Whether an automated system is monitoring the status of a nuclear power plant, a commercial jetliner, or your washing machine, perhaps the most challenging decisions revolve around what to do with alerts. On an average day at UCSF Medical Center, we prescribe about 12,000 medication doses, and order thousands more x-rays and lab tests. How should the doctor be informed if the computer thinks there is — or might be — a problem?

Because many academic medical centers installed Epic before 2012, UCSF had the advantage of learning from these early adopters. One near-universal recommendation was to be sparing with alerts, because every alert makes it less likely that people will pay attention to the next one.

Heeding this feedback, the medical center chose to disable thousands of the alerts built into the drug database system that the hospital had purchased along with Epic. Despite this decision, there were still tons of alerts. Of roughly 350,000 medication orders per month, pharmacists were receiving pop-up alerts on nearly half of them. Yes, you read that right: nearly half. The physicians were alerted less frequently — in the course of a month, they received only 17,000 alerts.

The alert problem was especially daunting in pediatrics. Given weight-based doses and the narrow therapeutic range for many medications, alerts fired on several of the 10 to 15 medications ordered by the doctors for the typical hospitalized youngster, and on the vast majority of orders processed by the pediatric pharmacists.

Computerized medication alerts represent only a small fraction of the false alarms that besiege clinicians each day. Barbara Drew, a nurse-researcher at UCSF, has been studying a similar problem, alarms in the ICU, for decades. During that time, she has seen them grow louder, more frequent, and more insistent. She has witnessed many Code Blues triggered by false alarms, as well as deaths when alarms were silenced by nurses who had simply grown weary of all the noise.

A 2011 investigation by the Boston Globe identified at least 216 deaths in the U. S. between January 2005 and June 2010 linked to alarm malfunction or alarm fatigue. In 2013, The Joint Commission, the main accreditor of American hospitals, issued an urgent directive calling on hospitals to improve alarm safety. The ECRI Institute, a nonprofit consulting organization that monitors data on medical errors, has listed alarm-related problems as the top technology hazard in healthcare in each of the last four years.

There are many reasons for false alarms: misprogrammed thresholds; dying batteries; loosening of an electronic lead taped to the patient’s chest. But plenty of alarms are triggered by the activities of daily hospital living. Liz Kowalczyk, who led the investigation for the Globe, spent a morning in the cardiac unit at Boston Children’s Hospital. She observed,

[The nurse] hurried into Logan’s room — only to find a pink-cheeked, kicking 3-month-old, breathing well, cooing happily. Logan was fine. His pumping legs had triggered the crisis alarm again. The red alarm is the most urgent, meant to alert nurses to a dangerously slow or fast heart rate, abnormal heart rhythm, or low blood oxygen level. But on this morning . . . infants and preschoolers activated red alarms by eating, burping and cutting and pasting paper for an arts and crafts project.

In the face of growing nationwide concern about alert fatigue, Barbara Drew, the UCSF researcher, set out to quantify the magnitude of the problem. For a full month in early 2013, she and her colleagues electronically tapped into the bedside cardiac alarms in UCSF’s five intensive care units, which monitored an average of 66 patients each day. Mind you, this is just the bedside cardiac monitor, which follows the patient’s EKG, heart rate, blood pressure, respiratory rate, and oxygen saturation. It does not include the IV machine alarms, mechanical ventilator alarms, bed exit alarms, or nurse call bell. Nor does it include any of the alerts in the computer system, such as the Septra overdose alert that Jenny Lucca overlooked.

Drew’s findings were shocking. Every day, the bedside cardiac monitors threw off some 187 audible alerts. No, not 187 audible alerts for all the beds in the five ICUs; 187 alerts were generated by the monitors in each patient’s room, an average of one alarm buzzing or beeping by the bedside every eight minutes. Every day, there were about 15,000 alarms across all the ICU beds. For the entire month, there were 381,560 alarms across the five ICUs. Remember, this is from just one of about a half-dozen systems connected to the patients, each tossing off its own alerts and alarms.

And those are just the audible ones.

If you add the inaudible alerts, those that signal with flashing lights and text-based messages, there were 2,507,822 unique alarms in one month in our ICUs, the overwhelming majority of them false.

Add in the bed alarms, the ventilators, and the computerized alerts . . . well, you get the idea.

Like many other physicians, pharmacists, and nurses, Jenny Lucca found alerts to be a constant nuisance. Even giving Tylenol to a feverish child every four hours triggered an alert that the dose was approaching the maximum allowed. Every training program has a “hidden curriculum” (the way things are actually done around here, as opposed to what the policies say or what the administrators told you during that interminable orientation). One of them — passed down from senior residents to the newbies — was, “Ignore all the alerts.”

While Lucca was slightly uncomfortable with that as a governing philosophy, 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 and attention, 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.

When I spoke with Jenny Lucca months after Pablo Garcia’s overdose, I asked her how she could have clicked out of the Septra overdose alert, knowing now that by doing so, she had confirmed an order for 38½ Septra tablets. She blamed part of it on alert fatigue, of course. But she also pointed to the appearance of the alerts in Epic. “There is no difference between a minuscule overdose — going 0.1 milligram over a recommended dose — and this very large overdose. They all look exactly the same.”

In fact, the Epic alert that Lucca received is a model of bad design (in the updated version of the software, it is a bit better). There are no graphical cues, no skull and crossbones — nothing that would tell a busy physician that this particular alert, unlike the dozens of others that punctuate her days, truly demanded her attention.

Once Lucca signed the Septra order and clicked out of the alert, it boomeranged to Benjamin Chan’s computer within a matter of minutes. The pharmacists at a place like UCSF serve as a crucial layer of protection, and Chan was an experienced professional who prided himself on his carefulness. But, on this particular day, the deck was stacked against him.

First, Chan had been on the wards with Lucca in the past. “I have worked with her, we know each other, and I trust her,” he told me. In retrospect, Chan said, it’s likely that this personal relationship was one of the reasons he let his guard down.

Second, 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 — two doctorally trained clinical pharmacists like Chan, and two pharmacy techs — buzz around, bouncing into each other like pinballs. In addition to the bodies, the room is packed tight with equipment, including two ventilated hoods for mixing volatile or toxic medications, a sink, shelves lined with bins stocked with medications, a label printer, IV bags, syringes, needles, and a locked cabinet for storing narcotics. On the day I visited, several months after Pablo Garcia’s overdose, one of the technicians was carefully mixing up medications, her arms sheathed in rubberized sleeves that penetrated a clear plastic tent.

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 periodically appeared at the Dutch door to pick up medications.

“The phones just never stop ringing,” Chan told me. “There are always nurses coming to the window to pick up their narcotics; the respiratory therapist comes looking for his meds. In going through one patient’s medication orders, I’ll be interrupted six or seven times, at least.”

It sure seemed risky to me, and a 2010 Australian study confirmed that it is. The investigators observed 98 nurses while they prepared and administered 4,271 medications. Every interruption increased the risk of a medication error by 13 percent. When a nurse was interrupted four times, the rate of errors likely to lead to permanent harm or death doubled.

Abundant research has demonstrated that the term multitasking is a misnomer — performance degrades rapidly when people try to do several things simultaneously, whether it’s your kids doing homework while texting or a pharmacist checking orders while answering the phone. Psychologists speak of the concept of “cognitive load” — the overall volume of things a mind is grappling with at a given time. While there are some individual differences in the ways we manage cognitive load, one thing is clear: none of us does this as well as we think we do.

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 — for good measure — contains the number “160” in 14 different places.