The acute and long-term effects of concussive and subconcussive head impacts on brain health have gained tremendous attention over the past five years. The treatment and management of concussion involves multiple providers from multiple disciplines and backgrounds. Varied backgrounds and approaches to assessing cognitive and motor function before and post-concussion are limiting factors in the efficient and effective management of concussion as discipline-specific rating scales and assessments serve as a barrier to effective patient hand-offs between providers. Combining principles of motor behavior with biomechanical approaches to data analysis has the potential to improve the continuity of care across the multiple providers managing athletes with concussion. Biomechanical measures have been developed and validated using mobile devices to provide objective and quantitative assessments of information processing, working memory, set switching, and postural stability. These biomechanical outcomes are integral to a clinical management algorithm, the Concussion Care Path, currently used across the Cleveland Clinic Health System. The objective outcomes provide a common data set that all providers in the spectrum of care can access which facilitates communication and the practice of medicine and in understanding the acute and long-term effects of concussion and subconcussive exposure on neurological function.
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The Utilization of Biomechanics to Understand and Manage the Acute and Long-term Effects of Concussion
Jay L. Alberts and Susan M. Linder
Learning From Failure
James A. Ashton-Miller and Ronald F. Zernicke
included contracts for patients to empower them and make each one accountable, aligning and linking of services to be patient-focused, developing case managers to facilitate service delivery for each patient, standardizing the care path based on evidence, and implementing common (electronic) medical
In Silico Biomarkers of Motor Function to Inform Musculoskeletal Rehabilitation and Orthopedic Treatment
Ilse Jonkers, Erica Beaucage-Gauvreau, Bryce Adrian Killen, Dhruv Gupta, Lennart Scheys, and Friedl De Groote
—have addressed this barrier. Based on our aforementioned experiences, the authors of this review would like to discuss the barriers to clinical integration and positioning of these in silico technologies within standard clinical care paths in the light of 4 specific challenges. The first challenge relates to the
