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Sports Medicine Diagnostic Coding System

Developed in Canada in 1991, SMDCS is a numerical system that uses a 6-character structure denoting body region, structure, and diagnosis. It follows a systematic anatomical design, first listing the area (XX), then structure (.00), and then the type of injury (.00). For example, KN.53.06 is the code for complete tear of the ACL. The first pair of letters is assigned to the location (knee), the next pair of digits is assigned to structure (ACL), and the last pair of digits is assigned to the type of injury (sprain). This format permits data sorting on the basis of any pair of digits to allow analysis of the body region, structure, and diagnosis. The Canadian Intercollegiate Sport Injury Registry and international organizations associated with rugby currently use this system as part of their ISS.19 For the most current version of SMDCS, sports injury specialists should refer to the University of Calgary’s website (www.sportmed.ucalgary.ca/Sport_Medicine/smdcs).

Epidemiology Definitions and Calculations

Current sport epidemiological research is limited by the lack of standard terminology across databases.1,2,4,6-8 Many published studies define injury, selection criteria, and population sizes differently. This directly affects estimated rates of injury. Because the calculation of IRs used different variables, many early epidemiological studies must be viewed individually, and generalizing the results is difficult. In the United States, football has the dubious distinction of having the highest rate of reportable injuries and is the leader in the most catastrophic injuries and fatalities.10 However, much of these data were not reported as a standard unit (AEs/1000) across studies. For example, when reviewing catastrophic and fatality data, football would be surpassed by ice hockey and gymnastics if AEs were calculated at the rate of participation per year instead of per season.7 Therefore, any interstudy comparisons must be made critically and analyzed for discrepancies.

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There are other confounding variables regarding what injuries are more prevalent in which sports. These include level of play (ie, elite vs novice), age, and gender.7 This further limits the generalizability of data and requires additional analysis to determine risk based on level of performer, age, gender, or other variables.

How Do We Define a Population at Risk?

Overall athlete participation is a critical component of surveillance. For most, a population that is at risk is defined by identifying those injured and those not injured. Injury surveillance and epidemiology studies use different terms, variables, and calculations. For consumers of these data, it can be difficult to understand and apply the information provided. Some injury data do not report the number at risk in the population. As such, these types of databases are only reporting injury frequency. Sports epidemiologists and researchers express risk and incidence as ratios created from dividing a numerator by a denominator. Examples include rate ratios, risk ratios, incidence rates, and incidence proportion. These terms are often used interchangeably, which is incorrect. True IRs cannot be generated using the total population at risk as the denominator.12

Statistical Terminology

Prevalence is the proportion of individuals in a population who have an illness/injury at a particular time. This represents the number of athletes with a current injury (acute and chronic) relative to the population at risk.6 True prevalence is not calculated in sport because conditions generally do not last longer than 1 year.

Injury Surveillance Systems Research Databases and Collection Agencies

Athletic trainers are typically the primary data collectors for ISS; therefore, it is important to be aware of the various sport databases and injury collection agencies. The accuracy of the data collected is critical to the quality control and validity of the system being used.

National Athletic Injury/Illness Reporting System

The NAIRS was the first attempt at a nationwide data collection process for IRs in sport. From 1977 to 1981, NAIRS focused on football injuries. During the original NAIRS work, more than 1 million AEs in a 3-year period were analyzed.12 NAIRS stopped collecting high school and college data in 1983.20 Issues with the NAIRS data collection were the length and complexity of the forms. NAIRS was the foundation of the current NCAA ISS.12,17-20 Although NAIRS is no longer active, it was the first sport ISS in the United States.

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