Risk modeling and shared decision making for postpartum depression
Risk modeling and shared decision making for postpartum depression
批准号:
10252153
负责人:
Michael B. Laskoff
金额:
$44.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-07-21 至 2023-06-30
关键词:
AddressAffectAreaBusinessesChildChildbirthClinicalClinical DataComplexConceptionsConflict (Psychology)DataDecision AidDepression screenDevelopmentDiagnosisDiscipline of obstetricsElectronic Health RecordEvaluationEvidence based interventionFamilyFeelingFeeling hopelessFundingFutureGoalsGroup Health InsuranceGynecologyHealthHealth InsuranceHealth PersonnelHealth ProfessionalHealth SciencesHealth Services AccessibilityImpairmentInfant MortalityInterventionIrisLeadLicensingLifeMachine LearningMedicineMental DepressionMental HealthMethodsMissionModelingMothersNatural Language ProcessingNew York CityOutcomePatient riskPatient-Focused OutcomesPatientsPhasePostpartum DepressionPostpartum PeriodPregnancyPregnant WomenPrevention strategyPreventive treatmentPrimary PreventionProcessProviderPsychiatryResearchRiskSecondary PreventionSiteSmall Business Technology Transfer ResearchStressSymptomsTechniquesTestingWomanchild bearingclinical careclinical research sitecommercializationdeep learningdepression preventiondepressive symptomsdigitaldigital healthdisabilityeffectiveness clinical trialevidence baseexperienceheuristicshigh riskhospitalization ratesimprovedmachine learning algorithmmotherhoodnovelpatient stratificationphase 1 studypopulation healthpractice settingproject-based learningprospectiverisk prediction modelroutine screeningscreeningshared decision makingsocial stigmasoftware as a servicesupport toolstooltreatment choiceusabilityuser centered design
中文摘要
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英文摘要
PROJECT ABSTRACT
Postpartum depression (PPD) is a strikingly common and potentially life-threatening mental health condition,
affecting 1 in 5 mothers in the US. PPD poses serious health concerns, not only to mothers but also their children
and the family. PPD has been associated with increased infant mortality, higher rates of hospitalizations,
impaired mother-child attachment, developmental problems in children, and increased stress within families.
However, in reality, women who are at high risk for depression during the childbearing years are usually neither
identified nor treated. In addition, even when depression is detected by health professionals, women rarely obtain
assistance, despite the wide availability of treatment choices. In this project, we plan to leverage large-scale,
integrated electronic health record and claims from the New York City Clinical Data Research Network to develop
automated, scalable risk prediction models for PPD. We will also develop a digital shared decision-making (SDM)
tool for PPD treatment by working collaboratively with healthcare providers and patients. The PPD risk model
and the digital SDM tool for PPD treatment developed in this STTR Phase I project will be used to conduct a
future large, prospective, multi-site clinical effectiveness trial to test their feasibility and utility in routine clinical
care of women during the postpartum period.
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会议论文
Bioethical Considerations for Building, Evaluating, and Implementing Artificial Intelligence in Perinatal Mood and Anxiety Disorders
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批准号:10593284
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项目类别:
-
资助金额:$13.73万
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财政年份:2021
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负责人:Michael B. Laskoff
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依托单位:
Risk modeling and shared decision making for postpartum depression
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批准号:10454932
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项目类别:
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资助金额:$43.43万
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财政年份:2021
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负责人:Michael B. Laskoff
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依托单位:
海外基金