Developing i2b2 into a Health Innovation Platform for Clinical Decision Support in the Genomics Era
Developing i2b2 into a Health Innovation Platform for Clinical Decision Support in the Genomics Era
批准号:
9157994
负责人:
Samuel Jeffrey Aronson
金额:
$69.69万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-28 至 2020-08-31
关键词:
AlgorithmsArchitectureBig DataBiologyBiopsyCardiacCardiologyClinicalClinical DataComputer softwareDataData AnalyticsData ScienceData SourcesDatabasesDevelopmentEchocardiographyEcosystemElectrocardiogramElectronic Health RecordEnvironmentFamilyFormulationGeneticGenomicsGenotypeHealthHealthcareHeart DiseasesHospitalsImageInformaticsInformation SystemsInheritedIntellectual PropertyLabelLaboratoriesMedicalMedical centerMethodsModalityMonitorNamesPathologyPatientsPhenotypePopulationRecording of previous eventsResourcesRoleSymptomsSystemTechnologyTestingThallium Myocardial Perfusion Imaging Stress TestTimeVariantVendorabstractingbaseclinical careclinical decision-makingclinical effectcohortdigitalexperiencefallsgenomic platforminnovationinsightinteroperabilityopen sourceoperationoutcome predictionpatient registrypopulation basedprecision medicinesupport tools
中文摘要
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英文摘要
Project Summary/Abstract
Many outcome predictors used in precision medicine are based upon experience with
populations of previous patients who are similar in important ways. However, standard
Electronic Health Record systems (EHRs) seldom support real-time population queries and
therefore cannot administer precision medicine as part of their integrated decision support for
clinicians. Furthermore, the data upon which many precision medicine algorithms operate is not
available in standard EMRs because it comes from advanced genomics, imaging analytics, and
other data modalities which fall outside of the data domains of standard EHR platforms. We
propose developing Informatics for Integrating Biology and the Bedside (i2b2), a well-
established, open source, integrated, big data analytic platform that is currently used at over
140 hospitals and medical centers, to study phenotype/genotype comparisons and incorporate it
into the EHR using small, connected applications named Substitutable Medical Applications and
Reusable Technologies (SMART). We will take the Partners HealthCare genomics platform,
GeneInsight, and integrate its data into our Epic EHR workflow using i2b2. We will then test
specific decision support algorithms for inherited cardiac diseases. The resulting software will
be open source and allow integration of genomics-based, big data decision support algorithms
broadly into EHRs. We will also use these same data to provide decision support to laboratory
professionals who classify variants relative to their clinical effects. Standard methods of
representing these data will be used to make the algorithms transportable and universally
applicable. The Decision Support Apps that are created will be evaluated not only for their
potential impact upon clinical care, but also for their durability and adaptability to different
healthcare environments.
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