Measuring Neonatal Regionalization
测量新生儿区域化
基本信息
- 批准号:10668862
- 负责人:
- 金额:$ 74.53万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-04-01 至 2028-02-29
- 项目状态:未结题
- 来源:
- 关键词:AddressAdministratorAdultBackCaliforniaCaringCharacteristicsChronic lung diseaseClinicalDataData SetData SourcesDimensionsEffectivenessEquityEthnic OriginEthnic PopulationEvolutionFamilyFundingGeographic FactorGeographyGestational AgeGoalsGuidelinesHealthHealth ServicesHealth systemHospital AdministratorsHospitalsIndividualInequityInfantInfant CareInstitutionInsuranceInsurance CarriersJointsLeadLength of StayLinkMachine LearningMapsMathematicsMeasuresMethodologyMethodsModelingMorbidity - disease rateNecrotizing EnterocolitisNeonatalNeonatal Intensive Care UnitsObservational StudyOutcomeOutputPathway AnalysisPatient CarePatient DischargePatientsPatternPatterns of CarePerformancePerinatalPerinatal CarePolicy MakerPopulationPositioning AttributePremature InfantProviderQuality of CareRaceRecommendationRecordsResearchResearch InfrastructureResearch PersonnelResourcesRetinopathy of PrematurityRiskSamplingScienceServicesShapesStructural RacismStructureSystemTechniquesTestingTimeUnited StatesUnited States National Institutes of HealthVariantVery Low Birth Weight InfantVisualVisualizationWorkadverse outcomeanalytical toolcare deliverycare outcomesclinical caredensitydesignexperiencefinancial incentivegraph theoryhealth equityhigh risk infantimprovedinnovationintraventricular hemorrhagemachine learning algorithmmortalityneonatal deathneonatal outcomenovelpopulation basedpostnatalprimary outcomesecondary outcomesocialsocial factorstool
项目摘要
Care and outcomes for the 60,000 very low-birth-weight (VLBW; <1500g) infants born annually in the United
States varies widely. National guidelines recommend that care be organized along hierarchical regionalized care
delivery networks, but too often these vulnerable infants are born in hospitals whose capabilities don't match
patient need. This necessitates postnatal transfer which has been associated with excess morbidity and
mortality. To date, research on regional care networks has been thwarted by a lack of appropriate linked data
sets and mathematical tools to understand care network characteristics and their effect on neonatal outcomes.
We propose to bridge this gap and advance health outcomes science by gaining a deep understanding of
network characteristics and their links to clinical care and outcomes. We will accomplish this by using linked data
sets, not available elsewhere, that allow for analysis of the individual and joint contributions of multi-level factors,
including network factors on clinical outcomes. In addition, we will apply network analysis, a branch of graphical
mathematics to visually display and quantify regionalized care network characteristics. We propose a large, near
population-scale, observational study to analyze routinely collected data from 2010 to 2020 from >290,000 VLBW
infants (>50% of all VLBW infants in the United States) in ~520 NICUs using linked vital records and patient
discharge data from 17 states. This study is designed to achieve 3 specific aims:
1) Quantify regionalization and structure of transfer networks for VLBW infants across the United States;
2) Test the association of network structure with clinical quality of care and outcomes; and
3) Model optimized structure of perinatal transfers networks.
Our analyses will employ network analysis as an innovative tool to measure care regionalization focusing on a
high impact primary outcome (survival without major morbidity), as a substantive departure from prior work.
Machine learning will be used to provide information on optimal network structures in terms of effectiveness,
equity and efficiency. These models will reveal how networks would need to be modified to satisfy optimization
goals and reveal potential trade-offs. We have a long track record of impactful research funded by the National
Institute of Health using this data. We also have an opportunity to investigate more granular questions in
California (140 NICUs), which has unique existing linkages to maternal and infant clinical and transport data. We
expect our research to have an immediate positive impact because it is designed to result in actionable
information for policy makers, administrators and clinicians to improve perinatal care delivery and equity.
美国每年出生的6万名极低出生体重(VLBW; <1500g)婴儿的护理和结局
项目成果
期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jochen Profit其他文献
Jochen Profit的其他文献
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{{ truncateString('Jochen Profit', 18)}}的其他基金
Revealing and Resolving Institutional Racism in the NICU
揭示并解决新生儿重症监护病房中的制度性种族主义
- 批准号:
10743828 - 财政年份:2023
- 资助金额:
$ 74.53万 - 项目类别:
A Dashboard of Racial/Ethnic Disparity in Care Provided by NICUs
NICU 提供的护理中种族/民族差异的仪表板
- 批准号:
9029857 - 财政年份:2015
- 资助金额:
$ 74.53万 - 项目类别:
A Dashboard of Racial/Ethnic Disparity in Care Provided by NICUs
NICU 提供的护理中种族/民族差异的仪表板
- 批准号:
9188087 - 财政年份:2015
- 资助金额:
$ 74.53万 - 项目类别:
Development and Validation of a Scorecard of Neonatal Intensive Care Quality
新生儿重症监护质量记分卡的开发和验证
- 批准号:
7501303 - 财政年份:2007
- 资助金额:
$ 74.53万 - 项目类别:
Development and Validation of a Scorecard of Neonatal Intensive Care Quality
新生儿重症监护质量记分卡的开发和验证
- 批准号:
8111934 - 财政年份:2007
- 资助金额:
$ 74.53万 - 项目类别:
Development and Validation of a Scorecard of Neonatal Intensive Care Quality
新生儿重症监护质量记分卡的开发和验证
- 批准号:
7907780 - 财政年份:2007
- 资助金额:
$ 74.53万 - 项目类别:
Development and Validation of a Scorecard of Neonatal Intensive Care Quality
新生儿重症监护质量记分卡的开发和验证
- 批准号:
7667455 - 财政年份:2007
- 资助金额:
$ 74.53万 - 项目类别:
Development and Validation of a Scorecard of Neonatal Intensive Care Quality
新生儿重症监护质量记分卡的开发和验证
- 批准号:
7301700 - 财政年份:2007
- 资助金额:
$ 74.53万 - 项目类别:
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