The first step in slowing out-of-control testing costs in U.S. health care was to ship some test analyses to well-trained doctors in India. The next — and final — answer will be turning all of this work over to algorithms that, when perfected, will do a better job than humans in India, America, or anywhere else. The jobs for people reading scans, tests, and patient metadata are certainly endangered. Just as threatened as this workforce are the people who measure and dole out our medications. Pharmacists in urban areas can make more than $130,000 a year. Their job is stressful, detail-oriented, and can be, unfortunately for pharmacists, easily quantified. That means the profession begs for a bot invasion, and it’s imminent. In 2011, the University of California at San Francisco opened a pharmacy staffed by nobody except a single robot. A Swiss logistics firm, Swisslog, created the $15 million robot for UCSF.
The machine, which receives information straight from the electronic messages that already go between doctor’s offices and pharmacies, has long, dexterous arms that pluck and pack pills from thousands of bulk boxes that are built into the walls of the contraption. The bot receives all information regarding the patient, including their condition, any allergies, and all other medications they may be on. Algorithms within the bot quickly check for conflicts and complications with the new prescription, ensuring that there will be no detrimental drug interactions. The algorithms in the UCSF machine don’t need any time to read up on the latest in pharmacology; they get updated drug information through electronic messages from pharmaceutical companies and assimilate it immediately. The machine, unlike a human, forgets nothing. That’s not to say that a machine can’t make an error — bugs can affect the best-written programs. But bugs are also easily fixed and algorithms can run concurrent tests on the bot that doles out the drugs, building safety redundancy into the robot pharmacist.
The bot in San Francisco has now filled two million prescriptions without making a single mistake. And there’s no human contact between the pills and their packaging, eliminating the chance of contamination.
So how does the human competition fare? There’s a strange dearth of data on pharmacy error rates, and the few extant studies show results that span from the scary — a 4 percent error rate — to even scarier — 10 percent error rates. It seems, however, that an accepted conservative number within the industry is about 1 percent. A national study of fifty pharmacies by the American Pharmacists Association showed that the average error rate is 1.7 percent. All of these numbers are scary. There are 3.7 billion prescriptions filled in the United States every year, which means, even by the most conservative of measurements, that there are more than 37 million prescription errors annually. The American Pharmacists Association estimated the number to be even higher, at 51.5 million.The costs of these errors to patients, our health system, and all parties involved in the pharmaceutical process are dear. Pharmacists are not helped by the fact that there remains a shortage of them nationally, which leads to overworking, understaffing, and even more errors. The demand for an algorithm-powered robot in this role is undeniable. Picking out pills, cross-checking for drug interactions, and ensuring that quantities and medications are exactly right are skills made for algorithm-powered bots. Few tasks are so quantifiable. There’s a business side of this equation as well. Walgreens, the country’s largest pharmacy chain, had four jury-decided lawsuits involving fatal prescription errors brought against it during thirteen months in 2006 and 2007, with awards topping $61 million. What if Walgreens could eliminate such liabilities from its balance sheet? It can and it will.