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| Identifying patterns of health care utilization among physical elder abuse victims using Medicare data and legally adjudicated cases | |
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| Investigator (PI): | Rosen, Anthony |
| Performing Organization (PO): |
(Current): Cornell University, Weill Cornell Medical College, Department of Emergency Medicine / (212) 746-0780 |
| Supporting Agency (SA): | National Institutes of Health (NIH), National Institute on Aging (NIA) |
| Initial Year: | 2018 |
| Final Year: | 2023 |
| Record Source/Award ID: | RePorter/R01AG060086 |
| Funding: | 2018 Award Amount: $496,662 |
| Award Type: | Grant |
| Abstract: | The overarching 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 a National Institute on Aging (NIA) Grant for Early Medical/Surgical Specialists' Transition to Aging Research (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 emergency department (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 multidisciplinary 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. |
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| Country: | United States |
| State: | New York |
| Zip Code: | 10065 |
| UI: | 20191413 |
| Project Status: | Ongoing |