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A Skeletal Atlas of Elder Abuse: Establishing Markers of Physical Abuse and Developing a Digital Diagnostic Tool for Education and Screening

Award Information

Award #
Funding Category
Competitive Discretionary
Congressional District
Funding First Awarded
Total funding (to date)

Description of original award (Fiscal Year 2020, $1,035,328)

The goals of this study are to 1) establish a skeletal atlas of elder abuse; 2) address the critical gap in current knowledge of how the aging process affects healing times following a fracture; 3) aid in education and improved criminal justice procedures; and 4) elucidate how differentiation of physical abuse from accidental injury contributes to the identification of modifiable risk factors for prevention of abuse. This project will provide a new standard of scoring and callus formation, demonstrate healing rates and stages in bone in individuals older than 60, and develop a baseline for diagnosing physical abuse in elders. The project is intended to produce physical and radiographic standards built upon forensic research, as well as an advanced bioinformatics approach to diagnosis, designed with usability and availability as key features.

During Phase 1 of the project, researchers will obtain and analyze radiographs and bone samples showing fractures at varying stages of healing from at least 250 cases of elder abuse and 300 witnessed accidental falls. Radiographic and skeletal samples will be obtained from victims of elder abuse that are investigated by the Office of the Medical Examiner in Maricopa County, Arizona, using the following criteria: decedent must 1) have been admitted for full exam, 2) be associated with an Adult Protective Services and/or law enforcement investigation, and 3) present with skeletal fractures. To establish a comparative baseline of those fractures most likely to occur in accidental falls, radiographic and skeletal samples from cases of witnessed falls will also be analyzed.

In Phase 2, collected data and physical exemplars will be scanned and incorporated into a 3D atlas and an associated digital diagnostic tool, driven by Bayesian probability modeling and machine-learning techniques, to be used in training and diagnosis in clinical and medico-legal settings.

In addition to peer-reviewed scholarly products, the digital diagnostic tool will be presented in seminars and workshops at national meetings for feedback and training of clinical and medicolegal professionals.

Note: This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF

Date Created: September 20, 2020