2023
Clinical Research Information Systems
Nadkarni P. Clinical Research Information Systems. Health Informatics 2023, 111-126. DOI: 10.1007/978-3-031-27173-1_7.Peer-Reviewed Original Research
2019
Clinical Research Information Systems
Nadkarni P. Clinical Research Information Systems. Health Informatics 2019, 171-190. DOI: 10.1007/978-3-319-98779-8_9.Peer-Reviewed Original Research
2016
Chapter 6 Clinical Research Information Systems: Using Electronic Health Records for Research
Nadkarni P. Chapter 6 Clinical Research Information Systems: Using Electronic Health Records for Research. 2016, 129-142. DOI: 10.1016/b978-0-12-803130-8.00006-3.Peer-Reviewed Original ResearchClinical study data management systemsElectronic health recordsHealth recordsData management systemPersonal health recordsService requestsCentralized managementManagement systemType of systemClinical research dataPatient-reported outcomesPragmatic clinical trialsQuality improvement initiativesResearch dataGenomic dataClinical trialsClinical dataPractical issuesInteroperationLimited situationsWorkflowResearch projectRequestsSystemDataChapter 11 Conclusions: The Learning Health System of the Future
Nadkarni P. Chapter 11 Conclusions: The Learning Health System of the Future. 2016, 205-216. DOI: 10.1016/b978-0-12-803130-8.00011-7.Peer-Reviewed Original ResearchLearning health systemEnterprise Resource PlanningBusiness process reengineeringProcess reengineeringKnowledge managementAbility of humansResource planningBusiness worldProbability of successPractical issuesReengineeringHealthcare systemIdeaSystemEmployer relationsSame experienceIssuesShare of failuresIndividual dimensionsChapter 5 Software for Patient Care Versus Software for Clinical Research Support: Similarities and Differences
Nadkarni P. Chapter 5 Software for Patient Care Versus Software for Clinical Research Support: Similarities and Differences. 2016, 115-128. DOI: 10.1016/b978-0-12-803130-8.00005-1.Peer-Reviewed Original ResearchElectronic health record systemsClinical study data management systemsData management systemHealth record systemsData capture systemKind of systemData modelRedundant effortsClinical research supportManagement systemRecord systemSingle institutionStudy protocolCapture systemSoftwareMultiple institutionsSubject recruitmentStudy configurationSystemTransactionsDifferencesHuman population
2014
Chapter 2 Data Integration: An Overview
Nadkarni P, Marenco L. Chapter 2 Data Integration: An Overview. 2014, 15-47. DOI: 10.1016/b978-0-12-401678-1.00002-6.Peer-Reviewed Original ResearchIntegration effortsIntermediary softwareSeamless accessData integration strategyPhysical integrationVirtual integrationData integrationTypes of dataData elementsLogical integrationSource systemSingle large organizationLarge organizationsSingle resourceUsersMultiple sourcesIntegration strategyIntegrationFormal sequenceQueriesMetadataSoftwareStorage technologiesRedundancySystem
2012
Requirements for guidelines systems: implementation challenges and lessons from existing software-engineering efforts
Shah H, Allard R, Enberg R, Krishnan G, Williams P, Nadkarni P. Requirements for guidelines systems: implementation challenges and lessons from existing software-engineering efforts. BMC Medical Informatics And Decision Making 2012, 12: 16. PMID: 22405400, PMCID: PMC3342141, DOI: 10.1186/1472-6947-12-16.Peer-Reviewed Original ResearchConceptsSoftware-engineering effortsSoftware engineering effortGuideline systemProduction-quality systemClinical decision support systemClinical guideline systemsDecision support systemWorkflow domainsAdditional requirementsNon-biomedical fieldsSupport systemImplementation perspectiveSuch requirementsImplementation viewpointSuch systemsProduction system robustnessImplementation challengesSimilar workRequirementsPrevious workSimilar problemsEffective designStudy of examplesSystemImplementersClinical Research Information Systems
Nadkarni P, Marenco L, Brandt C. Clinical Research Information Systems. Health Informatics 2012, 135-154. DOI: 10.1007/978-1-84882-448-5_8.Peer-Reviewed Original ResearchClinical research information systemResearch Information SystemInformation systemsNew open-source systemSpecialized software applicationsSystematic requirements analysisOpen source systemsSoftware applicationsRequirements analysisElectronic medical record systemVendor modelInformatics componentsMedical record systemHost of functionsData entryRecord systemPatient monitoringClinical researchClinical research enterpriseProtocol managementPatient recruitmentUsabilitySystemInformaticiansIssues
2011
Web-browser encryption of personal health information
Morse R, Nadkarni P, Schoenfeld D, Finkelstein D. Web-browser encryption of personal health information. BMC Medical Informatics And Decision Making 2011, 11: 70. PMID: 22073940, PMCID: PMC3276430, DOI: 10.1186/1472-6947-11-70.Peer-Reviewed Original ResearchConceptsPersonal health informationRemote data entryWeb browserSensitive informationData centersHealth informationData entryHealth recordsUnprecedented amountPatient dataPatient confidentialityFinancial lossesClinical dataInformationMedical conditionsEncryptionServerBrowserClinical researchEffective medical practiceRange of situationsConfidentialityAccessSystemMedical practiceInteroperability and Integration Considerations for a Process-Oriented Clinical Decision Support System
Shah H, Krishnan G, Williams P, Vogler A, Allard R, Nadkarni P. Interoperability and Integration Considerations for a Process-Oriented Clinical Decision Support System. 2011, 1: 437-442. DOI: 10.1109/services.2011.14.Peer-Reviewed Original ResearchClinical decision support systemDecision support systemElectronic medical record systemSupport systemWeb services technologyTwo-way data exchangeSet of interfacesService technologyData exchangeOpen sourceMedical record systemRecord systemChallenges of integrationIntegration considerationsIntegrationInteroperabilitySystemInitiative projectChallengesFunctionalityServicesTechnologySetInterfaceProjectMetadata-driven Software Systems in Biomedicine, Designing Systems that can adapt to Changing Knowledge
Nadkarni P. Metadata-driven Software Systems in Biomedicine, Designing Systems that can adapt to Changing Knowledge. Health Informatics 2011 DOI: 10.1007/978-0-85729-510-1.Peer-Reviewed Original ResearchSoftware systemsClinical study data management systemsBiomedical database systemsData management systemResearch support systemSoftware developmentDatabase schemaDatabase systemsExtensible designSoftware historyDesigning systemSupport systemManagement systemSuch systemsDevelopment skillsElectronic medical recordsNon-trivial examplesNew systemProblems oneBest systemDetailed projectMetadataOntologyCase studySystem
2006
Guidelines for the effective use of entity–attribute–value modeling for biomedical databases
Dinu V, Nadkarni P. Guidelines for the effective use of entity–attribute–value modeling for biomedical databases. International Journal Of Medical Informatics 2006, 76: 769-779. PMID: 17098467, PMCID: PMC2110957, DOI: 10.1016/j.ijmedinf.2006.09.023.Peer-Reviewed Original Research
2004
Managing Complex Change in Clinical Study Metadata
Brandt CA, Gadagkar R, Rodriguez C, Nadkarni PM. Managing Complex Change in Clinical Study Metadata. Journal Of The American Medical Informatics Association 2004, 11: 380-391. PMID: 15187070, PMCID: PMC516245, DOI: 10.1197/jamia.m1511.Peer-Reviewed Original ResearchConceptsMetadata managementClinical study data management systemsHigh-level specificationData management systemProduction rule systemMiddleware enginesUse casesMetadata modificationCentralized informationStudy metadataManagement systemMetadataInformationSubschemaSystemSoftwareSpecificationEngineCapabilitySpecific typesManagement
2003
TrialDB: A web-based Clinical Study Data Management System.
Brandt CA, Deshpande AM, Lu C, Ananth G, Sun K, Gadagkar R, Morse R, Rodriguez C, Miller PL, Nadkarni PM. TrialDB: A web-based Clinical Study Data Management System. AMIA Annual Symposium Proceedings 2003, 2003: 794. PMID: 14728299, PMCID: PMC1480035.Peer-Reviewed Original ResearchConceptsClinical study data management systemsData management systemClass of softwareManagement systemPre-existing softwareWeb-based technologiesOpen source formDatabase engineClinical domainsSuch softwareData managementCentralized managementDifferent clinical domainsChallenging taskSuch systemsValue modelingSoftwareRequisite functionalityIntranetInternetDiverse typesSystemTaskDomainEngine
2002
Metadata-driven creation of data marts from an EAV-modeled clinical research database
Brandt CA, Morse R, Matthews K, Sun K, Deshpande AM, Gadagkar R, Cohen DB, Miller PL, Nadkarni PM. Metadata-driven creation of data marts from an EAV-modeled clinical research database. International Journal Of Medical Informatics 2002, 65: 225-241. PMID: 12414020, DOI: 10.1016/s1386-5056(02)00047-3.Peer-Reviewed Original ResearchConceptsData martClinical study data management systemsTransaction-oriented systemsData management systemClinical research databaseDatabase schemaEntity attributesAnalytical processingHuman interpretationStudy metadataMetadataManagement systemArbitrary numberData entrySuch dataBrowsingValue modelSchemaMartHigher-level groupingsSystemDataProcessingDatabaseCreationMetadata-driven Ad Hoc Query of Patient Data
Deshpande AM, Brandt C, Nadkarni PM. Metadata-driven Ad Hoc Query of Patient Data. Journal Of The American Medical Informatics Association 2002, 9: 369-382. PMID: 12087118, PMCID: PMC346624, DOI: 10.1197/jamia.m1034.Peer-Reviewed Original ResearchConceptsClinical study data management systemsClinical patient record systemsQuery interfaceAd-Hoc QueriesData management systemWeb-based platformPatient record systemManagement systemClinical studiesRecord systemMetadataStandardized therapeutic interventionsUnderlying clinical conditionSystem operationNon-research settingsClinical parametersPatient managementClinical conditionsQueriesPortingTherapeutic interventionsInterfaceSystemPlatformAD
2000
Integration of a hematopoietic progenitor cell program using the ACT/DB database system
Perrotta P, Nadkarni P. Integration of a hematopoietic progenitor cell program using the ACT/DB database system. Computer Methods And Programs In Biomedicine 2000, 61: 195-207. PMID: 10710182, DOI: 10.1016/s0169-2607(99)00038-3.Peer-Reviewed Original ResearchConceptsClient-server databaseComprehensive software systemSQL Server databaseDiverse data requirementsWeb-based technologiesData entry formsSoftware systemsServer databaseDatabase systemsInformation technologyMicrosoft AccessControl functionalityEntry formData requirementsTechnologyInternetDatabaseQuality assuranceOracleDeploymentSoftwareSystemFunctionalityRequirementsProcessing