Abstract: Various embodiments are directed to simulating mechanisms of injury utilizing an objective impairment injury score risk model. A computing device may receive injury data from a user. The computing device may perform a security action that protects against unauthorized sharing of the injury data by storing the injury data as a group of linked blocks in a distributed computing system. The computing device may utilize a machine-learning model to generate a set of questions for the user. The questions may be utilized to determine weighting factors associated with the injury data. The computing device may utilize the machine-learning model to determine an impairment injury score based on the weighting factors. The computing device may display an injury risk management report to the user. The computing device may display, based at least in part on the report, a simulation describing a mechanism of the injury described in the injury data.

Abstract: Various embodiments are directed to utilizing an objective impairment injury score risk model. A computing device may receive injury data from a user. The computing device may then perform a security action that protects against unauthorized sharing of the injury data by storing the injury data as a group of linked blocks in a distributed computing system. The computing device may then utilize a machine-learning model to generate a set of questions for the user. The questions may be utilized to determine weighting factors associated with the injury data. The computing device may then utilize the machine-learning model to determine an impairment injury score based on the weighting factors. The may include an objectively determined value associated with a degree of impairment resulting from an injury described in the injury data. Finally, the computing device may display an injury risk management report, based on the score, to the user.

Abstract: Various embodiments are directed to utilizing an objective impairment injury score risk model. A computing device may receive injury data from a user. The computing device may then perform a security action that protects against unauthorized sharing of the injury data by storing the injury data as a group of linked blocks in a distributed computing system. The computing device may then utilize a machine-learning model to generate a set of questions for the user. The questions may be utilized to determine weighting factors associated with the injury data. The computing device may then utilize the machine-learning model to determine an impairment injury score based on the weighting factors. The may include an objectively determined value associated with a degree of impairment resulting from an injury described in the injury data. Finally, the computing device may display an injury risk management report, based on the score, to the user.

Abstract: Methods, systems, and computer program products assess injuries to elite athletes. A method involves receiving historical data associated with the athlete and receiving performance data from a functional assessment of the athlete. The functional assessment is designed based on a sport, a position, and/or the injury of the athlete. The method also involves querying a data source for mined data associated with athlete injuries similar to the injury being assessed, generating predictive data relevant to the injury, and analyzing the historical data, the performance data, the mined data, and/or the predictive data to produce a predictive analysis associated with the athlete.

Abstract: Methods, systems, and computer program products assess and manage work-related musculoskeletal injuries associated with one or more work sites. A method involves defining musculoskeletal injury categories and drawing relationships between the musculoskeletal injury categories by applying specialized medical knowledge. The relationships prevent informational disconnect between slightly disparate diagnoses between physicians who evaluate a same patient for the work-related musculoskeletal injury. The method also involves structuring storage of the relationships in a relational database, gathering for each work site, demographics and statistics on work-related musculoskeletal injuries associated with at least one of relatively high lost time or relatively high medical cost, and utilizing the relationships and the demographics to compile and retrieve data that facilitates prevention or improved resolution of the musculoskeletal injury.