Measuring and improving data quality for clinical quality measure reliability
Measuring and improving data quality for clinical quality measure reliability
批准号:
9428949
负责人:
Nicole Gray Weiskopf
金额:
$14.27万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-15 至 2020-08-31
关键词:
AdministratorAffectAreaAwardBehaviorCardiologyCaringClinicalClinical DataClinical ResearchClinical assessmentsDataData QualityData SourcesDocumentationElectronic Health RecordEnsureEnvironmentError SourcesEvaluationFirst Independent Research Support and Transition AwardsFoundationsFunding MechanismsGoalsGoldHealth SciencesHealthcareHeart failureInstitutionInsurance CarriersInterventionInterviewK-Series Research Career ProgramsKnowledgeLeadLogicManualsMeasurementMeasuresMedical InformaticsMentorsMethodologyMethodsOregonPatient CarePatient Self-ReportPatientsPerformancePlanning TheoryPolicy MakerProcessProviderQuality of CareRecordsReportingResearchResearch PersonnelResearch Project GrantsResourcesSamplingScienceStructureSurveysTimeTrainingTreesTrustUnited States National Library of MedicineUniversitiesUpdateWorkbasebiomedical informaticscareercareer developmentclinical careclinical epidemiologyclinical predictorscomputerizeddata integrationelectronic structureexperiencehealth care deliveryhealth care qualityimprovedmemberpoint of careprofessortool
中文摘要
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英文摘要
Project Summary/Abstract
Research Project: Reliable electronic health record (EHR)-based clinical quality measures (CQMs) are
necessary for the assessment and measurement of healthcare quality and delivery. They are also a vital tool
for evaluating the impact of interventions meant to improve care. Unfortunately, stakeholders have limited
assurance of CQM reliability, due in part to problems with data quality. In order to ensure the reliability and, by
extension, the usefulness of automated EHR-based CQMs, I propose the following: 1) generate a better
understanding of the causal relationships between EHR data quality and CQM reliability; 2) provide
stakeholders with methods for the assessment of CQM reliability, based upon underlying data quality; and 3)
identify provider-approved interventions for improving EHR data quality in order to improve CQM reliability.
Career Goals: I am seeking a National Library of Medicine K01 Career Development Award in Biomedical
Informatics for two primary reasons. First, this award would provide me with an opportunity to become an
independent researcher through the protected time the award ensures and allow me to develop my expertise in
key subject matter and methodological areas. Second, through the proposed research I will provide
stakeholders with a deeper understanding of CQM reliability, methods to measure CQM reliability, and
approaches for improving CQM reliability through interventions at the point of care, enabling the improvement
of clinical care itself. My long-term goal is to become an expert in mixed-methods approaches for measuring
and improving the quality of EHR data, thereby ensuring reliable and valid reuse of these data to support
patient care, evaluation of patient care, and clinical research.
Career Development and Training: I am an assistant professor with the Department of Medical Informatics &
Clinical Epidemiology at Oregon Health & Science University. Through my department and mentors I have a
unique level of access to EHR data, an existing CQM calculation engine, and various clinical environments.
The career-development goal of this award period is to use these resources and the expertise of my mentors
to solidify my knowledge and methodological abilities in three primary areas: 1) EHR data quality assessment
and improvement, 2) mixed-methods approaches, and 3) healthcare delivery science. The projects, mentors,
and consultants included in this proposal were chosen to provide me with the experience, knowledge, and
expertise that will prepare me for a career as an independent researcher specializing in these areas and give
me the foundation upon which to apply for a traditional funding mechanism. Specifically, the aims of this
proposal have been developed to lead directly to EHR-based and documentation-level interventions intended
to improve EHR data quality, CQM reliability, and the quality of clinical care overall, which will be the subject of
an application building upon the work described here.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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依托单位:
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依托单位:
Operationalizing Machine Learning and Discrete Event Simulation Models to Improve Clinic Efficiency
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项目类别:
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资助金额:$32.73万
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依托单位:
Measuring and improving data quality for clinical quality measure reliability
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批准号:9761576
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项目类别:
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资助金额:$15.11万
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财政年份:2017
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负责人:Nicole Gray Weiskopf
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依托单位:
海外基金