Identifying Patterns of Health Care Utilization among Physical Elder Abuse Victims Using Medicare Data and Legally Adjudicated Cases
使用医疗保险数据和法律裁决案件确定老年人身体虐待受害者的医疗保健利用模式
基本信息
- 批准号:10402860
- 负责人:
- 金额:$ 37.69万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-09-15 至 2025-04-30
- 项目状态:未结题
- 来源:
- 关键词:Accident and Emergency departmentAdultAgeAlgorithmsAmbulatory CareAreaAutomobile DrivingCase SeriesCharacteristicsChildChild AbuseChild Abuse and NeglectClinicalContinuity of Patient CareControl GroupsDataDatabasesDetectionDevelopmentEarly InterventionEarly identificationEconomic BurdenElder AbuseElderlyEmergency MedicineEmergency department visitEnrollmentEthicsFamilyFractureFutureGleanGoalsGrantHealthHealth Care CostsHealth PersonnelHealth ProfessionalHealthcareHospital DepartmentsHospitalizationImpaired cognitionInfluentialsInjuryInterventionKnowledgeLegalLimb structureLinkMachine LearningMedicalMedicareMedicare claimMethodologyMorbidity - disease rateNursing HomesOutcomePatternPolicePoliciesPreventive servicePrimary Health CarePublic Health InformaticsResearchResearch SupportRoentgen RaysSeminalSeriesServicesSpecialistSuggestionTestingVictimizationVisitVulnerable PopulationsWorkX-Ray Computed Tomographyabuse victimadjudicateagedbasecomorbiditycomputer scienceconvictcostexperiencefunctional disabilityhealth assessmenthealth care service utilizationhealth economicshospital utilizationimprovedinformatics toolinnovationinsightintimate partner violencelegal casesmaxillofacialmedication compliancemembermetropolitanmortalitymultidisciplinaryperpetratorspreventprospectiveradiological imagingstatistics
项目摘要
PROJECT SUMMARY
The over-arching aim of this research is to: improve understanding of the patterns of health care utilization and
associated costs of physical elder abuse victims to improve early identification and intervention and to inform
policy. In our prior research, supported by an NIA GEMSSTAR and Beeson grant to PI Dr. Rosen, we
leveraged unique partnerships with prosecutors’ offices to comprehensively examine legal case files from more
than 200 victims in two large metropolitan areas, representing the largest retrospective series of legally
adjudicated physical elder abuse cases ever examined. For the proposed study, we plan to link these cases,
for which we have done extensive clinical analysis, to Medicare claims data. The Specific Aims of this proposal
are: (1) To use Medicare claims to describe rates and patterns of health care utilization of victims before and
after detection, with a focus on potentially missed opportunities by health professionals to identify abuse and
differences based on victim characteristics, (2) To compare rates and patterns of ED visits and hospitalizations
of physical elder abuse victims to control groups selected algorithmically from Medicare claims data, and (3) To
compare patterns of health care utilization other than EDs/hospitals between victims and controls. The
proposed research will provide important insight into the patterns of health care utilization for physical elder
abuse victims, focusing on whether missed opportunities exist and suggestive patterns emerge. We plan to
employ sophisticated machine learning approaches to increase our ability to identify patterns suggestive of
physical elder abuse exposure. This will inform strategies for identification and intervention by health care
providers, and knowledge gleaned will support the future development of a health informatics tool to identify
potential victims. Findings on associated costs will help define the scope and impact of physical elder abuse.
This innovative approach leverages existing data gathered with NIA support and extrapolates from successful
research approaches in child abuse and intimate partner violence while expanding on them. As no additional
subjects will be prospectively enrolled as part of this research, we avoid many of the ethical concerns typical in
elder mistreatment work. Our multi-disciplinary team of experts in elder abuse, child abuse and neglect,
intimate partner violence, and emergency medicine as well as specialists in statistics, health economics, and
computer science is uniquely able to conduct this research. Previously, we have done seminal work examining
health care usage and health-related outcomes of elder abuse victims by linking adult protective services and
police databases to health care data, which is highly relevant for this proposal. We also have deep experience
in using Medicare claims data and machine learning for research. The long-term goal of our research is to
leverage a better understanding of health care use by elder abuse victims to improve the ability of health care
providers to identify, intervene, and prevent victimization and to inform policy changes to help this vulnerable
population.
项目总结
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Anthony Rosen其他文献
Anthony Rosen的其他文献
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{{ truncateString('Anthony Rosen', 18)}}的其他基金
Identifying Injury Patterns and Forensic Biomarkers Diagnostic of Physical Elder Abuse
识别老年人身体虐待的伤害模式和法医生物标志物诊断
- 批准号:
10400512 - 财政年份:2021
- 资助金额:
$ 37.69万 - 项目类别:
Identifying Patterns of Health Care Utilization among Physical Elder Abuse Victims Using Medicare Data and Legally Adjudicated Cases
使用医疗保险数据和法律裁决案件确定老年人身体虐待受害者的医疗保健利用模式
- 批准号:
10224085 - 财政年份:2018
- 资助金额:
$ 37.69万 - 项目类别:
Identifying Injury Patterns and Forensic Biomarkers Diagnostic of Physical Elder Abuse
识别老年人身体虐待的伤害模式和法医生物标志物诊断
- 批准号:
9230105 - 财政年份:2016
- 资助金额:
$ 37.69万 - 项目类别:
Improving Recognition of Elder Abuse through Analysis of Highly Adjudicated Cases
通过分析高度判决的案件提高对虐待老年人的认识
- 批准号:
8916538 - 财政年份:2014
- 资助金额:
$ 37.69万 - 项目类别:
Improving Recognition of Elder Abuse through Analysis of Highly Adjudicated Cases
通过分析高度判决的案件提高对虐待老年人的认识
- 批准号:
8757750 - 财政年份:2014
- 资助金额:
$ 37.69万 - 项目类别:
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