A Novel Graph Processing Architecture to Ascertain & Monitor Care Coordination
A Novel Graph Processing Architecture to Ascertain & Monitor Care Coordination
批准号:
8753355
负责人:
Nicholas Dean Soulakis
金额:
$17.05万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-02 至 2017-07-31
关键词:
Abnormal coordinationAdmission activityAffectAlgorithmsArchitectureAtlasesCaringCharacteristicsClinicalCommunitiesComplexConsultDataData ElementDatabasesDevelopmentDieteticsElectronic Health RecordEngineeringEpidemiologyFamilyFutureGoalsGraphHealth PersonnelHealthcareHeart failureHome environmentHospital PersonnelHospitalizationHospitalsIndividualInformaticsInformation NetworksInpatientsInterventionInvestigationKnowledgeLeadLearningLiteratureMeasuresMedicaidMedicalMedical Care TeamMedical RecordsMedicineMentored Research Scientist Development AwardMethodologyMethodsMetricMonitorNatureOutcomeOutpatientsPathway AnalysisPatient AdmissionPatient EducationPatient ReadmissionPatientsPersonsPharmaceutical PreparationsPopulationPopulation SurveillancePreventionPreventive MedicinePrimary Health CareProcessProcess MeasurePublic HealthPublic Health InformaticsRecoveryReportingResearchResearch Project GrantsRiskSocial WorkSourceSpecific qualifier valueStructureSurveysSystemTelephoneTestingTrainingUnited States Agency for Healthcare Research and QualityUniversitiesWorkWorkplacebasebiomedical informaticscardiovascular disorder epidemiologycomparative effectivenesscostdesign and constructionexperienceflexibilityfollow-uphealth care qualityhealth information technologyhospital readmissionimprovedmedical schoolsmultidisciplinarynovelpatient populationprofessorprogramsroutine caresocial science researchsuccess
中文摘要
描述(由申请人提供):
精心策划的多学科护理可改善患者的治疗效果并降低医疗成本。包括CMS和AHRQ在内的联邦机构寻求在全国范围内加强护理协调,作为提高医疗保健质量的一种手段。然而,定义和衡量护理协调的能力仍然是一个难以捉摸的目标。AHRQ“护理协调措施地图集”建议护理协调措施取决于:1)跟踪基本数据元素的HIT系统。2)为临床医生和工作人员提供有效的工作流程。本研究的总体目标是通过将医疗保健参与者、交互和数据元素详尽编码为门诊和住院环境中的图形表示来提高护理协调的确定性。拟议研究的具体目标是:1)使用西北大学生物医学信息学核心(NUBIC)企业数据仓库(EDW),全面描述所有临床和非临床西北纪念医院(NMH)人员及其与患者的互动,记录在住院或门诊病历系统中。2)将医疗保健人员网络及其交互表示为护理协调图。3)通过回顾性图表分析,确定护理团队的重要特征,包括但不限于规模、组成和相互作用的强度,如何影响心力衰竭患者的再入院率。
候选人Nicholas Soulakis是西北大学Feinberg医学院预防医学助理教授。他在一般流行病学,公共卫生监测和调查,以及生物医学信息学的强大训练,使他能够追求一个研究议程,重点是在初级保健中使用新兴的卫生信息技术的公共卫生报告的新方法。该K01奖项为Soulakis博士提供了一个独特的机会,可以扩展到质量信息学和患者结局的新方向,更好地了解医疗保健网络的确定,并开发更全面的科学方法来了解住院患者人群的护理协调动态。它还将使他能够通过学习多样化的新方法来加强他的当前研究议程,以更好地量化个人及其医疗团队之间的复杂互动,并通过建立西北大学工程和社会科学研究社区之间的合作关系。Soulakis博士的长期目标是开发一个独立的研究项目,重点是1)了解协调良好的预防性护理如何改善整个医疗环境中的人群结果2)利用这些知识开发最有前途的多层次干预措施,以使用健康信息技术不断改善和监测医疗质量。
英文摘要
DESCRIPTION (provided by applicant):
Well-orchestrated, multidisciplinary care improves patient outcomes and decreases medical costs. Federal agencies including CMS and AHRQ seek to increase care coordination nationally as a means of improving healthcare quality. However, the ability to define and measure care coordination remains an elusive target. The AHRQ "Care Coordination Measures Atlas" suggests care coordination measures depend on: 1) HIT systems that track essential data elements. 2) Effective workflows for clinicians and staff. The overall goal of this research is to improve the ascertainment of care coordination through an exhaustive encoding of healthcare actors, interactions, and data elements into a graph representation across the ambulatory and inpatient setting. The specific aims of the proposed research are to: 1) Using the Northwestern University Biomedical Informatics Core (NUBIC) Enterprise Data Warehouse (EDW), comprehensively characterize all clinical and non-clinical Northwestern Memorial Hospital (NMH) personnel and their interactions with patients as documented in either inpatient or outpatient medical record systems. 2) Represent the network of health care personnel and their interactions as a care coordination graph. 3) Identify how important characteristics of care teams including but not limited to size, composition, and intensity of interaction effect patient readmission rates for heart failure patients through retrospective graph analysis.
The candidate, Nicholas Soulakis, is an Assistant Professor of Preventive Medicine at the Northwestern University Feinberg School of Medicine. His strong training in general epidemiology, public health surveillance and investigation, and biomedical informatics has allowed him to pursue a research agenda focused on novel methods of public health reporting using emerging health information technology in primary care. This K01 award provides a unique opportunity for Dr. Soulakis to expand into a new direction of quality informatics and patient outcomes, to better understand the ascertainment of healthcare networks, and to develop a more comprehensive scientific approach to understanding the dynamics of care coordination for hospitalized patient populations. It will also enable him to strengthen his curren research agenda by learning diverse, new methodologies to better quantify complex interactions between individuals and their healthcare teams and by building collaborative relationships among the Northwestern University engineering and social science research communities. This training will help Dr. Soulakis achieve his long-term goal of developing an independent research program that focuses on 1) understanding how well-coordinated, prevention focused care improves population outcomes across healthcare settings 2) using this knowledge to develop the most promising multi-level interventions to continuously improve and monitor medical quality using health information technology.
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会议论文
A Novel Graph Processing Architecture to Ascertain & Monitor Care Coordination
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批准号:9113071
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项目类别:
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资助金额:$15.52万
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财政年份:2014
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负责人:Nicholas Dean Soulakis
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依托单位: