ERRORS
Resident:
At around noon on a cool July day in San Francisco, Jenny Lucca, a pediatrics resident at UCSF, began the process of admitting Pablo Garcia, whose rare genetic disease had led to bouts of gastrointestinal bleeding and abdominal pain. He needed further evaluation with an elective colonoscopy. After speaking to Pablo and his mother and examining the young patient, Lucca clicked into the physicians’ orders section in the electronic health record. Pablo was on about 15 different medications. Lucca ordered his usual immunosuppressive pills, the liquid bowel-cleansing prep for the colonoscopy and his monthly infusion of immunoglobulins.
Then she came to the Septra, an antibiotic that the teenager had been taking for years to prevent recurrent infections. The usual dose of Septra is one double-strength pill twice daily, and that is what Pablo was taking at home. She entered septra into the computer.
System:
13 months earlier UCSF had installed Epic. A series of decisions about how the system would run had made at the time of set up. Since pediatric patients can range from a preemie weighing a couple of pounds to a morbidly obese adolescent, many pediatric medications are dosed based on weight, usually expressed in mg/kg. The committee overseeing UCSF Epic implementation decided to require weight-based dosing for all children under 40 kilograms (about 88 pounds).
Another choice involved the translation of weight-based doses into pills. What if the computer calculated that a dose should be 120 mg (based on the child’s weight), but the only available pill was 100 mg? The decision: if the available medication was more than 5 percent off the calculated “correct” dose, then the pharmacist would contact the doctor.
Resident:
The weight-based dosing policy forced Lucca to order Pablo Garcia’s medication in milligrams per kilogram, since the youngster weighed less than 40 kg. The computer multiplied this weight by the 5 mg/kg and determined that the dose should be 193 mg. Of course, there is no 193 mg Septra pill; the nearest tablet size is the 160 mg double-strength Septra pill. The computer recommended that the dose be rounded down to a single tablet. This was ordered.
Pharmacy:
Benjamin Chan was working in a small satellite pharmacy on the seventh floor. As the pediatric clinical pharmacist, it was Chan’s job to sign off on all medication orders on the pediatric service. Chan immediately noticed a problem with this Septra order: the dose of 193 mg the computer had calculated (based on the teenager’s weight) was 17% greater than the standard 160-mg Septra double-strength tablets. Because this discrepancy exceeded the hospitals 5% policy Chan was not allowed to simply approve the order. Instead, it required that he contact Lucca (the resident), asking her to enter the dose corresponding to the actual pill size: 160 mg. The pharmacist texted Lucca: “Dose rounded by >5%. Correct dose 160 mg. Pls reorder.”
Of the scores of medications that the resident would order — and the pharmacist would approve — that day, this was probably the simplest: an antibiotic pill being taken as a routine matter by a stable patient.
Resident:
After receiving Chan’s text message, Lucca reopened the medication-ordering screen in Epic. What she needed to do was trivial, and she didn’t give it much thought. She typed “160” into the dose box and clicked “Accept.” She then moved to the next task on her long checklist, believing that she had just ordered the one Septra tablet that she had wanted all along. But she had done something very different.
System:
Do you spot the problem? Since doses can be ordered in either milligrams or milligrams per kilogram... In UCSF’s version of Epic, the decision was made to have the screen default to milligrams per kilogram for all kids weighing less than 40 kilograms. That seemingly innocent decision meant that, in typing 160, Lucca was actually ordering 160 mg per kg — not one double-strength Septra, but 38½ of them.
Resident:
Like many other physicians, pharmacists, and nurses, Jenny Lucca found alerts to be a constant nuisance. Every training program has a “hidden curriculum” (the way things are actually done around here). One of them — passed down from senior residents to the newbies — was, “Ignore all the alerts.”
She was convinced that most of the dozen or more alerts she received each day could be safely ignored, and she knew that doing so was the only way she could get her work done. With her task list brimming with dozens of unchecked boxes and more sick kids in need of her care, Lucca assumed that the alert she received after signing the Septra order was yet another annoying one with no clinical significance, and so she clicked out of it. With that, the order for 38½ Septras now ricocheted back to the pharmacy, having been signed and validated by a licensed physician.
Pharmacy:
Chan had been on the wards with Lucca in the past. “I have worked with her, we know each other, and I trust her as a physician” he told me. Plus the seventh-floor satellite pharmacy, where Chan works, is a frenzied place. In an 8 × 18-foot room (about the size of a parking space), four individuals buzz around bouncing into each other like pinballs. In the midst of this bustle, the pharmacists were checking every order that appeared in a computerized queue (often making several follow-up calls to determine whether the order was correct), while simultaneously answering the phones, supervising the technicians, and dealing with visitors who appeared to pick up medications.
With all of these social, logistical, and cognitive land mines to sidestep, it’s little wonder that Chan didn’t notice the “mg/kg” when he saw “160” only a few minutes after texting Lucca to order just that dose. Also, by a terrible coincidence, when you multiply 160 mg/kg by 38.6 kg, you get 6,160 mg (after rounding to the nearest tablet size), which contains the number “160,” another opportunity for what psychologists call “confirmation bias”— seeing what one expects so see.
So Chan accepted Lucca’s order for 160 mg/kg. And then he went on to click out of his own alert screen, which looked as bland and busy as the one that Lucca received and contains the number “160” in 14 different places.
System:
The order was sent electronically to be processed by the $7 million dollar robot that is programmed to pull medications off stocked shelves; to insert the pills into shrink-wrapped, bar-coded packages and send them to the patient floors. The robot dutifully collected the 38½ Septra tablets and sent them to Pablo’s floor, where they came to rest in a small bin waiting for the nurse to administer.
Nurse:
On July 26, 2013, Nurse Levitt was assigned a night shift, not in her usual ICU, but on a unit that was short-staffed, the general pediatrics floor. She gave him several of his medications, including multiple cups of the bowel-purging GoLYTELY liquid. Then she came to the order for the 38½ Septras in the computer . “I remember going to his drawer and I saw a whole set of rings of medications, which had come over from the robot. And I was like, wow, that’s a lot of Septra. . . . It was an alarming number.” She’d given Septra before, in the ICU, but always in liquid or intravenous form, never pills. Her first thought was that perhaps the pills came in a different (and more diluted) concentration. That might explain why there were so many.
Of course, Levitt now beats herself up for not tapping her colleague on the shoulder. But it’s not that surprising that she failed to do so. Studies have found that one important cause of errors is interruptions, so clinicians at UCSF and elsewhere have been counseled to avoid them. She also “didn’t want to sound dumb.” Finally, remember that Levitt was usually assigned to the pediatric ICU, where nurses, doctors and pharmacists still generally work side by side. “I’m so used to just asking a resident on the spot, ‘Is this the dose you really want?’” she said. But on the wards, where the pace is slower and the children are not as critically ill, the doctors have all but disappeared. They are now off in their electronic silos, working away on their computers, no longer around to answer a “Hey, is this right?” question, the kind of question that is often all that stands between a patient and a terrible mistake.
Levitt took the rings laden with medications to Pablo’s bedside. She scanned the first packet (each packet contained one tablet), and the bar-code machine indicated that this was only a fraction of the correct dose — the scanner was programmed to look for 38½ pills, not one. So she scanned each of the pills, one by one, like a supermarket checkout clerk processing more than three dozen identical grocery i