Streaming video over the internet is a memory hog. If Netflix were to simply store movie files as mp4s and send them out to subscribers on-demand, Stranger Things fans would crash the internet in minutes. Software engineers have solved this problem by creating “compression algorithms” to reduce the file sizes of the transmitted movies. Compression algorithms work by mostly ignoring each frame's composition and instead storing only the changes in the video from frame to frame, so-called “diffs.”

 The transition from one frame to the next is compressible, then, to the extent that it is predictable. Fast movies with a lot of action and cuts, like superhero spectaculars, are hard to compress because of the extra diffs. Slower movies with subtle changes frame-to-frame are easier to compress since the memory required to store and transmit the diffs is small.

 This is analogous to how our own minds work. When we’re left to a single, focused task, we can be remarkably productive. But in the modern workplace, emails, Slack messages, and texts interrupt us more than 150 times a day, and our productivity suffers. Computer engineers call the switch from one task to another a “context switch,” and they don’t like it. Thus, the compression algorithms above. But humans are subject to these context switches, too. Experiments have shown that the average time to recover brain function after a context switch, like interrupting writing this blog post to check an email, is more than 20 minutes. Multitasking is a myth, and most of us spend most of our days in constant recovery from these context switches.

 Now think of how interactions with doctors tend to go. After you’ve traveled 37 minutes traveling to the appointment and spent 64 minutes waiting for her, your doctor enters the room to greet you, often without having reviewed your chart ahead of time. She asks you an open-ended question about how you’re doing, and after a few seconds of pleasantries, you get to your chief complaint for the visit, like your stuffy nose or your back pain or your constipation. The doctor, who is likely trying to type into an electronic health record as you speak, interrupts you after an average of 11 seconds. Then, a nurse knocks on the door to tell your doctor that she has a call from the hospital radiology department on the line. Your doctor leaves the room and comes back a few minutes later, visibly frazzled. You do your best to get the rest of your constipation story out before your doctor sets down her laptop and asks you to climb onto the exam table for an exam. She mostly makes small-talk during the brief exam, then takes a minute to record her findings in the EHR while you wonder if you should peruse the two-year-old copy of People magazine hanging on the wall. You are left to accept the doctor’s recommendations that are based more on pattern recognition and a knowledge of disease epidemiology than any deep thinking about your specific pathology. So she’s wrong about five percent of the time.

 Don’t think of this scenario as a mark against your doctor. Think instead of the system in which she works. How many context switches did your doctor have to navigate to get to the end of your visit? When we point out negative health outcomes in this blog, like the fact that only half of indicated care is delivered to a given patient or that a quarter of care that is delivered may be unnecessary, we’re not out to get doctors. A doctor writes many of these blog posts, and reads all of them. What we’re trying to illuminate are systemic problems.

 Let’s magically teleport you and your doctor into a different system. This time, your doctor has reviewed your chart prior to your visit in a preplanned team “huddle” with her nurses and staff in which your preventive needs have been thoroughly reviewed according to USPSTF guidelines. Your chronic care needs have been addressed mostly outside the clinic visit by periodic communication with a community health worker and a nurse. You’ve sent important biometric information like blood pressures, weights, blood glucose levels, or peak airflow testing, to your doctor’s office already through a secure device or portal. When you get to the clinic, a medical assistant spends twenty minutes with you confirming critical elements of your history, sending predictable refill authorizations to the pharmacy, and predicting changes to your medications based both on the information you’ve sent and on your conversation. Your doctor enters the room knowing that most of your predictable care has been addressed already, and she can confirm or reject the changes in your predictable care that have been “compressed” by the clinical processes in place. Then, she can use most of her brainpower to take care of any unpredictable changes, what the software engineers might call “diffs,” like your new back pain or constipation. And this time, your doctor comes with a medical scribe to take notes for her, so that she doesn’t have to “text and drive” with you in the passenger seat. (in the future, she’ll likely rely on an “ambient” artificial intelligence program to document your visit, but that’s a topic for another day)

Maybe it’s not a surprise that multi-hundred-billion dollar companies get things right sometimes. Netflix has invented a better way for doctors’ offices to function. They just don’t know it.

[disclosure: KBGH receives funding from the Centers for Disease Control and the Kansas Department of Health and Environment to promote team-based care, including community health workers]

As the Medical Director of the Kansas Business Group on Health, I’m sometimes asked to weigh in on hot topics that might affect employers or employees. This is a reprint of a blog post from KBGH.