2024
Learning implementation of a guideline based decision support system to improve hypertension treatment in primary care in China: pragmatic cluster randomised controlled trial
Song J, Wang X, Wang B, Ge Y, Bi L, Jing F, Jin H, Li T, Gu B, Wang L, Hao J, Zhao Y, Liu J, Zhang H, Li X, Li J, Ma W, Wang J, Normand S, Herrin J, Armitage J, Krumholz H, Zheng X. Learning implementation of a guideline based decision support system to improve hypertension treatment in primary care in China: pragmatic cluster randomised controlled trial. The BMJ 2024, 386: e079143. PMID: 39043397, PMCID: PMC11265211, DOI: 10.1136/bmj-2023-079143.Peer-Reviewed Original ResearchConceptsClinical decision support systemsPrimary care practicesElectronic health recordsIntervention groupSystolic blood pressurePrimary careCare practicesBlood pressure <Health recordsPragmatic cluster randomised controlled trialCluster randomised controlled trialImproving hypertension treatmentPrimary care settingBlood pressure control ratesBlood pressureProportion of visitsProportion of participantsRandomised controlled trialsSystolic blood pressure <Control groupInjurious fallsRelated visitsCare settingsDiastolic blood pressure <Follow-upBridging clinical informatics and implementation science to improve cancer symptom management in ambulatory oncology practices: experiences from the IMPACT consortium
McCleary N, Merle J, Richardson J, Bass M, Garcia S, Cheville A, Mitchell S, Jensen R, Minteer S, Austin J, Tesch N, DiMartino L, Hassett M, Osarogiagbon R, Wong S, Schrag D, Cella D, Smith A, Smith J, Cella D, Cheville A, Hassett M, Osarogiagbon R, Schrag D, Wong S, Kroner B, Smith A, DiMartino L, Garcia S, Griffin J, Jensen R, Mitchell S, Ruddy K, Smith J, Yanez B, Bian J, Dizon D, Hazard-Jenkins H, Ardini M, Ahrens P, Austin J, Barrett F, Bass M, Begnoche M, Cahue S, Caron K, Chlan L, Coughlin A, Cronin C, Dias S, Faris N, Flores A, Garcia M, Hemming K, Herrin J, Hodgdon C, Kircher S, Kroenke K, Lam V, Lancki N, H Q, Mallow J, McCleary N, Norton W, O'Connor M, Pachman D, Pearson L, Penedo F, Podratz J, Popovic J, Preiss L, Rahman P, Redmond S, Reich J, Richardson J, Richardson K, Ridgeway J, Rutten L, Schaepe K, Scholtens D, Poirier-Shelton T, Silberman P, Simpson J, Tasker L, Tesch N, Tofthagen C, Tramontano A, Tyndall B, Uno H, Wehbe F, Weiner B. Bridging clinical informatics and implementation science to improve cancer symptom management in ambulatory oncology practices: experiences from the IMPACT consortium. JAMIA Open 2024, 7: ooae081. PMID: 39234146, PMCID: PMC11373565, DOI: 10.1093/jamiaopen/ooae081.Peer-Reviewed Original ResearchElectronic patient-reported outcomesElectronic health recordsClinical informaticsImplementation scienceImplementation of electronic patient-reported outcomesElectronic health record designElectronic health record systemsImplementation strategiesCancer symptom managementSystematic symptom assessmentAmbulatory oncology settingAmbulatory oncology practicesManagement of symptomsPatient-reported outcomesEHR functionsEPRO dataCancer symptomsSymptom managementIS researchHealth recordsImplementation scientistsPragmatic trialOncology settingInformatics implementationSymptom assessmentThe PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID
Krumholz H, Sawano M, Bhattacharjee B, Caraballo C, Khera R, Li S, Herrin J, Coppi A, Holub J, Henriquez Y, Johnson M, Goddard T, Rocco E, Hummel A, Al Mouslmani M, Putrino D, Carr K, Carvajal-Gonzalez S, Charnas L, De Jesus M, Ziegler F, Iwasaki A. The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID. The American Journal Of Medicine 2024 PMID: 38735354, DOI: 10.1016/j.amjmed.2024.04.030.Peer-Reviewed Original ResearchLC trialPROMIS-29Participants' homesTargeting viral persistencePlacebo-controlled trialDouble-blind studyElectronic health recordsCore Outcome MeasuresLong COVIDEQ-5D-5LRepeated measures analysisEvidence-based treatmentsPhase 2Double-blindParticipant-centred approachStudy drugPrimary endpointSecondary endpointsCommunity-dwellingHealth recordsHealthcare utilizationContiguous US statesViral persistencePatient groupDrug treatment
2023
Disparities in electronic health record portal access and use among patients with cancer
Griffin J, Kroner B, Wong S, Preiss L, Smith A, Cheville A, Mitchell S, Lancki N, Hassett M, Schrag D, Osarogiagbon R, Ridgeway J, Cella D, Jensen R, Flores A, Austin J, Yanez B, Cella D, Cheville A, Hassett M, Osarogiagbon R, Schrag D, Wong S, Kroner B, Smith A, DiMartino L, Garcia S, Griffin J, Jensen R, Mitchell S, Ruddy K, Smith J, Yanez B, Bian J, Dizon D, Hazard-Jenkins H, Ardini M, Ahrens P, Austin J, Barrett F, Bass M, Begnoche M, Cahue S, Caron K, Chlan L, Coughlin A, Cronin C, Dias S, Faris N, Flores A, Garcia M, Hemming K, Herrin J, Hodgdon C, Kircher S, Kroenke K, Lam V, Lancki N, Mai Q, Mallow J, McCleary N, Norton W, Connor M, Pachman D, Pearson L, Penedo F, Podratz J, Popovic J, Preiss L, Rahman P, Redmond S, Reich J, Richardson J, Richardson K, Ridgeway J, Rutten L, Schaepe K, Scholtens D, Poirier-Shelton T, Silberman P, Simpson J, Tasker L, Tesch N, Tofthagen C, Tramontano A, Tyndall B, Uno H, Wehbe F, Weiner B. Disparities in electronic health record portal access and use among patients with cancer. Journal Of The National Cancer Institute 2023, djad225. PMID: 37930884, DOI: 10.1093/jnci/djad225.Peer-Reviewed Original ResearchPortal accessPortal useClinical encountersRural-Urban Commuting Area codesIntervention implementationMultiple logistic regression modelManagement of symptomsCancer care disparitiesLogistic regression modelsElectronic health recordsEligible patientsCancer patientsSymptom surveillanceHigher oddsLower oddsCare disparitiesPatientsPersistent usersSociodemographic factorsYounger ageTreatment ConsortiumHealth recordsHealthcare qualityCommunity surveyArea codes
2021
Association between 30-day readmission rates and health information technology capabilities in US hospitals
Elysee G, Yu H, Herrin J, Horwitz LI. Association between 30-day readmission rates and health information technology capabilities in US hospitals. Medicine 2021, 100: e24755. PMID: 33663091, PMCID: PMC7909153, DOI: 10.1097/md.0000000000024755.Peer-Reviewed Original ResearchConceptsRisk-standardized readmission ratesHealth IT capabilitiesLower readmission riskReadmission riskReadmission ratesHealth information technologyElectronic health recordsHospital dischargeRetrospective cross-sectional studyU.S. acute care hospitalsHealth recordsAcute care hospitalsCross-sectional studyFragmentation of careHospital-level risk-standardized readmission ratesOne-point increaseHospital Compare websiteHealth information technology capabilitiesCare hospitalOutcome measuresOutpatient providersUS hospitalsCare deliveryPatient accessClinical stakeholders
2011
How Good Are the Data? Feasible Approach to Validation of Metrics of Quality Derived From an Outpatient Electronic Health Record
Benin AL, Fenick A, Herrin J, Vitkauskas G, Chen J, Brandt C. How Good Are the Data? Feasible Approach to Validation of Metrics of Quality Derived From an Outpatient Electronic Health Record. American Journal Of Medical Quality 2011, 26: 441-451. PMID: 21926280, DOI: 10.1177/1062860611403136.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAmbulatory CareChildChild, PreschoolGuideline AdherenceHumansInfantMass ScreeningMedical Records Systems, ComputerizedOutcome and Process Assessment, Health CareOutpatientsPatient SafetyPediatricsPractice Guidelines as TopicQuality Indicators, Health CareQuality of Health CareReproducibility of Results
2006
Patient-Centeredness and Timeliness in a Primary Care Network: Baseline Analysis and Power Assessment for Detection of the Effects of an Electronic Health Record
Fleming NS, Herrin J, Roberts W, Couch C, Ballard DJ. Patient-Centeredness and Timeliness in a Primary Care Network: Baseline Analysis and Power Assessment for Detection of the Effects of an Electronic Health Record. Baylor University Medical Center Proceedings 2006, 19: 314-319. PMID: 17106491, PMCID: PMC1618751, DOI: 10.1080/08998280.2006.11928191.Peer-Reviewed Original ResearchAmbulatory electronic health recordElectronic health recordsHealth recordsCare networkAppointment timePatient satisfaction surveyPrimary care networkBaylor Health Care SystemAmbulatory care networkQuality of careHealthTexas Provider NetworkInstitute of MedicineHealth care systemAdditional survey itemsExcellent satisfactionPatient centerednessPatientsQuality careCare systemPhysician interactionBaseline performanceFinancial impactBaseline analysisDimensions of qualitySatisfaction survey