Medicine has always been a cottage industry, a massive series of one-off health interventions in which every step is filled with human handling and judgment. But it cannot go on this way. Everywhere around the world, from sub-Saharan Africa to the United States, healthcare systems are bumping up against the functional limits of traditional medical ways and means.
There are certainly elements of healthcare for which no machine can substitute: the empathetic, experienced observation of a good clinician and the grace of human contact and care for those suffering and dying. But as Christopher Steiner explains in the excerpt below, many of the everyday operations of healthcare, for example, scanning slides of cells for signs of abnormalities, can be easily quantified and standardized — and thus managed more effectively by algorithms run on machines.
Efficiency used to be a worthy ideal in healthcare settings. But now it is a necessity — and one that requires not only incremental improvements, but step-wise transformations. We won’t be able to provide quality healthcare to everyone without it.
— Joe Flower
An excerpt from Chapter 6 of Automate This: How Algorithms Came to Rule Our World
Health care is full of easy wins for algorithms. The first thing to change will be how we analyze test results. The frequency, complexity, and costs of tests, from Pap smears to X-rays to MRIs to CT scans, have been among the major contributors to the explosion of health care costs during the last twenty years. When somebody shows up at the doctor not feeling well, they’re often subjected to a gauntlet of tests no matter what their symptoms indicate about their condition. When that flurry of tests is over, another one often follows. Even when there’s a 99.9 percent likelihood the test isn’t needed, it’s usually still mandated. The result, for those doing the testing, is an avalanche of easy revenue — thus exemplifying how capitalism, although it’s an effective paradigm for most of the economy, is not an efficient way to administer health care. A multitude of stats can be called on to support this, but simply consider that the United States’ average life expectancy of seventy-eight years is the same as that of Cuba, a country that spends less than 10 percent per capita of what the United States does on health care but achieves roughly the same result.
But this isn’t about an ideological battle. It is about algorithms bettering the system we have in the United States — and they will do that initially by becoming the default scanners, observers, and analysts of all of these tests. Where once your results required the expensive attention of a radiologist or a pathologist, in the future the attention of an algorithm will do just fine. It will, in fact, do better.
Take the Pap test, originally called the Pap smear (named after its Greek inventor, Georgios Papanikolaou). The test has cut down on cervical cancer mortality rates in the United States by more than 90 percent since it was first introduced in the 1940s. It examines a slide of a small sample of cells drawn from a woman’s cervix. The slide first goes to a cytotechnologist, a person specially trained to do one thing: look for signs of abnormalities in the cells that may indicate cancer. Suspect slides are then passed to a pathologist, an MD who may earn more than $300,000 per year. There exist algorithms that can already replace the cytotechnologist. Even better (or worse, if you’re a cytotechnologist), the algorithms help find more instances of cancer than their human competitors by scanning each image for visual clues that mimic those known to reveal cancers in old cataloged images. In one study carried out by BD, a medical technology company that creates some of the equipment behind the testing, labs using their algorithm in tandem with a cytotechnologist spotted 86 percent of cancer instances versus 79 percent for those scanning without the algorithm. The rising use of algorithms in medical scanning will snare more problems, like cancer, earlier, and minimize false negatives, the scariest issue with such scans. Even incremental improvement would change thousands of lives; in the United States alone, more than fifty-five million Pap tests are carried out every year…