A physician’s roundabout, intuitive way // determining diagnosis, dosage, prognosis through experience, trial and error // or a fleet of formulas // applying rules to data, expediting answers // and streamlining care?
Algorithms: Logical Medicine
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Mauricio Alejo for Proto
To nonmathematicians, the word algorithm (from a latinized version of the name of the ninth-century Persian astronomer who wrote a treatise on calculation) may seem arcane and off-putting, its definition difficult to pin down. Yet the thing itself, if not the term, pops up everywhere. Across the spectrum of human activity, algorithms run vital decision-making processes behind the scenes. If you’ve taken out a home mortgage, an algorithm was applied to your financial records to determine how to price your loan. If you were stranded after the eruption of Iceland’s Eyjafjallajökull volcano, algorithms were responsible for the rerouting of thousands of planes and crews to get you home. If you own a Volvo S60 sedan, algorithms are used to scan for pedestrians in your path and hit the brakes even if you don’t. In every modern industry, including medicine, algorithms rule.
An algorithm is any step-by-step procedure that applies rules to data, producing an unambiguous solution to a problem, and there is now a vast universe of clinical examples. The Medical Algorithm Project (MedAL), which stores peer-reviewed algorithms in an online database, contains more than 14,400. These tools can help physicians make diagnoses, choose treatments, calculate dosages, predict outcomes and monitor side effects. More are being developed every day.
Like their counterparts in mathematics, medical algorithms take myriad shapes. They can look like equations, scales, truth tables, checklists, scoring systems or decision trees. The simplest are performed with pen and paper, and the answers they provide may seem intuitive, something experienced physicians might come up with on their own, at least when dealing with familiar conditions. The widely used body mass index calculation, for instance, uses a straightforward ratio—mass in kilograms divided by the square of height in meters—to produce a number that physicians can use to see where a patient falls in a range from dangerously thin to morbidly obese.
Other clinical algorithms, however, are more complex and can help specialists keep up with a knowledge base that’s expanding exponentially. These formulas are computerized and often sift huge amounts of data and alternative approaches before reaching conclusions. For example, the algorithms that drive automated external defibrillators analyze the pattern of a patient’s heart rhythm to determine the number and strength of shocks required to restore normal functioning.
But simple or complicated, and despite their proliferation in textbooks, journals and, increasingly, electronic databases, most formal algorithms don’t get used. To critics such as Herbert L. Fred of the University of Texas Health Science Center, that’s a good thing. Fred, a professor of internal medicine, has written that algorithms lead physicians to interact with numbers, not patients, and has urged medicine to “give algorithms back to the mathematicians.” But advocates, including John Svirbely, medical director of laboratories at the McCullough-Hyde Memorial Hospital in Oxford, Ohio, and co-founder of MedAL, argue that algorithms save time, money and lives—or would, if they were integrated into everyday practice.
