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Explore This IssueSeptember 2019
MADRID—Each year in the U.S., more than 300,000 people—mostly older than 65—are hospitalized for hip fracture.1 The problem is a worldwide phenomenon and will likely increase as life expectancy increases.
Multiple risk factors for hip fracture are known, including older age, use of medications that cause bone loss, excessive alcohol or caffeine consumption, smoking and frailty. An issue often faced by clinicians is the proactive identification of patients at the highest risk for hip and other fractures.2 Systematic approaches to identify these patients have varied by doctor and practice, but the widespread use of electronic health records (EHRs) has now created an opportunity to develop automated systems
At the 2019 European Congress of Rheumatology (EULAR), June 12–15, Bo Abrahamsen, PhD, professor and consultant endocrinologist at the University of Southern Denmark, led an intriguing discussion about his work to create an automated short-term fracture risk prediction model based on existing information collected in EHR systems. In explaining the rationale for his work, Prof. Abrahamsen noted that such record systems provide a unique opportunity to study the epidemiology of fractures because they catalog information from a large number of patients, are used in clinical practice, are convenient and speedy, and do not require self-reporting. Interestingly, information on fracture data has been collected for many decades by Olmsted County, Minn., since 1928, in the Malmö Radiology Register since 1950, and elsewhere.
Several osteoporotic fracture risk calculators have been developed for clinical use. In 2009, researchers in the U.K. analyzed primary care data from more than 2 million patients to develop and validate two new fracture clinical risk scores that can be used to identify patients at high risk for fracture who may benefit from interventions to reduce their risk.3
In 2018, Danish researchers, including Prof. Abrahamsen, used public health registries with information on the total population of Denmark aged 45 and older—nearly 2.5 million patients—to develop a fracture risk evaluation model (FREM) to automate the process of identifying individuals at high risk for hip or major osteoporotic fractures.4 For this study, the researchers identified patients with an osteoporotic fracture in 2013 and looked retrospectively at patient information from the preceding 14 years to identify risk factors that could be used to estimate one-year risk of major osteoporotic and hip fracture. Although the positive predictive value of this algorithm was low, given that most patients won’t have a second fracture within a year of the first fracture, the negative predictive value was very high, at 99.2% for women and 99.5% for men.
The FREM tool & others are being evaluated for integration directly into EHR systems & nationwide patient information registries.
Many physicians may ask: Isn’t the Fracture Risk Assessment Tool (FRAX; an online calculator launched by the University of Sheffield, South Yorkshire, England, in 2008 to calculate the 10-year risk of major osteoporotic and hip fracture) already being used by physicians to counsel patients on fracture risk?5 Yes, however, Prof. Abrahamsen pointed out a few important caveats that may influence the utility of this tool. For example, the fracture risk estimate is for the subsequent 10 years, which may not be as valuable as shorter term risk estimates for some patients, specifically octogenarians or nonagenarians.