The end of MedTech week coincides with the start of a new football season. In a week when the father of a schoolboy footballer who sadly collapsed during a football match and died three days later from an underlying undiagnosed cardiac condition called for screening for cardiac conditions to be extended beyond the professional game, an Italian study highlighted how Artificial Intelligence could be used to predict injuries to professional footballers in the future.
It is clear that there is more information than ever now available to the army of data scientists who work within elite sports clubs. From a medico legal perspective a number of key issues arise for any organisation holding such data. Ensuring that it is safely stored, accessed and shared only with the appropriate persons is paramount to avoid hefty fines under GDPR. This could be up to 4% of worldwide turnover . Any athlete must consent to their personal data being shared amongst those within and outside their club.
Explaining the significance of the test results to athletes and obtaining their informed consent around medical treatment decisions and return to play is essential especially where it may be following assessment of cardiac screening or concussion injury. A failure to warn of risk associated with medical treatment or a return to play is a common allegation in medical malpractice claims brought by professional as well as amateur athletes. For children it is the parents who need to be warned of the risks and provide consent. Clear medical records of any such discussions are required as it will be the key evidence to consider years down the line in the event a complaint or legal claim is made.
Professional sport will continue to be at the forefront of using medical technology and AI but those who have this goldmine of data at their finger tips need to ensure a governance framework is in place to properly manage the risks. By having evidence of a culture which puts the welfare of the athlete at the forefront litigation risk can be minimised.
Data scientists in Italy, working alongside FC Barcelona and the Philadelphia 76ers basketball team, have developed a machine-learning algorithm that managed to predict nine out of the 14 injuries suffered by players of an elite Italian football squad during a season. As the season progressed, the algorithm learned to detect patterns between these variables and players getting hurt.