Analytics in Sports Medicine Implications and Responsibilities That Accompany the Era of Big Data

Analytics are increasingly being used in sports medicine and throughout orthopaedics. Data collected by athletes and teams come in many forms, including wearable devices, smart apparel, and other modalities, and may include global positioning and accelerometry data, heart rate, and sleep data. There is increasing evidence to suggest that these data can help to direct injury prevention programs by identifying risk factors for injury in sports. Biometric data collected from these devices may be analyzed with software packages, with add-on features for analysis of specific metrics such as accelerometry. Ethical considerations regarding data collection, storage, and utilization have yet to be fully defined as data could be used by multiple parties with interests that may or may not coincide with the interests of the athlete. Health-care providers will be increasingly expected to interpret and utilize data that patients provide them regarding performance and activity level. At the time of writing, there were no valid algorithms, to our knowledge, for the use of devices to accurately predict sports-related injuries. Invalid algorithms may cause changes in training that may ultimately lead to injury, so cautious use of these devices is warranted.