Everybody Hates Computers

This isn’t really a story about Medicine, instead it’s an illustration of the problems that integrated institutional software always has. That problem is, by the very nature of doing what it’s designed to do, it imposes costs in training and, ultimately, individual efficiency.

Oh sure it would be great if we were all coding geniuses AND experts in our day job so we could design tools specifically to suit our individual style, but that’s a rare combination. Normally you choose something that’s good enough and adjust your work to accommodate any imperfections. For instance, I compose all my pieces in Notepad, the primitive rudimentary text editor that ships free with every copy of Windows. Why? Well it does what I need. I can type, I can edit, I can save and cut and paste into other applications. It has a limited search and replace (you’ve never lived until you’ve learned to use the power of regular expressions, which it http://cinziamazzamakeup.com/?x=miglior-sito-per-comprare-viagra-generico-a-Parma doesn’t have). Most of all it’s ubiquitous. You can find Notepad, or an equivalent, in practically every operating system you can think of.

It’s not that I don’t have options. I have any number of Word Processors and Desktop Publishing programs to make things look pretty, the problem with them is that the hidden codes that make all the wizzy bang effects possible are http://maientertainmentlaw.com/?search=from-online-drugstore-real-levitra-canadian not transportable and dove comprare viagra generico a Firenze not compatible. That’s how you can claim click here your program is an original work and therefore copyrightable and not just another prednisone 80 mg daily Word ripoff. Of course with export options (some work better than others) this drawback is reduced, but it’s never entirely eliminated.

You know what hates formatting? Compilers. This is why I http://cinziamazzamakeup.com/?x=comprare-viagra-generico-100-mg-pagamento-online-a-Firenze also have a raft of Programming Editors that will do regular expression search. Most have extensive macro languages that will, according to Alan Turing, allow them to solve any problem that is computable (meaning that they have a conditional jump) and not merely record repetitive keystrokes.

I don’t use them because I no longer crank out 10 pages of ‘C’ a day and they’re a pain in the ass to set up. You can spend as long programming the editor as you do writing code and you have to learn yet another language. Work a treat when they do though.

In an institutional setting collaboration and data sharing are paramount. This means that if a description is limited to 255 characters (many are) then yours is too even if you really need a bigger one. Systems are designed to accomodate exceptional uses, but only to a certain degree and if you can’t fill a Phone Booth with people who have similar needs you’re unlikely to get the changes you desire.

Likewise Institutional Software is larded with features you will never, ever use (though you watch will be responsible for them in the proficiency test) because they’re important to somebody else. Beyond the fact that it’s confusing, the proliferation of functionality also likely buries the portions you actually need at the bottom of an obscure, arcane menu, accessible only through a Right Mouse Button Click while hovering over an infinitesimal and unmarked activation area.

Learn to live with it. These problems are go site not going away and even the smartest AI Assistant won’t help much because you have to train it.

Or you can train people, which seems to be what Doctors are doing and other than that it’s hard to figure out how they can stuff http://maientertainmentlaw.com/?search=generic-levitra-user-reviews another human being follow with a terminal into a teeny tiny Examining Room what’s not to love besides the Personnel Costs the Institution was trying to reduce?

Humans are much easier to train than machines.

buy viagra overnight delivery Why Doctors Hate Their Computers
By Atul Gawande, The New Yorker
November 12, 2018

On a sunny afternoon in May, 2015, I joined a dozen other surgeons at a downtown Boston office building to begin sixteen hours of mandatory computer training. We sat in three rows, each of us parked behind a desktop computer. In one month, our daily routines would come to depend upon mastery of Epic, the new medical software system on the screens in front of us. The upgrade from our home-built software would cost the hospital system where we worked, Partners HealthCare, a staggering $1.6 billion, but it aimed to keep us technologically up to date.

More than ninety per cent of American hospitals have been computerized during the past decade, and more than half of Americans have their health information in the Epic system. Seventy thousand employees of Partners HealthCare—spread across twelve hospitals and hundreds of clinics in New England—were going to have to adopt the new software. I was in the first wave of implementation, along with eighteen thousand other doctors, nurses, pharmacists, lab techs, administrators, and the like.

The surgeons at the training session ranged in age from thirty to seventy, I estimated—about sixty per cent male, and one hundred per cent irritated at having to be there instead of seeing patients. Our trainer looked younger than any of us, maybe a few years out of college, with an early-Justin Bieber wave cut, a blue button-down shirt, and chinos. Gazing out at his sullen audience, he seemed unperturbed. I learned during the next few sessions that each instructor had developed his or her own way of dealing with the hostile rabble. One was encouraging and parental, another unsmiling and efficient. Justin Bieber took the driver’s-ed approach: You don’t want to be here; I don’t want to be here; let’s just make the best of it.

I did fine with the initial exercises, like looking up patients’ names and emergency contacts. When it came to viewing test results, though, things got complicated. There was a column of thirteen tabs on the left side of my screen, crowded with nearly identical terms: “chart review,” “results review,” “review flowsheet.” We hadn’t even started learning how to enter information, and the fields revealed by each tab came with their own tools and nuances.

But three years later I’ve come to feel that a system that promised to increase my mastery over my work has, instead, increased my work’s mastery over me. I’m not the only one. A 2016 study found that physicians spent about two hours doing computer work for every hour spent face to face with a patient—whatever the brand of medical software. In the examination room, physicians devoted half of their patient time facing the screen to do electronic tasks. And these tasks were spilling over after hours. The University of Wisconsin found that the average workday for its family physicians had grown to eleven and a half hours. The result has been epidemic levels of burnout among clinicians. Forty per cent screen positive for depression, and seven per cent report suicidal thinking—almost double the rate of the general working population.

Something’s gone terribly wrong. Doctors are among the most technology-avid people in society; computerization has simplified tasks in many industries. Yet somehow we’ve reached a point where people in the medical profession actively, viscerally, volubly hate their computers.

Before, Sadoughi almost never had to bring tasks home to finish. Now she routinely spends an hour or more on the computer after her children have gone to bed.

She gave me an example. Each patient has a “problem list” with his or her active medical issues, such as difficult-to-control diabetes, early signs of dementia, a chronic heart-valve problem. The list is intended to tell clinicians at a glance what they have to consider when seeing a patient. Sadoughi used to keep the list carefully updated—deleting problems that were no longer relevant, adding details about ones that were. But now everyone across the organization can modify the list, and, she said, “it has become utterly useless.” Three people will list the same diagnosis three different ways. Or an orthopedist will list the same generic symptom for every patient (“pain in leg”), which is sufficient for billing purposes but not useful to colleagues who need to know the specific diagnosis (e.g., “osteoarthritis in the right knee”). Or someone will add “anemia” to the problem list but not have the expertise to record the relevant details; Sadoughi needs to know that it’s “anemia due to iron deficiency, last colonoscopy 2017.” The problem lists have become a hoarder’s stash.

“They’re long, they’re deficient, they’re redundant,” she said. “Now I come to look at a patient, I pull up the problem list, and it means nothing. I have to go read through their past notes, especially if I’m doing urgent care,” where she’s usually meeting someone for the first time. And piecing together what’s important about the patient’s history is at times actually harder than when she had to leaf through a sheaf of paper records. Doctors’ handwritten notes were brief and to the point. With computers, however, the shortcut is to paste in whole blocks of information—an entire two-page imaging report, say—rather than selecting the relevant details. The next doctor must hunt through several pages to find what really matters. Multiply that by twenty-some patients a day, and you can see Sadoughi’s problem.

The software “has created this massive monster of incomprehensibility,” she said, her voice rising. Before she even sets eyes upon a patient, she is already squeezed for time. And at each step along the way the complexity mounts.

“Ordering a mammogram used to be one click,” she said. “Now I spend three extra clicks to put in a diagnosis. When I do a Pap smear, I have eleven clicks. It’s ‘Oh, who did it?’ Why not, by default, think that go I did it?” She was almost shouting now. “I’m the one putting the order in. Why is it asking me what date, if the patient is in the office today? When do you think this actually happened? It is incredible!” The Revenge of the Ancillaries, I thought.

Sadoughi told me of her own struggles—including a daily battle with her Epic “In Basket,” which had become, she said, clogged to the point of dysfunction. There are messages from patients, messages containing lab and radiology results, messages from colleagues, messages from administrators, automated messages about not responding to previous messages. “All the letters that come from the subspecialists, I can’t read ninety per cent of them. So I glance at the patient’s name, and, if it’s someone that I was worried about, I’ll read that,” she said. The rest she deletes, unread. “If it’s just a routine follow-up with an endocrinologist, I hope to God that if there was something going on that they needed my attention on, they would send me an e-mail.” In short, she hopes they’ll try to reach her at yet another in-box.

As I observed more of my colleagues, I began to see the insidious ways that the software changed how people work together. They’d become more disconnected; less likely to see and help one another, and often less able to. Jessica Jacobs, a longtime office assistant in my practice—mid-forties, dedicated, with a smoker’s raspy voice—said that each new software system reduced her role and shifted more of her responsibilities onto the doctors. Previously, she sorted the patient records before clinic, drafted letters to patients, prepped routine prescriptions—all tasks that lightened the doctors’ load. None of this was possible anymore. The doctors had to do it all themselves. She called it “a ‘stay in your lane’ thing.” She couldn’t even help the doctors navigate and streamline their computer systems: office assistants have different screens and are not trained or authorized to use the ones doctors have.

“You can’t learn more from the system,” she said. “You can’t do more. You can’t take on extra responsibilities.” Even fixing minor matters is often not in her power. She’d recently noticed, for instance, that the system had the wrong mailing address for a referring doctor. But, she told me, “all I can do is go after the help desk thirteen times.”

Indeed, the computer, by virtue of its brittle nature, seems to require that it come first. Brittleness is the inability of a system to cope with surprises, and, as we apply computers to situations that are ever more interconnected and layered, our systems are confounded by ever more surprises. By contrast, the systems theorist David Woods notes, human beings are designed to handle surprises. We’re resilient; we evolved to handle the shifting variety of a world where events routinely fall outside the boundaries of expectation. As a result, it’s the people inside organizations, not the machines, who must improvise in the face of unanticipated events.

Artisanship has been throttled, and so has our professional capacity to identify and solve problems through ground-level experimentation. Why can’t our work systems be like our smartphones—flexible, easy, customizable? The answer is that the two systems have different purposes. Consumer technology is all about letting me be me. Technology for complex enterprises is about helping groups do what the members cannot easily do by themselves—work in coördination. Our individual activities have to mesh with everyone else’s.

Consider that, in recent years, one of the fastest-growing occupations in health care has been medical-scribe work, a field that hardly existed before electronic medical records. Medical scribes are trained assistants who work alongside physicians to take computer-related tasks off their hands. This fix is, admittedly, a little ridiculous. We replaced paper with computers because paper was inefficient. Now computers have become inefficient, so we’re hiring more humans. And it sort of works.

Not long ago, I spent a day following Lynden Lee as he scribed at a Massachusetts General Hospital primary-care practice. Lee, a twenty-three-year-old graduate of Boston University, is an Asian-American raised in Illinois, and, like many scribes, he was doing the job, earning minimum wage, while he applied to medical school. He worked for Allan Goroll, a seventy-two-year-old internist of the old school—fuzzy eyebrows, steel-wool hair, waist-length white coat.

Lee, wearing the scribe uniform of neatly tucked oxford shirt and khakis, went to get the morning’s first patient from the waiting room. He’d developed a short speech to introduce himself: “I help take notes, so that Dr. Goroll can spend more time with you instead of typing at the computer. But, of course, if there’s anything you need to say, or would like to discuss with Dr. Goroll, in private, I can certainly leave the room.”

Scribes aren’t a perfect solution. Underpaid and minimally trained, they learn mostly on the go, and turn over rapidly (most within months). Research has found error rates between twenty-four and fifty per cent in recording key data; Goroll still spends time after clinic reviewing the charts and correcting errors. But Lee spared him many hours a week, and Goroll was thrilled about it. He got back enough time to start work on the eighth edition of a textbook he has written on primary-care medicine. And, because of his scribe, he was able to give his patient his complete attention throughout the consultation. In recent years, he’d found this increasingly difficult.

Shteynberg said she was all in favor of scribes: “Because now Dr. Goroll will come right up in front of my eyes, and he listens.” She explained that he used to look at his screen, instead of at her, and type while he spoke.

“That bothered you?” he asked, surprised.

“Oh, yes,” she said.
We are already seeing the next mutation. During the past year, Massachusetts General Hospital has been trying out a “virtual scribe” service, in which India-based doctors do the documentation based on digitally recorded patient visits. Compared with “live scribing,” this system is purportedly more accurate—since the scribes tend to be fully credentialled doctors, not aspiring med students—for the same price or cheaper. IKS Health, which provides the service, currently has four hundred physicians on staff in Mumbai giving support to thousands of patient visits a day in clinics across the United States. The company expects to employ more than a thousand doctors in the coming year, and it has competitors taking the same approach.

Siddhesh Rane is one of its doctor-scribes. A thirty-two-year-old orthopedic surgeon from a town called Kolhapur, he seemed like any of my surgical colleagues here in Boston, direct, driven, with his photo I.D. swaying on a lanyard around his neck. He’d joined the company for the learning opportunity, he said, not the pay (although many of the IKS staffers were better paid than they would be in a local medical practice).

He explained the virtual-scribe system to me when we spoke via Skype. With the patient’s permission, physicians record an entire patient visit with a multidirectional microphone, then encrypt and transmit the recording online. In India, Rane listens to the visit and writes a first draft of the office note. Before starting the work, he went through a careful “onboarding” process with each of the American physicians he works with. One, Nathalee Kong, a thirty-one-year-old internist, was based at an M.G.H. clinic in Revere, a working-class community north of Boston. For a week, Rane listened to recordings of her patient visits and observed how she wrote them up. For another week, they wrote parallel notes, to make sure Rane was following Kong’s preferences. They agreed on trigger phrases; when she says to the patient, “Your exam is normal except for . . . ,” Rane can record the usual elements of her head-to-toe exam without her having to call each one out.

A note for a thirty-minute visit takes Rane about an hour to process. It is then reviewed by a second physician for quality and accuracy, and by an insurance-coding expert, who confirms that it complies with regulations—and who, not incidentally, provides guidance on taking full advantage of billing opportunities. IKS Health says that its virtual-scribe service pays for itself by increasing physician productivity—in both the number of patients that physicians see and the amount billed per patient.

Kong was delighted by the arrangement. “Now all I have to do is listen to the patient and be present,” she told me. When taking a family history, she said, “I don’t have to go back and forth: ‘O.K., so your mom had breast cancer. Let me check that off in the computer before I forget.’ I’m just having a natural conversation with another human being, instead of feeling like I’m checking off a box, which I literally was doing.”

Before working with Rane, Kong rarely left the office before 7 P.M., and even then she had to do additional work at home in order to complete her notes. Now she can leave at five o’clock. “I’m hopeful that this prevents me from burning out,” she said. “That’s something I was definitely aware of going into this profession—something that I really feared.” What’s more, she now has the time and the energy to explore the benefits of a software system that might otherwise seem to be simply a burden. Kong manages a large number of addiction patients, and has learned how to use a list to track how they are doing as a group, something she could never have done on her own. She has also learned to use a function that enters a vaccine table into patients’ notes, allowing her to list the vaccinations they should have received and the ones they are missing.

Her biggest concern now? That the scribes will be taken away. Yet can it really be sustainable to have an additional personal assistant—a fully trained doctor in India, no less—for every doctor with a computer? And, meanwhile, what’s happening across the globe? Who is taking care of the patients all those scribing doctors aren’t seeing?

It was a Monday afternoon. I was in clinic. I had no scribe, in India or otherwise; no cool app to speed me through my note-writing or serve up all my patient’s information in some nifty, instantly absorbable visual. It was just me, my computer, a file of papers, and John Cameron, a lanky, forty-three-year-old construction supervisor who’d been healthy all his life, felt fine, but was told to see a surgeon for reasons that he still didn’t completely understand.

It all started, he told me, with a visit to his primary-care provider for a routine physical. I held a printout of the doctor’s note. (My high-tech hack is to have key materials printed out, because it takes too long to flip between screens.) It said that she’d found a calcium level so high it was a wonder that Cameron wasn’t delirious. The internist sent him to an endocrinologist, who found, deep in his electronic records, a forgotten history of several benign skin lesions. The specialist wondered if Cameron had a rare genetic syndrome that’s known to cause tumors and, in turn, hormone abnormalities, skin lesions, and high calcium levels.

The diagnosis seemed very unlikely, but a battery of tests had turned up surprising results, including abnormal levels of a pituitary hormone. I needed to log into the computer to check the original lab reports. He watched me silently click one tab after another. Minutes passed. I became aware of how long it was taking me to pull up the right results. Finally, I let go of the mouse and took Cameron to the examining table. When I’d finished the exam and we sat down again at my little computer desk against the wall, I told him what I’d determined. He had a parathyroid tumor, it had pushed his calcium levels dangerously high, and it needed to be removed surgically. I took out a pen and paper, and drew a picture to explain how the surgery would be done. First, though, we needed to get his calcium under control. The abnormal levels of the pituitary hormone suggested that he might have a tumor in his pituitary gland as well—and might even have the unusual genetic syndrome. I was less sure about this, I told him, so I wanted to do more testing and get an opinion from an expert at my hospital.

Cameron’s situation was too complicated for a thirty-minute slot. We’d gone way over time. Other patients were waiting. Plus, I still had to type up all my findings, along with our treatment plan.

“Any questions?” I asked, hoping he’d have none.

“It’s a lot to take in,” he said. “I feel normal. It’s hard to imagine all this going on.” He looked at me, expecting me to explain more.

I hesitated. Let’s talk after the new tests come back, I said.

Later, I thought about how unsatisfactory my response was. I’d wanted to put my computer away—to sort out what he’d understood and what he hadn’t, to learn a bit about who he really was, to make a connection. But I had that note to type, and the next patient stewing across the hall.

A week or two after my visit with Cameron, I called him to review his laboratory results. A scan had pinpointed a parathyroid tumor in the right side of his neck, which would be straightforward to remove. A test showed that he didn’t have the genetic syndrome, after all, and a brain scan showed no pituitary tumor.

I had more time for his questions now, and I let him ask them. When we were done and I was about to get off the phone, I paused. I asked him if he’d noticed, during our office visit, how much time I’d spent on the computer.

“Yes, absolutely,” he said. He added, “I’ve been in your situation. I knew you were just trying to find the information you needed. I was actually trying not to talk too much, because I knew you were in a hurry, but I needed you to look the information up. I wanted you to be able to do that. I didn’t want to push you too far.”

It was painful to hear. Forced to choose between having the right technical answer and a more human interaction, Cameron picked having the right technical answer. I asked him what he meant about having been in my situation. As a construction-site supervisor, he said, he spends half his day in front of his laptop and half in front of people. His current job was overseeing the construction of a thirty-eight-unit apartment complex in town. “I have to make sure that things are being done per design and the specifications,” he said. That involves looking up lots of information, logging inspection data, and the like. But, at the same time, he has to communicate with lots of people. “I have to be out in the field checking and dealing with subcontractors and employees of our own.”

The technology at his disposal has grown more powerful in recent years. “We have cloud-based quality-control software, where we document the job at different stages. I can use that information for punch lists and quality-control checks. We also have a time-lapse camera where we can go back and look at things that we might’ve missed.” The technology is more precise, but it’s made everything more complicated and time-consuming. He faces the same struggle that I do.

Cameron was philosophical about it. He’s worked with big construction companies and small ones and used numerous software systems along the way. He couldn’t do without them. And yet, he said, “all these different technologies and apps on these iPads, all the stuff that I’ve had to use over the years, they’re supposed to make our job easier. But they’re either slow, or they’re cumbersome, or they require a lot of data entry and they’re not efficient.” The system inundates his subcontractors with e-mail alerts, for instance. “ ‘You gotta submit this, you’re behind on that, you didn’t finish the punch list.’ The project managers and superintendents and subcontractors eventually say, ‘Enough’s enough. We can’t deal with all these e-mails. It’s ridiculous.’ So they ignore them all. Then nothing gets done. You end up on the phone, back to the old-school way. Because it’s a people business.”

He went on, “I don’t allow anybody to work on my job unless they go through a one-hour orientation with me. I have to know these guys personally. They have to know me. Millions of years human beings evolved to look at each other in the face, to use facial expression to create connection.”

I’d talked to dozens of experts, but Cameron might have been the wisest of them all.