identifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record–Based Computable Phenotype Derivation and Validation Study. JMIR Medical Informatics 2019, 7: e15794. PMID: 31674913, PMCID: PMC6913746, DOI: 10.2196/15794.Peer-Reviewed Original ResearchOpioid use disorderNegative predictive valuePositive predictive valueEmergency department patientsEmergency departmentUse disordersHealth care systemPredictive valueComputable phenotypeExternal validation phasesDepartment patientsCare systemPhysician chart reviewLarge health care systemExternal validation cohortEmergency medicine physiciansHigh predictive valueElectronic health recordsChart reviewChief complaintValidation cohortPragmatic trialClinical dataBilling codesMedicine physiciansPulmonary Embolism Hospitalization, Readmission, and Mortality Rates in US Older Adults, 1999-2015
Bikdeli B, Wang Y, Jimenez D, Parikh SA, Monreal M, Goldhaber SZ, Krumholz HM. Pulmonary Embolism Hospitalization, Readmission, and Mortality Rates in US Older Adults, 1999-2015. JAMA 2019, 322: 574-576. PMID: 31408124, PMCID: PMC6692667, DOI: 10.1001/jama.2019.8594.Peer-Reviewed Original Research
2018
Imaging Dose, Cancer Risk and Cost Analysis in Image-guided Radiotherapy of Cancers
Zhou L, Bai S, Zhang Y, Ming X, Zhang Y, Deng J. Imaging Dose, Cancer Risk and Cost Analysis in Image-guided Radiotherapy of Cancers. Scientific Reports 2018, 8: 10076. PMID: 29973695, PMCID: PMC6031630, DOI: 10.1038/s41598-018-28431-9.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overBone Marrow CellsBrainChildChild, PreschoolCone-Beam Computed TomographyCost-Benefit AnalysisFemaleHumansInfantLungMaleMiddle AgedMonte Carlo MethodNeoplasmsPhantoms, ImagingRadiation DosageRadiotherapy DosageRadiotherapy, Image-GuidedRisk FactorsThoraxYoung AdultConceptsCancer riskAssociated cancer riskImage-guided radiotherapyImaging proceduresLifetime attributable riskImaging dosesAverage lifetime attributable riskRadiological imaging proceduresRed bone marrowRetrospective studyCancer patientsLung cancerAttributable riskCancer incidenceBilling codesIndividual patientsBone marrowBrain cancerImage guidance proceduresPelvic scanPatientsCancerOrgan dosesRadiotherapyDosesMedicare Cancer Screening in the Context of Clinical Guidelines
Maroongroge S, Yu J. Medicare Cancer Screening in the Context of Clinical Guidelines. American Journal Of Clinical Oncology 2018, 41: 339-347. PMID: 26886947, DOI: 10.1097/coc.0000000000000272.Peer-Reviewed Original ResearchConceptsCancer screeningScreening ratesFee-for-serviceColorectal cancer screening ratesBilling codesCancer screening ratesColorectal screening testsMedicare fee-for-serviceMedicare Part B beneficiariesMonte Carlo permutation methodMedicare FFS populationBeneficiaries per yearMedicare FFS programEvidence-based guidelinesScreening testRetrospective claims dataProstate cancer screeningPublic health issueMammography ratesFFS populationScreening trendsMedicare populationClaims dataGuideline publicationPatient preferences
2017
The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity
Sigakis M, Leffert L, Mirzakhani H, Sharawi N, Rajala B, Callaghan W, Kuklina E, Creanga A, Mhyre J, Bateman B. The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity. Obstetric Anesthesia Digest 2017, 37: 16-17. DOI: 10.1097/01.aoa.0000512008.03839.93.Peer-Reviewed Original ResearchMassachusetts General HospitalPositive predictive valueMaternal morbiditySevere maternal complicationsSevere maternal morbidityHospital discharge dataMichigan Health SystemMaternal complicationsGeneral HospitalDiseases codesBilling codesAcademic centersPredictive valueICD codesHealth systemMorbidityPresent studyDischarge dataComplicationsHospital
2016
The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity
Sigakis MJ, Leffert LR, Mirzakhani H, Sharawi N, Rajala B, Callaghan WM, Kuklina EV, Creanga AA, Mhyre JM, Bateman BT. The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity. Anesthesia & Analgesia 2016, 123: 731-738. PMID: 27387839, PMCID: PMC7481827, DOI: 10.1213/ane.0000000000001436.Peer-Reviewed Original ResearchConceptsICD-9-CM codesSevere maternal morbidityPositive predictive valueMaternal morbidityMassachusetts General HospitalMichigan Health SystemGeneral HospitalClinical categoriesHealth systemCorresponding medical chartsConfidence intervalsLower confidence limitAnesthesia complicationsDelivery hospitalizationsObstetric categoryDelivery admissionMedical chartsDischarge diagnosisDiseases codesClinical dataLaboratory valuesBilling codesInternational ClassificationMorbidityBilling records
2015
ICD-9 diagnosis codes have poor sensitivity for identification of preexisting comorbidities in traumatic fracture patients
Samuel AM, Lukasiewicz AM, Webb ML, Bohl DD, Basques BA, Davis KA, Grauer JN. ICD-9 diagnosis codes have poor sensitivity for identification of preexisting comorbidities in traumatic fracture patients. Journal Of Trauma And Acute Care Surgery 2015, 79: 622-630. PMID: 26402537, DOI: 10.1097/ta.0000000000000805.Peer-Reviewed Original ResearchConceptsICD-9 diagnosis codesNational Trauma Data BankInjury Severity ScoreProximal tibia fracturesBilling codesTibia fracturesDiagnosis codesOdds ratioSurgeons National Trauma Data BankICD-9 billing codesTraumatic fracture patientsPrevious myocardial infarctionTrauma Data BankICD-9 diagnosisMultivariate logistic regressionLarge national databaseICD-9 codingAdministrative billing codesFracture patientsIndividual comorbiditiesPatient comorbiditiesComorbidity diagnosesProspective studyTrauma populationMyocardial infarction
2010
Extracting timing and status descriptors for colonoscopy testing from electronic medical records
Denny J, Peterson J, Choma N, Xu H, Miller R, Bastarache L, Peterson N. Extracting timing and status descriptors for colonoscopy testing from electronic medical records. Journal Of The American Medical Informatics Association 2010, 17: 383-388. PMID: 20595304, PMCID: PMC2995656, DOI: 10.1136/jamia.2010.004804.Peer-Reviewed Original ResearchConceptsElectronic medical recordsMedical recordsColorectal cancer screening ratesCRC screening statusCancer screening ratesManual reviewStatus indicatorsHealth services researchersColonoscopy testingEMR notesTypes of CRCScreening statusScreening ratesColonoscopy screeningBilling codesUseful adjunctGold standardElectronic recordsColonoscopyPatientsServices researchersFurther investigationRandom sampleTemporal expression
2009
Development of a natural language processing system to identify timing and status of colonoscopy testing in electronic medical records.
Denny J, Peterson J, Choma N, Xu H, Miller R, Bastarache L, Peterson N. Development of a natural language processing system to identify timing and status of colonoscopy testing in electronic medical records. AMIA Annual Symposium Proceedings 2009, 2009: 141. PMID: 20351837, PMCID: PMC2815478.Peer-Reviewed Original ResearchConceptsNatural language processingNatural language processing systemsElectronic medical recordsLanguage processing systemNLP systemsIdentifier systemLanguage processingMedical recordsProcessing systemElectronic textsColorectal cancer screening ratesCancer screening ratesPrimary care populationColonoscopy testingScreening ratesCare populationBilling codesQueriesColonoscopySystemStatus indicatorsAlgorithmCodeProcessingStatus
1999
Comparing AMI Mortality Among Hospitals in Patients 65 Years of Age and Older
Krumholz H, Chen J, Wang Y, Radford M, Chen Y, Marciniak T. Comparing AMI Mortality Among Hospitals in Patients 65 Years of Age and Older. Circulation 1999, 99: 2986-2992. PMID: 10368115, DOI: 10.1161/01.cir.99.23.2986.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionMyocardial infarctionWhite blood cell countPatients 65 yearsSystolic blood pressureCongestive heart failureMedical chart reviewReceiver-operating characteristic curveBlood cell countRisk-adjusted outcomesYears of ageAdministrative billing codesRisk-adjustment modelsHospital outcomesSerum creatinineChart reviewDerivation cohortHeart failurePatient characteristicsBlood pressureCardiac arrestValidation cohortCandidate predictor variablesAMI mortalityBilling codes
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply