Designing Predictive Models for Musculoskeletal Injury and Injury Reoccurrence After Returning to Full Duty Following an Injury

Posted August 27, 2019

Dr. Daniel Rhon, PT, DPT, DSc., Brooke Army Medical Center, Fort Sam Houston, TX

Dr. Daniel Rhon, PT, DPT, DSc., Brooke Army Medical Center, Fort Sam Houston, TX

Dr. Daniel Rhon

Musculoskeletal injuries, such as lower back and extremity pain, are highly disabling conditions among U.S. Service members. Such injuries can occur in deployment settings, where Warfighters are exposed to much physical strain from carrying heavy equipment and from mission tasks. However, most musculoskeletal injuries occur in non-deployment or non-combat settings from sports-related activities and overuse, as well as in operational occupations that involve more physical labor. Musculoskeletal injuries require adequate time to heal, and therefore, contribute to many lost hours from duty and delay Service members’ return to full duty. As a result, the readiness of the Force is negatively affected by consequences, such as delayed graduation from training programs, reduced number of personnel available for specific military occupations, decreased deployability, and even delayed separation from military Service.

Further, once a musculoskeletal injury occurs, there is a risk that the injury or other injuries could occur again. Although injured Service members often undergo a variety of treatments, recovery from injury may be inadequate before being cleared to return to duty. Hence, the risk for the injury to worsen or for another injury to occur increases.

To date, there is no standard physical performance measure for effectively assessing readiness to return to full duty after injury. Therefore, Dr. Rhon and his team are designing statistical predictive models to identify specific risk factors for injury and injury reoccurrence. Using various biopsychosocial variables such as age, sex, sleep habits, fear avoidance, pain catastrophizing, prior injury, muscle physiology, and physical fitness levels that could influence injury and injury reoccurrence, a multifactorial model was developed for predicting future injury after undergoing physical rehabilitation.

These models will also include scores from a battery of physical function performance assessments for balance, agility, endurance, power, extremity and trunk stability, and fundamental movements. Taken together, all of these variables will be combined in predictive algorithmic models to determine the risk for sustaining another injury or reoccurrence of the same injury following after being cleared to return to duty. Dr. Rhon has already recruited participants for an upcoming research study, where these newly developed predictive models will be employed and validated. Additionally, the research team is using healthcare data to pinpoint common musculoskeletal injuries in order to examine the longer-term health outcomes of specific injuries. By modeling specific types of musculoskeletal injuries together with a diverse set of physical performance and biopsychosocial variables, the study team intends to develop robust algorithms for predicting injury risk outcomes.

The overreaching deliverable expected from this investigation is an injury prevention approach that enables screening for known preventable musculoskeletal risks to ensure these risks are addressed prior to being cleared to return to full duty after an injury. This approach has potential to be developed into a standard physical performance measure for assessing readiness to return to duty after considering the risk for sustaining further injury. Establishing a standard physical performance measure could offer reassurance that injured Service members are sufficiently healed and can be operationally functional before returning to full duty.



Public and Technical Abstracts: Development of Predictive Models of Injury for the Lower Extremity, Lumbar, and Thoracic Spine after Discharge from Physical Rehabilitation

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Last updated Thursday, May 26, 2022