Don’t Think About Possibilities. Think About Adjacent Possibilities.

Imagine that the receding COVID-19 pandemic had happened ten years ago. What would we have done for work? Would we have simply masked up and soldiered on as folks did with the 1918 influenza pandemic and accepted the inevitable, staggering death toll? Would we have suspended all business for a few weeks or months and used even more generous government borrowing and spending to keep our heads above water?

Fortunately, most of us didn’t have to make those choices. (“Essential workers,” like folks working in shipping, grocery stores, health care, and other fields, did have to make those choices, and we should recognize and applaud their work and sacrifice). Most of us had access to computers and high-bandwidth internet connections that allowed us to transition our work or school to a virtual space. But that would not have been possible even ten years ago. At that point, neither the software nor the internet was ready. The development of widely available broadband and the subsequent development of Zoom, Microsoft Teams, WebEx, GoToMeeting, Google Teams, and a half-dozen other virtual meeting platforms is a good example of the “adjacent possible,” the most famous idea brought forth by the physician and theoretical biologist Stuart Kauffman.

In his book “At Home in the Universe,” Kauffmann described early earth as (I’m paraphrasing here) a “primordial stew.” Atoms and molecules collided with each other and transformed each other in infinite ways, eventually sticking together into a set of new molecules that self-organized and self-replicated in a process we now call “life.” In his typically mathematical way, he points out how close to “infinite” he means when he talks about those new molecules:

“Biological proteins use 20 kinds of amino acids — glycine, alanine, lysine, arginine, and so forth. A protein is a linear sequence of [amino acids]. Picture 20 colors of beads. A protein of 100 amino acids is like a string of 100 beads. The number of possible strings is just the number of types of beads, here 20, multiplied times itself 100 times. That’s 10¹²⁰, or a 1 with 120 zeroes after it. Even in these days of vast federal deficits, 10¹²⁰ is a really big number. The estimated number of hydrogen molecules in the entire universe is 10⁶⁰. So the number of possible proteins of length 100 is equal to the square of the number of hydrogen molecules in the universe [emphasis mine].”

The complexity of life on earth, which is so daunting at first glance, seems much more inevitable when the interaction between such a vast number of molecules is considered. Here, a “trial” is two molecules interacting with the potential to form a new, novel molecule:

“Assuming that a “trial” occurs in a volume of one cubic micron and takes one microsecond, Shapiro calculated that enough time has elapsed since the earth was born to carry out 10⁵¹ trials, or less. If a new protein were tried in each trial, then only 10⁵¹ possible proteins of length 100 can have been tried in the history of the earth. Thus only a tiny portion of the total diversity of such proteins has ever existed on the earth! Life has explored only an infinitesimal fraction of the possible proteins.”

In the multi-billion-year history of planet Earth, we’ve experienced a tiny, tiny fraction of the proteins that could exist! The potential for other combinations of amino acids in new proteins represents the adjacent possible. Science writer Steven Johnson takes a more poetic and less mathematical approach to the adjacent possible. He describes it as “a kind of shadow future, hovering on the edges of the present state of things, a map of all the ways in which the present can reinvent itself.”

I went into this week’s blog post with the plan to talk about how the history of health insurance intersects with American ideals, what with Independence Day coming. But I veered into this topic instead because it seems the most American of all. We experience the health care system as it exists. We assume that its current temperature is what it always has been and always will be, like fish who don’t realize the temperature of their water or even know that water exists. But suppose we step back and see the tiny innovations happening in health care and the little experiments that succeed and fail daily. We can imagine an adjacent possible where everyone’s lives are better.

When you examine your benefit design, I hope you can keep that in mind. Paraphrasing Bill Gates, we all tend to overestimate the change that will take place in the next year, but we underestimate the change that will take place in the next decade. Good administrators, like good politicians, make changes that are popular and make people’s lives better. Think of minor problems in your benefit design that you can try to fix now. Some will fail, some will succeed, but in ten years, the effort to change them could genuinely transform health care. Just as we’ve not yet experienced the vast majority of possible proteins in Earth’s history, I’m confident that since the founding of the first American health insurance plan in 1850, we have tried only a tiny fraction of potential combinations of innovations in health care delivery.

Happy Independence Day.

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.

About that BMI...

We here at the Kansas Business Group on Health are big on the BMI (no pun intended). The “body mass index,” which compares a person’s weight in kilograms to the square of his height in meters (BMI = kg/m2), is a very crude predictor of metabolic health. I’m willing to bet that if you’ve used a commercial health risk assessment for your employees, the vendor calculated everyone’s BMI. But when we use a standard like the BMI, we’re obligated to discuss its limitations.

The BMI is not a recent, cutting-edge invention. Belgian polymath Adolphe Quetelet first described it in the 19th century. After a couple of relatively fallow centuries in the scientific literature, it reemerged in 1972 thanks to legendary University of Minnesota nutrition researcher Ancel Keys. But the cutoffs for what constituted normal or excessive body weight for a given height were hard to settle on. At first in the United States, data from the second National Health and Nutrition Examination Survey (NHANES II) were used to define obesity in adults as a BMI of 27.3 kg/m2 or more for women and a BMI of 27.8 kg/m2 or more for men. Investigators based these seemingly arbitrary numbers on the gender-specific 85th percentile values of BMI for persons 20 to 29 years of age in NHANES II, the years 1976-1980, a big problem considering the year-over-year growth of excess body weight in America. Then, in 1998, an NIH expert panel elected to adopt the World Health Organization (WHO) classifications for overweight and obesity. Since then, we’ve considered a BMI of ≥25.0 kg/m2 to be “overweight” and a BMI of ≥30.0 kg/m2 to be “obese.” The American Medical Association declared obesity a disease in 2013, using the same definitions. Nowadays, the US Preventive Services Task Force, the independent panel whose recommendations underlie which preventive services are paid for by insurance, recommends screening all adults and children over age six with a BMI. However, experts still define childhood obesity as a BMI ≥95th percentile rather than a hard cutoff as in adults.

Defining an abnormal body weight in hard numbers like this has its advantages. In theory, it removes subjective judgment from the clinician or the patient on the shape of the patient’s body and simply places everyone in a category of risk. We use these cutoffs in our work here at KBGH in CDC-funded work. A person with an “overweight” BMI of 25.0 kg/m2 or above, for example, qualifies for the Diabetes Prevention Program, a one-year behavioral change program meant to reduce the risk of developing diabetes over time. Since the Diabetes Prevention Program has been shown to increase quality of life, decrease absenteeism, and lower the cost of care, we encourage folks to see if they qualify.

But given its long pedigree and the crudeness of the measure, it comes as no surprise that the BMI and similar measures have some shortcomings. As early as 1942, investigators showed that professional football players initially rejected for military service due to elevated weights relative to their heights actually had smaller proportions of body fat than nonathletic young naval men. A later NFL Study revealed that some players, even at positions not typically associated with body mass, such as wide receivers, had elevated BMIs due to their massive muscles. The BMI does not take into account body composition, after all.

And we’ve long known that different racial groups (speaking of measures with some shortcomings) have different BMI “cutoffs” for risk of disease. The recognition that different BMI cutoffs should trigger actions to prevent complications has caused investigators to try to identify ethnicity-specific BMI cutoffs. A new study in the Lancet attempts to do just that.

Investigators looked at millions of visits of non-diabetic patients to primary care offices over about thirty years. They collapsed the self-reported ethnicities of the patients into five categories: White, South Asian, Black, Chinese, and Arabic. Since the study was in England, the population was overwhelmingly white (90.6%), so take that into account as you interpret the results.

They used the White BMI cutoff of ≥30 kg/m2 as their reference group and compared everyone else to the risk in that population. The numbers showed that to equal the diabetes risk of a population of White patients with a BMI of ≥30 kg/m2, other ethnic populations would need to exceed the following cutoffs:

• South Asian: ≥23.9 kg/m2

• Black: ≥28.1 kg/m2

• Chinese: ≥26.9 kg/m2

• Arabic: ≥26.6 kg/m2

They concluded that “Revisions of ethnicity-specific BMI cutoffs are needed to ensure that minority ethnic populations are provided with appropriate clinical surveillance to optimise the prevention, early diagnosis, and timely management of type 2 diabetes.” That is, in the opinion of the researchers, we need to take into account the self-reported ethnicity of the person when we decide how risky their BMI is. I guess I’m on board with this recommendation as long as we don’t use the data to stigmatize but instead to non-judgementally and proactively address health risks.

If your company is interested in getting more employees at risk of diabetes into the Diabetes Prevention Program, please contact us!

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.

Do Medication Rebates Harm Patients? Yes.

Medication rebates are by now a time-honored part of employer-sponsored health insurance. How do they work? Let’s assume a drug costs $100. A substantial fraction of that, as much as $66 or more in the case of insulin, goes not toward the cost of the production of the drug, nor for pure profit on the part of the manufacturer, but back as a “rebate” to you, the employer (~90% on average, according to CVS and Express Scripts) and to the pharmacy benefit manager (PBM).

Let’s examine the incentives at work in this system. Imagine that KBGH Project Manager Matt Thibault were to invent a magically effective new cardiovascular drug tomorrow that cost only $2 per dose. This drug would soon be in the hands of every high-risk cardiovascular patient in America, right? Maybe not. At a price of $2, no PBM would likely be interested in having the drug on formulary because the potential for the PBM to make money off the drug in the form of rebates (or, for that matter, on spread pricing, a topic for another day) is tiny; any percent of $2 is a small amount of money.

Make that same drug $20 per dose and offer a 50% rebate split between the PBM and the employer, though, and now we’re getting somewhere. PBMs routinely move drugs up the formulary list in exchange for greater rebates. This has led to rebates being renamed, perhaps more accurately, as “kickbacks.” The incentives are aligned, then, to make sure the drug is as expensive as possible in order to maximize kickbacks to the PBM.

It would be one thing if consumers at the retail pharmacy level could see this happening and make a decision on where to buy their medications. But rebates are strictly confidential (although that may change soon). In order to keep rebates secret, PBMs also have to keep net prices—the cost of the drug after applying the rebate–confidential. To avoid having to say what the net price is, insurers typically require anyone with coinsurance to pay for a percentage of the retail pharmacy list price, not the secret net price.

It isn’t hard to predict where this system ends up. Drugs inevitably get more expensive, PBMs make more money than the drug companies they ostensibly help with supply chain issues, and patients (a.k.a., your employees) bear the burden in the form of increased list prices. A recent study in JAMA Health Policy (paywall) bears this out.

Investigators estimated the effective out-of-pocket share of drug costs that would have been paid by a hypothetical patient from 2014 to 2018, taking into account both initial coverage, a “coverage gap” (as in Medicare Part D), and a catastrophic coverage phase. In the study years, the average list price–what the drug costs, rebate included–per unit increased 29%. The average net price–the cost of the drug after applying the rebate–increased only 7%. The huge divergence between list and net prices was completely due to a 98% increase in average rebates.

This astonishingly high list-to-net ratio grew fastest for drugs with branded and generic competitors, from 2.7 in 2014 to 3.4 in 2018. The list-to-net ratio grew, but more slowly, for drugs with branded competitors only (from 1.4 to 1.6) and drugs without any competition (from 1.2 to 1.4). So we have yet another example in the paradoxical medical economy in which competition, rather than decreasing cost to the consumer, increases cost to the consumer (again, a topic for another day).

Americans do not overconsume medical resources. American health care is expensive almost exclusively because of flawed pricing structures. We simply pay more for any given service, medication, or outcome than people in peer countries do. Yet almost every intervention employers implement is designed to reduce consumption, and relatively few interventions are aimed at pricing. Rebates inherently increase the price of medications to the consumer and inevitably lead to less adherence to prescribed medications.

So don’t wait for new PBM transparency laws to take effect. Have a frank conversation about how you want medication prices to work in your employee health plan. A simple first step that doesn’t go all the way to a pure, “pass-through” PBM relationship, is to tell your insurer that you want to include “point-of-sale rebate pass-through” with your plan. This would pass the rebate payment through to the consumer (your employee) at the point of sale, reducing their out-of-pocket obligation by ensuring that their coinsurance applied only to the net price. Your employees will thank you.

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.

Is the Time Over for Overtime?

If you have a lot of hourly employees, chances are they like overtime, or, more precisely, most of them like overtime pay. In 2016, the World Health Organization estimates that 488 million people worldwide worked at least 55 hours per week.

But evidence is emerging that excess overtime may be bad for workers’ health. A recent study from the World Health Organization found that people working more than 55 hours a week were 35 percent more likely than their peers working 35-40 hours a week to have a stroke and 17 percent more likely to die of heart disease. The study was methodologically sound; the authors published their protocol ahead of time, which is generally a sign of a robust analysis. But it was observational. Employees weren’t randomized to work longer or shorter hours.

So the somewhat histrionic headlines you may have seen about this study that scream, “Overwork Killed More Than 745,000 People In A Year,” should perhaps more accurately say, “working 55 hours or more per week was associated with 745,000 additional deaths out of a population of 488 million workers.” It is possible, after all, that other factors in these super-workers contributed to their bad outcomes. Salaried employees are more likely to have health insurance. Increasing workers’ wages tends to result in lower smoking rates. And we know that the routine stresses of life, like paying bills, paying for medications, finding childcare, and doing everyday routine self-care, are associated with worse health outcomes in people with less income. It’s possible to construct a mental model that, instead of blaming the excess vascular disease on the extra work hours, pins the blame on the workers’ lack of resources. In that model, the extra work hours are a symptom of the greater problem, not the cause of the health outcomes. In other words, are better outcomes in non-overtime workers due to working less overtime, or are they due to simply having more money?

Regardless, this study and others like it point to potentially beneficial strategies we could employ with our workforce. Some radical workplaces, arguing that the eight-hour workday is a relic of 19th-century socialism, have experimented with a six-hour workday, with special training for employees in increasing productivity. If the employees can accomplish in six hours what they used to achieve in eight, they get to keep the money they’d earn in eight hours, but they get two “free” hours a day. The company saves the overtime pay, saves the overhead of two more hours of office time per day, and if the study results at the top of this post are to be believed, saves the human and financial cost of additional disease burden.

Have you noticed any relationship between your overtime “super-users” and their health outcomes? Let us know what you’ve done about it, and we’ll share.

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.

Vaccines: Influence, Not Mandate

The vaccines against SARS-CoV-2, the organism that causes COVID-19, are a slam-dunk, whether in terms of their economic impact, a humanistic perspective, or an observed reduction in morbidity and mortality. And the United States as a whole is doing reasonably well in getting people vaccinated (although Sedgwick County is a little behind the national average). As of the writing of this blog post, more than half of US adults have received full vaccination, and a large additional fraction has received at least partial vaccination. And while I’m not particularly interested in the pursuit of a theoretical threshold like “herd immunity,” most everyone agrees that the more people we can get vaccinated before this fall, the better. After all, the virus is still spreading among the unvaccinated population as quickly as it was at its peak.

Some universities are mandating vaccination. I can understand why. But my instincts always trend more toward influencing decisions rather than mandating behaviors. So it was helpful (and, I’ll admit, a little discouraging) to see that the Equal Employment Opportunity Commission (EEOC) recently ruled on using incentives to get employees vaccinated. In short, and to steal from our frequent collaborator Al Lewis:

“If employers set up a system in which they administer the vaccine themselves on a voluntary basis, businesses can also offer employees incentives — be they perks or penalties — so long as they are “not so substantial as to be coercive.”

If the process of setting up vaccine distribution yourself sounds tricky, you’re right. The new mRNA-based vaccines, in particular, while scientific marvels, are pretty delicate and require special handling. So we anticipate most of our members will utilize more traditional routes to vaccination, like clinics and health departments. How can we get our employees to take that leap?

In thinking out loud about this question, I’m cross-tabulating two sources. Source one is the new edition of Influence by Robert Cialdini, a seminal text in the science of persuasion. Source two is a summary by German Lopez, based mainly on Kaiser Family Foundation survey data, on the six overarching reasons some Americans are slow to be vaccinated: lack of access, lack of fear of COVID-19, fear of side effects, lack of trust in vaccines, lack of confidence in institutions, and conspiracy theories.

Let’s discuss how Cialdini’s Seven Keys to Influence might address those six big reasons for slow vaccination and how we can apply them to get more people immunized:

1. Reciprocity. Pharmaceutical representatives don’t give out medication samples, tchotchkes, and meals to doctors’ offices out of charity or even advertising. They do it to cause a feeling of indebtedness on the part of the clinical staff. Doctors who receive these gifts are far more likely to prescribe medications represented by salespeople than are doctors who don’t receive the gifts. The same goes for people who’ve received free address labels from a charity. We can copy this strategy in our employee populations by pointing out the generosity of our leave policies around COVID-19 infections or exposures. The company is doing this for you. All we ask in return is that you do your part by reducing everyone’s risk by getting vaccinated. And we’ll even help give you time off and help you get to the vaccination distribution center!

2. Commitment. When a company asks you to sign up for their newsletter, “club,” or punchcard, they’re trying to get a commitment from you, however small it may be. Consider asking your employees to sign up for a newsletter from your wellness department or vendor, and make sure vaccines are mentioned in nearly every edition.

3. Social proof. Colleges and universities once tried to discourage binge drinking by pointing out how many students were injured or killed by binge drinking behavior. It didn’t work. When those same colleges and universities pivoted to a strategy of showing how many students did not binge drink, they saw results. People do what they see others doing. So once you have an idea that a big chunk of your employees has already been vaccinated, point this out in a campaign and emphasize how proud the company is of its employees’ contribution to safety. Even an employee who doesn’t particularly fear infection may want to be part of a positive culture.

4. Authority. People trust authority figures. In the vaccine world, people trust their personal physicians most of all. So if you feel your vaccine push is falling short, encourage employees to see their doctor to talk about the minimal risks and potentially huge benefits of vaccination.

5. Liking. People prefer to be seen positively by their peers. This desire can often override other emotions or beliefs like a lack of trust. If we can make vaccination the norm in our workplace and point out the positive effect of people who’ve received the vaccine, a certain number of people will experience a change of heart.

6. Scarcity. When Amazon alerts you, “Only two remaining in stock,” they’re taking advantage of our attraction to scarce resources. Gold and platinum would not be expensive and desired if you could dig them out of your backyard with a shovel. So this summer, as we anticipate another rise in COVID-19 cases in the fall, we should point out the scarcity of time to take advantage of vaccination. Only three months left!

7. Unity. This principle takes advantage of our natural tribal instinct toward “Us versus Them.” When the anti-smoking Truth Initiative debuted, it used this exact trick by casting Big Tobacco as an opponent to be defeated by a unified, righteous group of young nonsmokers. The effect on the youth smoking rate, pre-vaping, was astonishing. By one estimate, it prevented 300,000 kids per year from smoking. The Truth Initiative essentially turned the Big Tobacco companies into conspirators and encouraged kids to rebel. And it worked.

Our goal shouldn’t be to trick anyone into doing something they don’t want to do. But in working to get the largest possible fraction of the population vaccinated, we should use the best, most scientifically sound arguments and strategies we can.

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.

Doctors, like orange juice, are better with breakfast

When I was a medical student, I thought I wanted to be a radiologist. I love the science. I like the physics of radiation, and my ego was invested in the idea of being a “doctor’s doctor” that other doctors looked to for wisdom and interpretation of diagnostic testing. Radiology checked all those boxes without the ooey-gooey autopsies and whatnot that are part of the daily routine of pathologists.

Then I did a radiology rotation.

I truly did like the science of x-rays and the conversations with other doctors and all the rest. I discovered one problem, though: I could not stay alert for hours at a time in a dark room looking at films. Come two or three o’clock in the afternoon, I would inevitably start to fade. Once, I even nodded off in the radiology suite. So, with the safety of future patients in mind, I decided to go a decidedly more well-lit and upright route, eventually completing a residency in internal medicine and a fellowship in endocrinology, diabetes, and metabolism. If nothing else, the work in endocrinology was ambulatory. If I’m moving, I can’t fall asleep.

I review my personal history as a wind-up for a research paper in JAMA Health Policy this last week (paywall). Investigators looked at records from primary care practices–these studies always pick on primary care docs–to see how likely a patient was to receive a “statin” medication depending on the time of day of his or her appointment. This is no casual question. Viral pandemics aside, cardiovascular disease remains the leading cause of death in the United States. Appropriate use of statin medications like atorvastatin (Lipitor), rosuvastatin (Crestor), and others dramatically reduce the risk of death from any cause in people at risk for heart disease.

Using United States Preventive Services Task Force (USPSTF) guidelines, which state that we should offer statins to anyone with known vascular disease, anyone with a diagnosis of a genetic problem called “familial hypercholesterolemia,” or anyone with a low-density lipoprotein (LDL) cholesterol level of 190 mg/dL or more (among other diseases like diabetes), the researchers found a disturbing trend. Compared with 8 am appointments, which the investigators used as their reference group, the likelihood of getting a statin was lower at all hours except 9 am. And the likelihood of getting a statin pretty consistently fell as the day went on: 88% at 9 am, 63% at 12 pm, and 69% at 3 pm. Overall, you were only 69% as likely to get an appropriate statin prescription in an afternoon appointment as you were in a morning appointment. Here’s the raw, “unadjusted” data:

JAMA Health Policy

And yes, radiologists make more mistakes later in their shifts, too. But this phenomenon is not limited to doctors. Judges sentence defendants more harshly just before lunch, when they’re hungry, and sentence more leniently after a break. Car crashes peak between 5 and 7 pm. Students taking standardized tests perform better earlier in the day and recover performance after rest. If you’re like me, you may have found that you do your best creative work earlier in the day, and you’re better off going to meetings or working on a task list later in the day.

The wellness industry has long coached patients to get the earliest available appointment of the day, but our reasoning has had more to do with the fact that if you go earlier in the day, you’re less likely to have to wait. With this data, we have to consider not only the time in the waiting room but the outcome of the visit.

[Disclaimer: the Kansas Business Group on Health has CDC funding to encourage appropriate use of statin medications.]

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.

What Health Care Can Learn From Netflix

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.

How Do Doctors Self-Refer?

In my full-time clinical practice days, other practitioners often referred patients to me for accidental findings on x-rays, ultrasounds, or MRI exams. Sometimes a patient would have had a CT scan of her abdomen that revealed an asymptomatic tumor inside her adrenal gland. More often, an ultrasound of the carotid arteries or an MRI of the spine uncovered a mass within the thyroid gland. This phenomenon is so common that these discoveries have a name: “incidentalomas.” Never accuse doctors of not being wordsmiths.

For thyroid incidentalomas, I would usually drag a portable ultrasound machine into the patient’s room and get a quick look at the lesion with my own eyes. Through reasonably straightforward criteria, the patient and I could choose whether or not to biopsy, to repeat an ultrasound in a year or two, or to forget we ever saw the lesion. I never charged extra for these informal bedside exams. I considered this particular use of the ultrasound machine akin to a 21st-century stethoscope. I wouldn’t charge a patient an additional fee for listening to her heart or lungs, so it didn’t seem proper to charge them for this use of ultrasound. That wasn’t charity on my part; this philosophy is becoming so prevalent as to have guidelines crop up around it.

But sometimes, I saw features in a thyroid nodule or a lymph node that made me think the lesion should be biopsied, usually by me. And I was paid well for these procedures (technically, the University of Kansas was well-paid since I was salaried. I made the same amount of money whether I did the procedure or not). A thyroid biopsy, which takes maybe ten minutes, pays about the same amount as caring for a diabetic patient for a year (thank the RUC). The revenue from diagnostic studies comes not only from the professional fee, which pays the doctor for her interpretation and consulting regarding the study but also from a “facility fee” meant to cover technical costs surrounding the maintenance and use of special equipment. A physician who owns the equipment needed to perform labs or imaging can profit by collecting both of these fees. So the incentive for me or any other doctor to do imaging or procedures in our own practices–so-called “physician self-referral”–is considerable.

Stark laws arose a few decades ago to discourage physician self-referral and kickbacks from referrals to other physicians, but they made specific exceptions to allow “necessary testing” in physician offices. Once upon a time, the American Medical Association Code of Ethics prohibited doctors from owning imaging or lab equipment. The AMA said doctors should not have a financial interest in testing. But that rule eventually changed, and now, the AMA is much softer on physician-owned testing, insisting only that doctors make diagnostic and treatment decisions without taking financial issues into account. The trouble is, from a financial standpoint, that philosophy probably doesn’t work.

Doctors are human, and physician-owned imaging and lab centers unequivocally appear to drive up the cost of care by increasing the likelihood of getting additional procedures without improving outcomes. In a tiny sample of the literature on this topic, a group of researchers has shown that MRI scans of the neck, lower back, knee, and shoulder, when performed in physician-owned machines, are much more likely to be normal, indicating overuse by the physicians who own the machines and bill for their use. Multiple studies show that physician-owned hospitals are associated with an increase in spending without a corresponding increase in quality, a phenomenon that leaks into the outpatient setting as well. For example, physicians, particularly those treating immune or malignant diseases, routinely sell drugs to their patients at a small markup. Some physicians make more of their income from such practices than they do by seeing patients. Their incentive is naturally toward using more expensive drugs, whether they consciously intend to or not.

This is the part of the post where I propose a brilliant policy strategy. Except I’m not sure there is one, apart from the transparency rules we’ve discussed at length on this blog. Physician-owned testing, after all, does come with some benefits. Patients can often get the test performed on the same day and in the same location. Since doctors are so powerful, there’s likely not a movement afoot to take their radiology machines away.

But by using more direct contracting with physicians, we could limit the incentive for doctors to overuse certain diagnostic and therapeutic procedures. If I had been paid a flat monthly rate to take care of the endocrine needs of Corporation X in my example in the intro, I would have simply done the necessary procedures on patients without even thinking of the cost to the employer or the patient or thinking of my potential income. The few hundred bucks I might have made from a couple of thyroid biopsies would have been folded into my fee for caring for the entire population.

If you have past experience with direct physician contracting (or with frustrating up-charges from doctors self-referring), please let us know. We would love to better understand the experiences of our members around this issue.

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.

How Much Health Should Flow Through Your Smartphone?

We at KBGH get pitched a lot of apps. Apps for blood pressure, apps for blood sugars, apps for lab and imaging pricing. Lots of apps. In the roughly two years that the current staff has been at KBGH, I think pitches from outside companies have covered most of medicine in apps, save a few small nooks and crannies. I don’t think we’ve been pitched a fertility app yet, for example, but I might be mistaken. And this isn’t an ivory tower problem for us; we’re in on the creation of apps as well. We’re working with WSU’s College of Innovation & Design on a Rural Health Challenge to, in part, help connect rural patients with their doctors via technology. That technology may include smartphone apps since, according to a Cochrane review, there is “low-certainty evidence of the effects of mobile phone-delivered interventions to increase adherence to medication prescribed for the primary prevention of [cardiovascular disease].”

But, as we’ve blogged about before, your computer or smartphone may not be the most direct route to a healthy, happy life. Excess time on devices, particularly that spent on social media, may be bad for us and may paradoxically exacerbate loneliness and isolation. So how much of our medical care should run through our phones? I’m generally optimistic about the future of telemedicine, but I’m pessimistic about the attention economy, in which companies are incentivized to grab increasingly big chunks of our time.

Regardless of my opinion, though, people have thought hard about what should go into a good medical application. Here are four elements paraphrased from Swiss investigators Kenny R. Lienhard and Christine Legne:

1. Mobile medical apps should guide a patient through every step of instruction, setup, clinical measurement, and analysis and feedback. Imagine that you just downloaded an app to your smartphone to help communicate blood pressures to your doctor. The app shouldn’t just tell you how to send the blood pressure. It should give you instructions on the technique for where to place the cuff. It should provide feedback if it senses your technique is wrong, like if different readings get very different results. It should help you analyze the numbers; if your blood pressure is consistently high or low, it should prompt you to talk to your doctor about it.

2. The user interface should be adapted to cope with patients’ physical and cognitive restrictions. This goes without saying. The American Medical Association (AMA) recommends that health care materials be written at or below a sixth-grade reading level. But the interface should also account for people with impaired vision or hearing or differences in dexterity, to name a few.

3. A mobile medical app should build on a robust medical knowledge base, ensuring an evidence-based approach to mobile app design. This one is tougher because most of us–present company included–don’t necessarily know the ins and outs of app design. But manufacturers can search out the best medical advice for many circumstances and account for those in the testing of the app.

4. Mobile medical apps should facilitate both patients’ and physicians’ routines. This is crucial, and it applies directly to work we’ve done at KBGH. It is great to get blood pressure results to your doctor. But it’s even better if the app, upon seeing those blood pressure results, can make a treatment recommendation to your doctor. We call this “decision support.” The app may give bad advice once in a while, like recommending a thiazide diuretic for a gout patient, but making more sophisticated decisions is what the doctor is there for.

What experiences have you had with medical apps? Let us know!

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.

Health Care Proxy Shoppers

Over the weekend, I was listening to some health policy podcasts while gardening, as one does, and the surgeon and medical waste researcher Dr. Marty Makary was interviewed on Freakonomics. He mostly didn’t talk about surgical techniques or hardcore quantitative measures of wasted health care dollars, though. Instead, he outlined his mother’s strategy in grocery shopping. Mrs. Makary is a bargain shopper. While I might just grab a couple of lemons from whichever store I’m in when I think of it, she carefully compares prices between stores and buys the cheapest option. People like Dr. Makary’s mom make up only 10-20% of all shoppers, he said, but they hold down the price of lemons for the rest of us. Economists call them “proxy shoppers.” Just like proxy voters, they make decisions about the cost of lemons for all of us.

Dr. Makary shared this vignette to illustrate how price transparency may help contain costs in medicine. It got me thinking: Who are the proxy shoppers in medicine? Price transparency is increasing, after all, but patients still don’t use it as much as one might expect. And while there are ways to encourage patients to use price transparency, especially as it relates to their out-of-pocket expenses and deductibles, ultimately, the contract they’re working with barely involves them. As Larry Van Horn says in the Freakonomics episode, business-to-business contracts in medicine between a payer and a health system include a third party (the patient) who has no say in the contract at all.

So the proxy shoppers in medicine mostly are not patients. The actual proxy shoppers are the people most likely to be reading this blog post, like the HR professionals and benefits specialists who plan, coordinate, and pay for their employees’ health care. And we should use our power as proxy shoppers carefully.

That’s it. That’s my post. I don’t mean to be a downer. I know you have a lot on your plate already, trying to manage the benefits of dozens or hundreds or even thousands of employees’ benefits. But the next time you sit down to negotiate a contract, I hope this is in the back of your mind: You have a power like almost no one else’s to hold down the cost of medical care in a country where it’s genuinely out of control. You can pick up the lemon that’s closest to you and pay whatever it costs, or you can check the price of that lemon in the grocery store down the street.

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.

Can We Trust Information on YouTube?

Once upon a time, in my academic career, I worried that inaccurate mass media depictions of, say, diabetics would cause people to make bad care choices. If you’re thinking of Julia Roberts in Steel Magnolias right now, trust me: Julia Roberts in Dolly Parton’s hair salon is the tippy-tip of the iceberg. Now I worry more about YouTube, the modern-day Library of Alexandria of instructional videos.

In the past year or so I have watched YouTube videos, off the top of my head, to learn to: change a blinker bulb in my car, fix my thermostat, learn to run specific reports within Quickbooks, refresh my memory on how to do certain math problems for helping with my daughter’s homework, and shut off the “move to wake” feature in my iPhone. And dozens more.

But I’ve also used YouTube in the past to remind myself how to reduce my son’s dislocated elbow (my son’s orthopedic history gets more complex by the year). There’s an old saying in medicine: “see one, do one, teach one.” I needed to “see one” again before I subjected my son to it. The procedure was successful, for what it’s worth. (Being a doctor’s kid is weird. I digress.) Are you scheduled to have your thyroid gland removed? YouTube can show you the procedure. Are you a new type 1 diabetic who wants to practice carbohydrate counting for insulin dosing? Boom. Starting chemotherapy and interested in using cooling therapy to reduce hair loss? Look no further. Recently we talked about the reliability of physician rating sites (spoiler: potentially useful, but with major caveats). How do YouTube videos stack up for general medical information? For the purposes of this post, I’m mostly ignoring obvious conspiracy-mongering about COVID vaccinations, cholesterol medications, and whatnot. Like pornography, I trust that you’ll know those when you see them.

To get an answer on the accuracy and utility of YouTube videos for medical inquiry, I looked not to YouTube, but to PubMed, the search engine of the National Library of Medicine. Here’s what I found:

YouTube contains so much information that investigators tend to categorize it by learner, generally either medical trainees or the general public. Videos for medical trainees seem to be relatively generously reviewed by researchers. Using our example of thyroid surgery from above, one study found that most YouTube thyroid surgery videos were posted by surgeons operating in academic institutions, which they took to mean the intentions of the videos were purely educational and not promotional. But the researchers also noted that surgeons who had no history of traditional academic publications–i.e., not necessarily the most respected people in the field–posted the majority of surgeon-sourced videos. This led the authors to conclude that “Trainees and educators alike should critically analyze the quality of video content,” which is the academic equivalent of throwing shade. A systematic review of studies of YouTube videos aimed at medical learners backed this up, concluding that “While videos authored by academic physicians were of higher quality on average, their quality still varied significantly,” and “Video characteristics and engagement metrics were found to be unreliable surrogate measures of video quality.” That is, a video’s slick production and millions of views did not mean it was accurate.

Videos aimed at the general public tend to be more harshly judged. One study by two emergency room doctors investigating the quality of videos pertaining to the management of low blood sugars went so far as to say that “health videos should only be uploaded by physicians,” a statement hilarious in both its confidence and its wrongness. Surely someone without a medical degree somewhere, at some point, has been filmed saying something accurate and helpful. But, in general, the quality of public-facing YouTube videos does appear to suffer in comparison to professional learner-directed videos. A systematic review from 2015, admittedly ancient history in internet years, concluded that “YouTube contains misleading information, primarily anecdotal, that contradicts the reference standards and the probability of a lay user finding such content is relatively high.” But, on the bright side, they also found that “videos from government organizations and professional associations contained trustworthy and high-quality information.” We at KBGH, who have produced and posted videos of our own, hope that we fall into that category.

Let’s bottom-line what we can take from this research. First, beware of any video that makes claims that seem extraordinary. Someone who says that removing a food from your diet is as powerful as taking cholesterol medications for preventing heart attacks, for example, better have good evidence to back that statement up. Second, pay attention to the source. Videos from academic centers, government agencies, and professional associations appear to be the most reliable. But they’re also, I suspect, the most conservative. Few such organizations are willing to put themselves out on a limb compared to their peers. Finally, beware of using the number of views or shares as a marker of the reliability of a video’s contents. As we’ve discussed before in this very blog, the internet is set up to make sure the most radical statements get the most eyeballs.

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.

Do Online Physician Ratings Actually Help?

Toward the end of my full-time clinical career, I attended a speech by a physician who encouraged doctors to “own” their online personas. He said we should actively manage our social media presence, our clinic websites, and our ratings by third-party sites like Angie’s List and Yelp. Against my instincts, I took his advice and Googled myself. Reader, I don’t mean to be histrionic. Many factors contributed to the end of my clinical career. But that innocent internet search did not, to put it lightly, make me excited to show up for work the next day:

I don’t share this anecdote as a bid for your pity. My experience with online ratings represents a tiny fraction of the “feedback” that a politician or a college football coach gets daily. I share the story as an entree to a question: do online physician ratings accurately reflect the quality of care people receive? If the ratings are accurate, then we should encourage our employees to use them. If they’re inaccurate, we should encourage employees (and practitioners) to ignore the ratings.

This is no idle inquiry. Some studies have suggested that up to 60 percent of patients consider online reviews important in choosing a provider. A recent national survey (paywall) of Americans aged 50 to 80, the heart of an internist’s practice like mine, revealed that more than 40 percent had looked up a physician’s rating for themselves at some time in their lives. Women, people with higher education levels, and (predictably) people with at least one chronic condition were more likely to have looked up a physician rating. The investigators in the recent study looked at several factors contributing to how prospective patients chose a physician, and online ratings came in only ninth, behind factors like “accepts my health insurance” and “convenient office location.” But the physician’s rating was still considered important almost as often as word-of-mouth reputation among family and friends, consistent with the results of smaller surveys.

But the ratings themselves are less influenced by clinical outcomes, like death, infection, or well-being, than they are by the patient’s experience. As we’ve blogged about before, denial of a patient request, especially for pain medications or lab tests, results in a dramatic decrease in patient satisfaction. That is surely poison for an online rating, regardless of the appropriateness of the denial. A very sophisticated study of dentist ratings showed that things like wait time were strongly associated with higher ratings, while raters barely mentioned clinical outcomes like infection or tooth loss. These experience-centric ratings may also reinforce biases that we already know exist. One study showed that, globally, male surgeons were rated higher on technical skills, while female surgeons were more highly rated for interpersonal skills.

It’s hard to tell if the ratings correlate with those harder clinical outcomes. A study of orthopedic surgeons’ online ratings found no correlation between ratings and total knee replacement outcomes. And one study found that the design of the rating website itself, like the presence or absence of advertisements for other doctors on the page, affected the quality of the data. But there is a hint of better outcomes in certain situations. A retrospective study showed that patients who had hip replacement surgery at hospitals highly ranked on physician rating sites did slightly better than patients at lower-ranked hospitals, for example.

If we can draw any conclusions from this muddled body of research, it seems that the most important lessons are, first, patients should understand the limitations of online reviews. A negative review of a highly skilled oncologist who has a gruff bedside manner may obscure the fact that his staff has experience in steering patients into clinical trials that may help complex cases. His staff’s skill may only be known by other providers. And second, doctors need to learn to use their online reviews as a source of quality improvement data. Someone who gives a doctor a lousy review may well have a valid complaint. The patient experience in American healthcare hardly has a sterling reputation. Instead of simply bristling at negative reviews, doctors should use the reviews as a tool to enact positive change.

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.

Drug prices are getting more transparent, too

We’ve covered the waves of price transparency that are washing over health care the past few weeks in the KBGH Book Club and here in the blog: no more surprise medical bills, new public tools for comparing procedure prices, no more gag clauses on cost or quality, and others. But we haven’t talked about what’s coming in drug pricing transparency. Americans pay far, far more than peer countries for prescription drugs. Drug prices account for almost a fifth of our excess health spending, even more than administrative overhead and salaries. How bad is the problem? Americans make up less than five percent of the world’s population, but we account for 80% of pharmaceutical revenues.

It is easy to cast the pharmaceutical manufacturers alone as the bad guys here; they spend far more on advertising than on research and development, they are far more profitable than any other sector in the economy, they cannibalize profits to gift to shareholders, and they lobby Congress far harder than any other industry. But manufacturers are not the only players. The manufacturers only set list prices, which are publicly disclosed. Manufacturers negotiate rebates with insurers and pharmacy benefit managers (PBMs) in order to move their drugs up the list on the insurers’ and PBMs’ formularies. Rebates and discounts like this have grown to an astonishing extent over the past few years, leading to “net” prices for many brand-name drugs that are lower than list prices. As we’ve pointed out before, insulin has a typical rebate of 66%. Because the process is so opaque, consumers have no way of knowing the actual price paid for the drugs. Payers argue that this “confidentiality” (if you’re charitable; “secrecy” if you’re cynical like me) allows them to more effectively negotiate because transparency would only allow drug manufacturers to get net prices closer to their very high list prices. This is transparently false. If secrecy were such a tool for keeping costs down, the industry would not be fighting transparency rules. Instead, the manufacturers would be demanding more transparency to allow prices for their products to rise naturally. 

Manufacturers and PBMs have reason to be concerned because of the “Transparency in Coverage” final rule that was issued in 2019 as part of the usual flurry of executive orders that precede and accompany any presidential transition. The rule, which takes effect for plan years beginning January 1, 2023, requires that:

1.     insurers disclose the 1) current list price and 2) historical net price for prescription drugs,  

2.     the data be available in “machine-readable” files (that is, not blurry .pdf scans) online to allow for comparisons, and

3.     insurers provide real-time personalized estimates of cost-sharing. 

 Legal challenges may slightly change the final product prior to 2023. But the rule has unusually solid bipartisan support: both Presidents Trump and Biden support it, along with a clear majority of congressional Republicans and Democrats. So it will be difficult to overturn completely. This is all the more reason to make sure our employees are educated shoppers for health services moving forward.

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.

Do we need to coach patients how to read their notes?

Do you know what is in your medical record? I don’t mean dry lab values or x-ray reports. I mean your doctors’ interpretations of those things, along with intimate, personal details like the results of your physical examinations and their impressions of your adherence to medications and home environment. The information is about you, but it also belongs to you. But it wasn’t always available to you. The 1996 Health Insurance Portability and Accountability Act (HIPAA) gave patients the legal right to review their medical records. But few lay people other than medical malpractice attorneys knew what to do with the information. 

And electronic health record (EHR) vendors have historically treated your data as proprietary, in spite of whatever HIPAA had to say about it. The data was treated as the EHR vendor’s property and was difficult to transfer from one health record to another. Stopgap measures like the Kansas Health Information Network popped up to try to make the data transferable from one hospital or clinic to another. But even this was suboptimal. Compare your experience with your health data to your experience with your financial data, which is probably almost as sensitive. You have undoubtedly used your ATM card from, say, Intrust Bank, to check your balance at, for example, a Fidelity ATM. We take it for granted, just like I take for granted that my USB drive from my home Mac computer will plug into my work PC. I don’t have to rely on the substantial expertise of a middle man to know that the data will transfer.

Since the 1990s several experiments have led to a movement for patients to have ready access to their doctors’ notes, be they on paper or in an electronic format. The best known organization goes by the name “Open Notes.” Now, new federal rules stemming from the 21st Century Cures Act aim to promote further patient access to their electronic health records via secure online “portals.” With a few exceptions, starting April 5, 2021, clinical notes and much other electronic information must be made available free of charge to patients. And the new rule forbids health systems or electronic health record vendors from “information blocking,” the practice of treating electronic health data as a proprietary asset and restricting access. The Annals of Internal Medicine (paywall) has a nice infographic:

Annals of Internal Medicine

To help folks transition to this new world, I think employers, insurers, and health care providers need to be proactive. To start, we should encourage our patients or employees to find their health record and to discuss it with their treating practitioner. Medical records are teeming with mistakes, due to cut-and-paste, poor user interoperability, and old-fashioned errors. Patients who find these mistakes shouldn’t run straight to the nearest malpractice attorney. Instead, both the patient and the doctor might be enlightened by a discussion of what should have been in the note.

Second, we should teach our employees and patients that what is in the record is meant to be objective. It is not a subjective judgement of anyone’s value as a human being. When I was in full-time academic practice, I remember a colleague being berated by a patient for noting that the patient smelled like urine (because she did, objectively, smell like urine). But once the patient’s embarrassment over reading the note faded, she was able to have a very meaningful conversation with her doctor about her urinary incontinence, and she was prescribed a medication that helped tremendously. Without access to her record this may never have happened. 

Finally, we need to remind patients that their record is truly private. In the era of predatory social media companies we’ve largely given up on the idea that any of our personal information should be private. But Facebook is probably not the best forum in which to litigate disagreements with doctors or nurses or to share screenshots of one’s medical record.

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.

Facetime With Your Doctor Doesn't Matter As Much As You Think

Value, in medicine as in other industries, is a simple ratio of quality to cost:

 Value = Quality/Cost

As quality goes up or cost goes down, value increases. In the clinical setting, though, consider the tension that this produces: on the one hand, patients value “facetime” with the doctor. There is some validity to their desire. Studies consistently show that outcomes for patients who like and trust their doctor are modestly improved compared to patients who do not have a good relationship with their doctor.

On the other hand, more powerful studies show that it’s not necessarily the doctor-patient relationship that produces the best outcomes on a population basis (like the population of employees your company insures). Instead, it’s the careful application of care protocols.

This is hard to swallow. We’re all the stars of our own sitcoms, and we’d like to think that our doctor makes a personalized, artisanal, set of decisions for our care at each visit based on solid training and artful instinct. Unfortunately, that philosophy is not born out in the data. This is because most clinical interventions have a small effect on the individual patient. Prescribing a common older class of osteoporosis medications, for example, reduces the three-year risk of a hip fracture from three percent to two percent (a 35% relative risk reduction, but only a 1% absolute risk reduction). But that effect, which is small to the individual patient, is extremely powerful when amplified up to the population level: preventing 1,000 hip fractures in a population of 100,000 patients over the course of a few years is an amazing outcome. Each hip fracture costs more than $50,000, and hip fractures cost American healthcare purchasers almost $6 billion a year, a number big enough to really move the value equation above. The contribution of a single encounter with a patient to that outcome is almost trivial, though.

As sexy as House-style exotic diagnoses of individual patients can be, we’re better off thinking in terms of treating populations, not patients, with protocolized strategies. We’ve blogged before about examples of this, like Kaiser Northern California’s hypertension treatment algorithm that is largely executed by their medical assistants, or MAs. The MAs are overseen by the doctors, but the algorithm itself makes most of the decisions. With this approach, Kaiser has such good blood pressure control system-wide that their patients are more likely to die from cancer than from a heart attack. This is astonishing.

To the older attending physicians I worked with during my medical training, there was hardly a more biting insult than to say that someone was practicing “cookbook medicine.” They considered the decision-making process in any individual patient encounter sacrosanct. And Kaiser’s protocol is proudly “cookbook,” at least for the majority of patients. The job of the modern physician, then, is to tease out which patients may not be well-served by the “cookbook.” A small but non-trivial number of patients have underlying medical conditions, drug allergies, or other factors that may make them poor candidates for certain algorithms. These are the patients from whom the doctors should be making their money.

So the next time you’re thinking of who is going to care for your employees, especially if you’re thinking of direct contracting with physicians (which we’re very much in favor of at KBGH), ask the practitioners what they think of this philosophy. Is every patient an individual for whom a personalized solution must be hand-crafted for every problem? Or are they more interested in good systems, especially for common illnesses, screenings, transitions of care, and continuity of care? If their answer is the former, dig deeper before you commit.

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.

Congress Bans Surprise Bills (mostly)

On Super Bowl Sunday my son managed, in that mysterious preteen boy way, to break his leg while snow sledding. We went to the emergency department and received good, straightforward care. His leg was splinted and his pain was controlled in time for kickoff. He’s healing up nicely.

But now my family has a pendulum swinging over its head. Will we get a bill that is as straightforward as his care was, or will we get a set of “out-of-network” bills, even though the emergency department we went to was considered “in network” (we checked)?

This is no hypothetical threat. Hundreds of thousands of Americans get stuck with out-of-network bills from emergency departments, often for tens or even hundreds of thousands of dollars, because of a sinister business model being advanced by private equity firms. Those firms have twisted this quirk of American medicine, where a doctor working in an in-network hospital can be considered out of network, into a profitable business model in which they buy physician groups and intentionally move the providers out of network. It’s exasperating not only for its shadiness, but for the fact that the out of network doctors often charge rates far above what insurance companies are willing to pay. And it works: as many as one in five ER visits have surprise bills attached to them.

But late in 2020 Congress did something that seems like an obvious bipartisan win for everyone involved, but which was kept from happening for a depressingly long time by lobbying from those same private equity firms: they banned surprise medical billing. Some are calling it “Sarah Kliff’s Law,” after the former Vox, now New York Times, reporter who asked people to send her outrageous examples of this kind of behavior over the last few years.

The law requires insurers and medical providers who cannot agree on a payment to, instead of just mailing out outrageous bills destined to be sent to collection agencies, use an outside arbiter to settle on a fair fee. The fee is based mostly on typical payments for similar services. Then the patients can be charged the same cost-sharing they would have paid for in-network services, and no more. The most powerful effect of the law may be in avoiding arbitration altogether; the New York Times reported last winter that, in the dozen or so states that have set up their own arbitration systems like this prior to Sarah Kliff’s law, most price disputes get successfully negotiated before an arbitrator is even involved.

The law is not perfect. It doesn’t take effect until 2022. And while it will apply to doctors, hospitals, and air transport (which can generate particularly huge bills), it excludes ground ambulances even though a majority of ambulance rides nationwide generates an out-of-network bill. Sarah Kliff herself reported that the omission was due to lawmakers’ fear that untangling the complex local and federal regulations around ambulance services would have delayed or killed the entire bill. If you’re an optimist, you’ll predict that Congress will take up the ambulance issue separately in the future. If you’re a pessimist, you’ll predict that private equity firms will simply move their money away from ER physician groups and toward ambulance services.

Learn more about this kind of skullduggery and what you can do to fight it in the KBGH Book Club.

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.

How to Get Your Employees to Take Advantage of Price Transparency

In the KBGH Book Club we’ve gone through the “What’s wrong with this situation?” phase, and we’re just entering the “What can we do about this?” phase. A solution that is proposed again and again in this book and in the benefits world in general for controlling costs in medical care is price transparency.

In theory price transparency works like this: since most of the medical care that we receive is non-urgent, we should have time to compare prices. So if only the price of, say, an elective knee MRI at several locations was published on a website, we could simply compare the different radiology practices, choose the lowest price, and go to that practice for our MRI. There is some evidence to support that this works. My favorite study, which I wrote about in a previous blog post, showed that parents choosing a treatment for their child’s appendicitis still mostly chose the cheaper option when they were given cost information, even though it affected their insurance payment more than their out of pocket cost.

Because of this, and because of an Executive Order President Trump signed on October 29, 2020, CMS and the Departments of Labor and Treasury have issued a final rule that will, for the first time, require most private health insurance plans to do two things:

1. They will have to provide personalized cost-sharing information to patients.

2. They will have to publicly report negotiated prices for specific health care services through an online tool. The tool initially will be required to have the ability to compare rates and out-of-pocket expenses for 500 of the most common labs, visit codes, and procedures (deadline January 1, 2023). Starting January 1, 2024, these tools must report this cost information for all health care services. Legal challenges to these rules will undoubtedly continue (not everyone believes, as we do at KBGH, that transparency = trust). But barring a truly explosive set of judicial rulings, we can expect a great deal more price transparency moving forward than what we have now.

Unfortunately, as Jeffrey Kullgren and Mark Fendrick note in a recent editorial (paywall), transparency tools have not yet been shown to reduce overall spending, even when patients are paying pre-deductible prices, when they should be most sensitive to prices. Multiple phenomena may account for this. Patients may simply have too many choices (the old “too much jam” phenomenon). Some patients may assume that less expensive options are of lower quality. Patients may simply not know when more than one option is available. Kullgren and Fendrick make several suggestions on how to make the new price transparency rule work:

1. Make sure employees know that health care services are “shoppable.” We’ll all have to sell patients on the idea that the information is “trustworthy, reliable, and worth using,” as the authors say. This will mean working with our insurance partners to make sure those things are true. Relying simply on the fantasyland “chargemaster” prices for hospital services, for example, will undoubtedly make employees skeptical or cynical about the process.

2. Many employees will need guidance on how to best use the transparency information. A specific example given by Kullgren and Fendrick is direction on when prices could be most helpful. Planning a knee replacement in a few weeks or months, for example, is a good use of pricing information. Trying to price shop after a diagnosis of a potentially life-threatening cancer requiring urgent treatment, though, is clearly not a good practice, in spite of what my favorite parents-cheaping-out-on-their-sick-kids study above may say.

3. On the provider side, we need to continue moving away from fee-for-service reimbursement models and toward quality-driven, alternative payment models. Much of this movement is happening on the public side in Medicare and Medicaid. On the employer side, a move toward more direct contracting with providers could be a good way to accomplish this.

4. Employers need to work with professional societies (like the Medical Society of Sedgwick County, with whom KBGH is allied) to continue to advocate that cost containment is a core professional responsibility of modern medical providers. Integrating cost information into the medical record like the Veteran’s Administration does for drug pricing may be a good practice.

5. We need to pressure different health systems to adopt electronic health record interoperability standards so that, when patients use price information to seek services at alternate facilities, their care won’t be fragmented between doctors that can’t access the same information.

How do you propose we nudge our employees toward taking advantage of price transparency moving forward? We’d love to hear your ideas!

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.

Your data belongs to you, not to your claims administrator

At some point you have probably requested data from a claims administrator, like the fraction of your health care spending that is going toward mental health codes like depression, anxiety, or post-traumatic stress disorder, or a quality indicator for a certain hospital or health care system. It’s highly likely that the person or organization you communicated with told you they couldn’t  provide the data because doing so would have been a “HIPAA violation.” Huh?

The 1996 Health Insurance Portability and Accountability Act, colloquially known as “HIPAA” (hip-uh), was passed with two goals in mind: protection of “personal health information,” or PHI, and the ability to easily switch insurance policies from carrier to carrier to get better coverage, a better price, or additional services. HIPAA accomplished protection of PHI, but it did not, ironically, dramatically increase the portability of insurance coverage.

But that shortcoming of the law is a distraction. Here’s all you need to know about a claims administrator’s assertion that HIPAA prevents you from getting aggregate data on your employee population: It’s not true. If we didn’t already know this, KBGH Book Club attendees have recently learned it from Dave Chase’s The CEO’s Guide to Restoring the American Dream. In this week’s Section, II, “How and Why Employers are Getting Fleeced,” Dave says, “Sometimes [claims administrators] use HIPAA privacy as a smokescreen [to] prevent you from having your data analyzed by an outside party, an issue HIPAA effectively accommodates.” Since the law clearly allows you to access this data, if you’ve been blocked it was more likely that your claims administrator inserted a clause into your contract stating that claims data is proprietary and owned by them, the carrier, and not by your company, the purchaser. But HIPAA itself clearly allows this kind of data analysis: “HIPAA specifically allows transmission of aggregate data in order to promote high quality health care, and the HIPAA privacy rule specifically addresses aggregate data use for purposes of research, public health, or health care operations.”

But the good news for you, the purchaser, doesn’t stop there. The Consolidated Appropriations Act, signed on December 27, 2020, prohibits gag clauses on price and quality information and forbids plans and issuers from signing contracts that restrict the disclosure of provider-specific cost or quality information. And that’s not all! The Act also forbids plans and issuers from restricting access to deidentified claims or encounter information to HIPAA business associates like your company, including financial information, provider information, service codes, and “any other data element.”

This isn’t a full-throated defense of HIPAA. The KBGH book club is leading us down some interesting, unusual policy paths, and this law is probably worth a second look in the future. Whenever restrictions on regulations are lifted, as restrictions on telemedicine were in the early days of the COVID-19 pandemic and as HIPAA restrictions are being lifted in Texas now, owing to widespread power outages, it is natural to wonder why the restrictions were ever in place to begin with. If the practice can be jettisoned for now, why was it so important before? Can we still protect privacy, as HIPAA does, without the rule being so burdensome? That’s a topic for future discussion.

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.

Measuring Health Care Productivity

If you’re reading along in Dave Chase’s The CEO’s Guide to Restoring the American Dream with the KBGH book club, you know that in our upcoming discussion of Section II of the book the issue of “productivity” in health care becomes central. Dave says that “...health care hasn’t had a productivity gain in 20 years.” He cites a 2011 paper (paywall) from the New England Journal of Medicine, typically a very reliable source, that posits that output per worker, defined as volume of activity--”encounters, tests, treatments, and surgeries”--has not changed over time per unit of cost:

New England Journal of Medicine

 This assertion that health care is not gaining productivity seems counterintuitive. After all, we’ve had several huge advances in the science of medicine in the last 20 years, ranging from the adoption of findings of basic, bench research like mRNA vaccines and immunotherapies for cancer to the incorporation of social science research findings like team-based care and checklists. The trouble is that health care doesn’t fit neatly into our notion of productivity the way other industries might. Patients aren’t widgets to be cranked out on an assembly line or miles of pipe to be laid down or even billable hours for a consultancy. And all those “encounters, tests, treatments, and surgeries,” as we’ve discussed ad infinitum in this very blog, don’t necessarily lead to improved health. The authors of the NEJM paper concede that “it is possible that some gains in quality have been achieved that are not reflected in productivity gains.”

 This discrepancy led me down a rabbit hole that ultimately landed on a working paper published on the National Bureau of Economic Research’s website in September of 2020. Investigators applied a deceptively simple methodology to health care that might look familiar to many readers: they constructed a “satellite account” for medical care. Satellite accounts are a theoretical framework that allows focus on a specific field of economics or social life within the larger context of national accounts. Other examples might include studies of environment, tourism, or unpaid household work.

 And instead of using the providers of care as the “industry,” the investigators used the medical conditions themselves. “For example, there is an industry for heart disease and a second one for lung cancer,” the authors say. “Our accounts make no distinction based on the type of care provided; all that matters to people is how much they spend on care and their resulting health.”

That is to say, the primary “input” of the system was medical care, or all those “encounters, tests, treatments, and surgeries” that were considered the “output” of other studies. The “output” of the satellite account was simply health. They looked at 80 conditions in an elderly population between 1999 and 2012, roughly the same time period as Dave Chase’s 20 years of purported productivity stagnation in health care. And their findings conflicted with prior findings:

NBER

The figure above indicates that the most productive part of medical care, in spite of the heroic amounts of money we spend on it, was treatment for cardiovascular disease, which grew by nine percent. Cardiovascular care alone accounted for ~79% of the total increase in this new definition of health care productivity from 1999 to 2012. [Note: KBGH receives CDC funding for improved prevention, detection, and management of cardiovascular risk factors like diabetes, high blood pressure, and high blood cholesterol]

But in case you think I’m patting myself and the health care industry on the back, note that very little productivity was observed in mental health, and that we may have even regressed in productivity around infectious diseases (and all this nearly a decade before COVID-19!). Medical care, even under this new definition, did not compare positively to other industries; an overall increase in productivity of ~0.7% per year is hardly an inspiring number. But it is an increase nonetheless, and a more meaningful metric than simply the number of “encounters, tests, treatments, and surgeries.”

My purpose in writing this blog post isn’t to dazzle you with numbers, or even to convince you that American health care works well, since even a casual observer can see its dysfunction. My purpose, and one of the purposes of our book club, is to continue to encourage people to rethink their definition of what “good” health care is. Too many of us fall back on the fact that American health care is relatively fast, since we have more CT scanners and MRI machines than anywhere else in the world, and we ignore the fact that all those CT scanners don’t seem to lead to Americans living longer or having better lives. The real, meaningful output of our medical system should be health, not the number of procedures performed.

If you’re not part of our book club yet, it’s not too late!

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.

Introducing Advanced Primary Care

In the last couple of years, we’ve tried to drive home a couple key points about the routine medical care of your employees:

First, even though annual “check-ups” may not be that important, steady access to a primary care provider is essential. Access to primary care increases the life expectancy of a community. Primary care visits are declining, being crowded out by visits to retail clinics, urgent care centers, emergency rooms, and specialist visits.

Second, primary care is the most cost-effective form of health care, and to avoid unnecessary costs, most of your care should be coordinated through a primary care provider. American adults who have a primary care physician may have healthcare costs as much one-third lower than the costs of their peers who lack a PCP. Almost two-thirds of Medicare claims for wasteful or unnecessary care are by physicians with no relationship to the patient’s primary care practitioner.

But it’s possible that even with those assertions we’re thinking too small. KBGH is a member of the National Alliance of Healthcare Purchaser Coalitions (say that three times fast), and they have adopted the provocative stance that simple access to primary care isn’t enough. The Alliance has begun advocating for “Advanced Primary Care.”

If you’re a provider, you might cringe at the name. Isn’t the “advanced” part insulting to a seasoned, experienced, competent doctor who does “regular” primary care? Names are tricky. But the name isn’t meant to connote the achievement of a certain score on board exams or the possession of a special skill set. Instead, Advanced Primary Care, as defined by the National Alliance, describes a philosophy and commitment to seven key, sometimes overlapping, attributes in the clinic: 

1. Enhanced access. Many patients end up in the emergency department simply because they could not access their primary care practitioner during normal business hours or they got frustrated by the time it takes to schedule and complete a visit. Primary care practitioners who offer available appointments on nights or weekends can reduce emergency room utilization.

2. Increased time with patients. The average fee-for-service primary care physician carries a patient panel of roughly 2,200 patients. In models in which the physician or practice directly contracts with employers, this number may be more like 400-600 patients. This allows additional time with each patient to encourage better engagement, to better identify social determinants of health, and to relationship-build to ensure continuity of care over time.

3. Realigned payment methods. Much of the current fee-for-service model perversely incentivizes increased care or increased volume without increased quality of outcomes. Advanced primary care, which operates more frequently on a salaried or subscription model, seeks instead to incentivize patient activation, case and care coordination, accountability for health outcomes, and judicious use of downstream referrals.

4. Organizational and infrastructural “backbone” to support patient-centered leadership, additional training for staff when needed, and commitment to quality improvement over time. This may mean changes in the practice’s staffing and use of information technology.

5. Behavioral health integration in order to deliver “whole person health,” not just physical health. This can be in the form of a social worker, therapist, or psychologist on site or coordinated via telemedicine.

6. A disciplined focus on health improvement, not just reactive care, with a deep understanding of population risk factors and a strategy to focus resources within that population to where they will drive the greatest overall improvements. Advanced primary care seeks to anticipate problems like seasonal influenza, not just respond to crises that arise from those predictable problems.

7. A process of referral management to other providers or services, like specialist physicians, labs, radiology departments, and allied health, that explicitly seeks to maximize quality while moderating downstream cost.

The National Alliance has a good infographic on Advanced Primary Care below. If you’re interested in exploring direct contracting with primary care providers for your employee benefit package, please let us at KBGH know. We would love to help out.

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.