How Is This Medical Bill Possible?

How Is This Medical Bill Possible?

Two recent hospital admissions and the medical record dictation records events, visits, and documentation of physical examinations that did not occur.

Hospital stay 1 was for asthmatic bronchitis.  Thru the ED I was admitted to a FP, who consulted a Pulmonary doc.  The Pulmonary did H & P and all of the treatment and exams during stay, and did a great job.

The FP spent about 2 minutes total during the stay.  He did no exam ever, yet billed Medicare for multiple visits, exams and did discharge note, including physical that was never done.

Is this the new way if generating income by false documentation and upcoding?

 

Hospital stay #2 was admission for removal of benign meningioma.  Early morning admission, visit with surgeon about 2 hours after surgery and no further doc visits that day.  Medical record documents extensive note from critical care team, including physical exam of me that never occurred.

Day 2 was noteworthy for increasing headache from 6 level to 7, then 8, then 9.  Complaints of severe headache and severe nasal congestion finally discovered by my own research of side effects of Kepra, started without any discussion with me.  Multiple complaints to nurses 3 times finally resulted in doc visit after he went to lunch.  Significant change in Med’s and Ct scan resulted in decrease in pain after 4 to 5 hours.  I had demanded d/c of Kepra prior to this.  At about 1 PM there is documentation in medical record of another critical care team visit with NP and MD supervisor noting another non-existent physical exam stating patient in no distress.

On contact with hospital they continue to assert that the exams did occur as documented.

Contacted IG of Medicare with no response.

Multiple letters and phone calls to hospital.

Is this new and accepted practice to compensate for low reimbursement levels?  Anything further to do or am I beating my head against the wall?

It’s Time to Truly Share the Chemo Decision With Cancer Patients

It’s Time to Truly Share the Chemo Decision With Cancer Patients

You (or a loved one) has cancer, but the latest round of chemotherapy has unfortunately had only a modest impact. While you’re acutely aware of the “wretchedness of life that becomes worn to the nub by [ chemotherapy’s] adverse effects” you’re also a fighter.

How do you decide whether to continue with chemo?

The answer to that question is both intimately personal and inextricably tied to health policy. Cancer is the leading cause of death among those aged 60 to 79, and it is the second leading cause of death for all Americans. With expenditures on cancer care expected to top $158 billion (in 2010 dollars) by 2020, the financial and emotional stakes are both high.

How do you decide whether to continue with chemo?

The answer to that question is both intimately personal and inextricably tied to health policy. Cancer is the leading cause of death among those aged 60 to 79, and it is the second leading cause of death for all Americans. With expenditures on cancer care expected to top $158 billion (in 2010 dollars) by 2020, the financial and emotional stakes are both high.

 

Last July, the Centers for Medicare & Medicaid Services (CMS) launched a five-year program meant to change how oncology practices are paid for chemotherapy. Its goals were reducing unnecessary spending, improving care, and involving patients more closely in decisions. In a recent policy report from the Urban Institute, Shared Decisions in Cancer Care: Is Medicare providing a Model? Bob Berenson and I focused on that last goal.

We concluded that Medicare’s Oncology Care Model (OCM) falls short. Yes, it is “patient-centered” in that it includes a 13-point care plan recommended by the Institute of Medicine (IOM); that’s a big step forward. Yes, the OCM tries to reduce overly aggressive use of chemotherapy and underuse of hospice services among patients close to death.

Nonetheless, a formal shared decision-making process (SDM) remains vitally important. That’s clear from repeated IOM recommendations since 1999, as well as our review of the literature. What’s also clear, though, is that no powerful groups were lobbying for formal SDM, while, not surprisingly, provider resistance remained. As a result, despite nearly two decades of policy recommendations, the formal SDM required in OCM draft regulations in 2015 disappeared from the final regulations with barely a ripple of protest.

The omission is important, because the OCM is influential.  It involves more than 195 oncology practices nationwide, affecting an estimated 155,000 Medicare beneficiaries. In addition, 16 private health insurers, including Aetna, Cigna and Highmark, are patterning their own payment models after it.

The problem of overuse of chemotherapy in late-stage cancer is well known. In 2012, an American Institute of Clinical Oncology expert panel found, that chemotherapy use among patients for which there was no evidence of clinical value was the most widespread, wasteful and unnecessary practice in oncology. Yet important doctor-patient conversations about prognosis in advanced cancer didn’t take place or occurred late in the course of an illness with someone other than an oncologist.

Many patients receiving chemotherapy for end-stage cancers do not understand it is unlikely to be curative. (Or, I suspect, the financial incentives the OCM is intended to address for oncologists to keep on prescribing chemo anyway.) In a 2016 survey of cancer patients, one-third of respondents said they weren’t getting the information about treatment options they needed to make an informed decision.

A conversation about continuing chemotherapy is not only difficult emotionally; it also requires doctors to understand how the framing of a decision and the information that underlies it can bias the results. When SDM is done right, however, it can improve care quality, appropriateness, and value without creating anxiety or diminishing hope. It may also address social disparities, since black and Hispanic patients tend to receive less information from their doctors, about the reasons for treatment recommendations.

From the narrow view of value-based care as obtaining better outcomes at lower cost, there’s inadequate evidence to tout SDM as a cure for overtreatment. However, there’s an important distinction between moral values, such as patient autonomy and peace of mind, and solely economic ones.

We found more than enough evidence to support a Medicare and private payer test of shared decision-making test either in a subset of cancers or in a subset of OCM-participating practices. The alternative to SDM, we write, is a situation in which “judgment calls about the appropriateness of chemotherapy may still be dominated by physician judgment.”

Formal SDM is doable today. As we conclude:

A large body of research indicates that many of the 1.7 million Americans diagnosed with Cancer today would greatly value more information-rich conversations with their doctors. Whether or not that desire for greater control over life-and-death decisions saves money for third-party payers, the implementation of shared decision-making shouldn’t require a moonshot-level effort.

Electronic Medical Records 2017: Science Ignored, Opportunity Lost

Electronic Medical Records 2017: Science Ignored, Opportunity Lost

My big brother Bill, may he rest in peace, taught me a valuable lesson four decades ago. We were gearing up for an extended Alaskan wilderness trip and were having trouble with a piece of equipment. When we finally rigged up a solution, I said “that was harder than it should have been” and he quipped in his wry monotone delivery, “There are no hard jobs, only the wrong tools.”

That lesson has stuck in my mind all these years because, as simple as it seems, it carries a large truth. It rings of Archimedes when he was speaking about the simple tool known as the lever: “Give me but one firm spot on which to stand, and I will move the earth.”

Enter the Electronic Medical or Health Record (EMR or EHR) as it exists in most forms today. As information tools for clinicians, most EMRs have been purchased by administrators who know nothing of patient care or workflow, and most of these EMRs have been reverse engineered from billing and collection systems, because the dollar drives all.

 

Truly value-driven care is blocked by these misguided tools. Multiple studies have demonstrated that using the EMR adds hours to our workday without corresponding benefit. This only pushes costs up and quality down. In fact, story after story tells of doctors retiring early or changing professional direction to escape the frustrating click, click, click all day long. Compounding this is the federal government mandating meaningless use criteria that say we will not get paid unless we use these programs and meet certain click-box ratios. You do not need “Validated Studies” to understand this. You just need to talk to doctors around the country. I challenge you to talk to ten practitioners at random who are involved in day-to-day emergency medicine or primary care medicine, the guys and gals on the busy front line, and find two of them who are enamored with their EMR tools.

On any given day in my primary care practice I can show you an eight to twelve page fax from the hospital that spews pages of prattle and lab data, informs me that the patient is not Hispanic and has no religious preference, yet I cannot find the diagnosis or the plan. As if that is not bad enough, these documents meet the requirement for Meaningful Use since they hit enough click-boxes. So, what has happened, and how are we going to fix it?

Since these systems were designed around billing and collections, they were never designed to help the work flow of diagnosis and management. They are, in fact, little more than dysfunctional databases that record what the doctor typed or dictated after the fact without organizing these fragments in a clinically useful manner. And sometimes not even the recording function gets done. Two documents I received last week had twelve and ten pages of printout, yet the last page, labeled “Doctor’s Summary”, was blank. Another one from three weeks ago, labeled ‘Preoperative Note’, had a single sentence “The risks and benefits of surgery were thoroughly discussed with the patient.” That was an H&P? Yet another point-and-click generated History and Physical proclaimed that a 12-point Review of Systems was performed and found to be negative (qualifying the visit for up-coding) and that the male patient had no vaginal irritation, stress urinary incontinence, or post-menopausal bleeding. And yesterday I received an operative report dictated March 24, 2017 on an operation done in December. (Honestly, I am not making this up!) Given that these tools record whatever the provider chooses to record, they can only be as accurate or inaccurate, as methodical or sloppy, as timely or late, as the mind that generated them. In short, they are not scientific tools aimed at improving diagnosis and management.

Consider a trio of astronauts climbing into the cockpit of a craft sitting on a million pounds of fuel about to blast them into the cosmos. Can you imagine them being asked to guide the craft into space, around the moon, and back to a precise landing spot, and told they had an accounting spreadsheet that was reverse engineered to run their console and their guidance system? How preposterous does that sound? But the difference is that doctors do not get into the cockpit with the patient. Those astronauts have a vested interest in their system working well. Doctors just put in their shift and grumble all the way home about how ridiculous the system has become.

I am an instrument-rated pilot with approximately 2,000 hours of flight time. I’m still alive to talk about it for one simple reason. Pilots have very precise and rigorous training requirements that we must complete every six months, or else we cannot fly in instrument conditions, which essentially means rain, fog and clouds. And we have a vested interest in that training.

It allows us to bring our craft into the airport environment on a precise heading and angle of descent that sets us up for landing when we break out of the mist and see the runway perfectly lined up with our flight path. In contrast, doctors can get a degree and never pick up a book again for years, but can legally go on treating patients based on memorized remnants from 1977. Most doctors try to do better, but must manage without proper tools or guidance systems. They tolerate this situation because they don’t have to get into the cockpit with the patient. And when that plane crashes, they still get paid and go home to their families.

So, what are we to do? To move ahead, I submit that we need to go back and start over.

The Problem Oriented Medical Record

Beginning in the late 1950s, Dr. Larry Weed saw the futility of traditional medical record tools and set out to address it. He began by conceiving a standard of care for organizing medical record data in a clinically rational manner. Known as the Problem-Oriented Medical Record (POMR), this standard established problem lists and SOAP notes, among other elements. But in the late 1970s and early 1980s, he concluded that the POMR, computerized or not, was an incomplete tool. The POMR organized clinician inputs but left the content of those inputs to the physician’s unaided mind. So he devised a system that mandated precise inputs of basic, inexpensive, raw patient data, and coupled those data with corresponding medical knowledge, before the doctor’s mental machinery was allowed to act.

Number Needed to Kill = One

We know from decades of research that humans start developing hypotheses almost immediately when inputs start. Unfortunately, the wrong hypothesis can and will make us branch off into the wrong algorithm much too quickly. (Chest pain radiating down the left arm and up into the neck associated with an abnormal ECG must be coronary occlusion, therefore act quickly and give blood thinners. Number Needed To Treat = 43. Except that you forgot to consider his dissecting aortic aneurysm. Number Needed To Kill = One.)

The Problem Knowledge Coupler

Dr. Weed’s answer was the “Problem Knowledge Coupler,” a new tool that could use computational power to cross-match signs, symptoms, physical exam findings and inexpensive lab data with the current knowledge in the medical literature about a given problem. It is critically important here to understand that patients do not present with diagnoses, they present with problems. Nor do they present with simple conditions with a single treatment option. They present with complex permutations of undiagnosed symptoms requiring individual analysis.

Point and Click Diagnosis

Many of the current click-point programs set up a progress note labeled by a diagnosis when the patient presents. An example is the “Upper Respiratory Infection” note that the nurse will start when she rooms the patient with a cough. Questions about an upper respiratory infection will be asked, heart and lungs and ENT exam findings clicked in, and then the provider will diagnose either a viral or a bacterial URI and maybe prescribe an antibiotic. However, the early lung tumor will not be diagnosed because the ‘diagnosis’ of URI was actually used as the presenting finding instead of the ‘problem’ the patient actually presented with, which was cough.

This is a matter of scientific integrity. I was trained as a chemist. Imagine that I had “data” consisting of hypothesized results rather than observed findings, and tried to publish a paper based on my supposed results. I would not get far, but something like this happens in medicine routinely whenever a physician confuses a diagnostic hypothesis with an observed problem, and then gets his usual reimbursement for his opinion and treatment plan. Not only is the patient at greater risk, but the medical record is corrupted as a vehicle for quality improvement, economic accountability, and scientific research.

Problem Knowledge Couplers do not let the unaided human mind jump to conclusions. They methodically gather the basic history and physical findings, then allow for any lab data that might be available, and only then “couple” the unique findings of that particular patient with the known information in the medical literature to give a complete differential diagnosis for that particular patient at that particular point in time. A printout can then be provided to the patient or family so that they can watch for evolving signs or symptoms that may help further delineate their evolving condition. The unaided human mind cannot do that. Studies have shown that we break down when the grid exceeds 5 or 6 findings relating to 5 or 6 diagnostic possibilities. But Dr. Weed knew that computers excel at just that type of combinatorial analysis, while humans excel at other tasks in the process.

In 1983, I was working on my first attempt at writing a novel, and I had just bought my first IBM PC with a 5.25 floppy that could hold an incredible 64K of data; several chapters on one little disk versus a stack of 64 pages of typewriter paper. I marveled at the power. But in 1983 very few people had personal computers, and in fact very few small businesses had them. At the same time I realized how little I knew of the vast store of knowledge that was out there, and I was looking for a computer program that could help me think clearly about what I was seeing in my patients. To my dismay, every article I hungrily read about “Computers In Medicine” turned out to be billing programs. They had nothing to do with medicine. They were business programs.

Then I met Dr. Larry Weed at a meeting in Minneapolis in 1985. He gave the most memorable presentation, saying out loud what I had been thinking for years. He was developing Couplers and had 12 completed at that time, but he was also developing a computerized medical record that was problem oriented, so the history and analysis of the progress of a given problem was identifiable and organized chronologically. We decided to work together, and over the next 7 years I became the Beta Test Site for the Couplers and POMR tools. Living in a town of 800, on call 24/7 for years on end, and integrating a Beta program into a busy practice was both exhilarating and exhausting. But it did show us what was possible. (For a detailed description, see my chapter, “The Perspective of a Practitioner,” in Larry Weed’s 1991 book, Knowledge Coupling: New Premises and New Tools for Medical Care and Education. For a comprehensive discussion, see Dr. Weed’s 2011 book, Medicine in Denial. That book’s table of contents, overview and introduction, including a diagram of the system components and feedback loops envisioned by Dr. Weed, are available here.)

One example comes to mind. I was in Canada with my Explorer Scout Troop teaching them outdoor survival skills, and I had a locum tenens physician filling in in Faulkton, S.D., for me. When I returned, my typist, Zelda Gebhard, brought a chart to me and thought I should review it. The elderly gentleman in question had anemia and weakness, and her question was why had the doctor not done a stool hemoccult on him? The trail was there to see because the system spelled it out, and she was so accustomed to our methodical approach. Yet the doctor had placed him on iron and let it go at that. Sure enough, the hemoccult was positive and the cecal cancer was removed a week later.

Now, it is easy enough to say, “The doctor should have known better,” and cast the blame on him. But that would be missing a huge point. This type of short shrift of patient’s problems happens every day in every city of every state. There is only one person who has a 100% vested interest in the patient’s total picture: the patient. I ask you: if a typist with a secretarial degree can arrive at a correct diagnosis with a good roadmap, why are not the doctors using those roadmaps? And the answer would be that they have spent 10 to 15 years memorizing the roadmap and are being paid large salaries to tell people how to navigate within the healthcare system.

Like Google Maps For Medicine

If you wanted to go from Minneapolis to Miami, how many of you would hire a Ph.D. in geography to go along with you and pay him $100 an hour for his advice? Of course it is a ridiculous question. You learned how to read a map in grade school, we have professional mapmakers who keep our maps up to date, and you drive yourself to Miami. And now we have electronic maps that make them all the more powerful. Yet, where is the map system in medicine? It is collated in thousands of books and resides in the memory banks of thousands of professionals who rely on the unaided human mind to ask you the few questions they have time for and arrive at your diagnosis or treatment decision. With a library of couplers, a personal computer, and an Internet connection, patients could analyze their own problems and go to the doctor for the physical exam and tests that are then indicated. And with a well thought out medical record, the physician and patient together could track progress and treatment success.

State of Interdigitation

What we have instead is hundreds of companies selling million dollar programs that are driving us mad with their helter skelter approaches and unfulfilled promises. We were promised that the program would cut down our medical record overhead by fifty thousand dollars a year, but we were not told that it would require a NEW department of IT people that would cost us twice that. We started with one computer specialist and now have 5 in our clinic alone. Adding insult to injury, we have a government that mandates using computers in a “meaningful” way because computers are supposedly proven to make things more efficient. This is like the government mandating that shippers use rail lines to move their products because they haul more cargo per gallon of fuel than trucks, yet allowing each state to have their own rail line with different gauges for their wheelbase. Forty-eight different rail lines that cannot interdigitate with one another would cause chaos in the shipping industry, but we experience that every day in medicine. And that is only the recording side of the medical record. What about the front end, when the patient arrives at our door with a new problem? Without scientific inputs, we cannot get scientific throughputs. Where is the roadmap for that chaos?

Where Are Our HIT Leaders?

Where are the leaders on the national level? Nearly thirty years ago Dr. Weed and I were asked to critique a national white paper on the EMR put out by the Institute Of Medicine and published in 1991. They did not take our advice. No one mandated that vendors use the same language or the same format because that would not allow “free enterprise.” What has happened in medicine is what would have happened in shipping if the government had not mandated that the railroads use the same wheel gauge. Nothing is getting fixed, yet all the buzz these days is about “Physician Burnout” exceeding 50% because every hour of clinical work requires 2 hours of clerical work.

Until we have a system that works, nothing is going to change. An Institute of Medicine report in 1999, “To Err Is Human”, claimed that 98,000 deaths per year were attributable to medical error. That is 1,885 deaths per week, or the equivalent of a 737 crashing every day, yet nothing gets done. Of course there is physician burnout. But what about patient burnout? They are the ones who are suffering the most. They are the ones who are complaining that the doctor has his face in the computer instead of on them.

Meaningful Use vs Meaningless Chaos

After 40 years of practice I jokingly threaten to quit my current practice, go to the mall, open a consulting office, get a pen and paper, and TALK to any patient who is willing to forego insurance papers, co-pays, massive overhead structures, and pay a 20 dollar bill for a quick consult and a roadmap of where to go next. But it is no joking matter. The system is broken and billions of dollars are being wasted on a system that doesn’t work. Why does a GP from a small town have to be the one to complain? Where are the professors from the leading institutions demanding – nay, developing – a fix? Where is a library of couplers that patients can access to help work out their problems to see if it is something that even requires testing? Where is a medical recording system that has the same “wheel gauge” across the country so that my patient with Lupus can go to the Mayo Clinic and have their record accessible and cumulative? Only then can we have “Meaningful Use” instead of the meaningless chaos we now suffer.

Daily we practitioners put together a chain of history and physical and laboratory evidence that we then try to steer into meaningful scientific conclusions, but we have the wrong tools for the job. We are pushing that chain from behind instead of pulling it from the front. Until we have the proper tools, and with no firm spot on which to stand, I guess we just have to push harder.

Not Really Insurance: The Pre-Existing Condition Debate

Not Really Insurance: The Pre-Existing Condition Debate

The recent debate over the potential repeal and replacement of the ACA, with the current focus on coverage for preexisting conditions, has drawn a great deal of attention to the concept of health insurance.  While our political leaders are constantly talking about it, few of them seem to understand the “insurance” component of health insurance. As a result, much of what they say about preexisting condition coverage is gibberish. We are here to set the record straight.

At its most basic level, insurance provides protection against the risk of unexpected financial losses. We focus on the term risk because if we were risk neutral (i.e., we were indifferent between sure things and actuarially equivalent gambles), then we would not value this protection. But nearly all of us are risk averse, meaning that we would rather not face having to dramatically reduce consumption of everything we enjoy in the event we are hit with an astronomical medical bill.  Because we are risk averse, health insurance improves our collective well-being by helping us collectively smooth our consumption.  Everyone who purchases insurance consumes somewhat less of everything else when healthy, but does not have to consume dramatically less when sick.

 

Turning to preexisting conditions, consider a person who is currently uninsured but has recently been diagnosed with a serious medical problem.  Given the opportunity, this person would love to purchase a health insurance policy.  But make no mistake about it, this policy is no longer insurance in any traditional sense of the term.  By skipping out on paying premiums until the illness strikes, this individual has consumed a lot more than everyone else when healthy, yet is able to consume almost the same as everyone else when sick (almost because there is likely to be some cost sharing).  This isn’t consumption smoothing, it is free riding, and this is what the prohibition on considering preexisting conditions encourages.

(To be fair, some individuals may lack the means to purchase insurance at any price, even with ACA subsidies, and it is excessively harsh to describe them as free riders.  We will return to these cash-constrained individuals at the end of this blog.)

There are two problems with free riders.  First, someone has to bear the cost – that someone is the “responsible” (although some might say “foolish”) individual who purchased insurance all along.  Second, because free riding drives up the price of insurance for everyone, some responsible individuals refrain from buying insurance in the first place, potentially even leading to a death spiral.

To help make things clear, we have constructed a simple numerical example.  Suppose there are 100 people who each have a 20 percent chance of incurring a $50,000 medical bill at some point in the next five years.  If everyone purchases insurance, premiums would be $10,000 each year.  But suppose that only 70 people buy insurance every year, while 30 people free ride, purchasing insurance only at the time they require medical care. In expectation, 20 people will be sick each year, 14 “responsible” individuals and 6 free riders. With an annual insurance pool of 76 enrollees (the 70 responsible ones and the 6 free riders), the insurer would have to charge a premium of $13,158.   This is quite a good deal for the free rider, who otherwise would have had to come up with $50,000 (or paid over $13,000 in premiums each year).

This table summarizes the conclusions:

 

If insurers could discriminate based on preexisting conditions, they certainly would not issue a policy to someone requiring $50,000 of medical care for any less than $50,000 in premiums.  But prohibited from discriminating, insurers must “over-charge” responsible customers in each year to make up for the shortfall of having to cover the free riders.  The amount of the overcharge is not small, and the increased premiums may well scare additional people out of the market.

It is remarkable to us that seemingly the only feature of the ACA with broad appeal is the provision that bans insurers from considering health status when offering and pricing insurance plans.  The purported purpose of this ban is to assure that all individuals have access to insurance, but that clearly is not the true effect.  Instead, the effect is to encourage free riding while punishing those who do the “responsible” thing.  It is for this reason that the ACA contains both a mandate (which given its size is of dubious effectiveness) and pre-specific annual periods of open enrollment (i.e. you can only purchase insurance, barring extraordinary circumstances, during a pre-specified time of the year). These are the provisions that are under attack, yet these are what make the ban on preexisting condition exclusions almost sensible.  Our politicians have it ass backwards. If anything, we should be increasing the cost of the mandate to discourage free-riding.

One possible solution to the free-riding problem would be to not provide coverage to those who game the system and/or gamble on their health status.  However, there is a reasonable argument made that as a society we do not want anyone to face high medical bills, and potentially even medical bankruptcy, even if they knowingly chose to free ride. This sentiment certainly underlies existing arguments that even those who have been diagnosed with cancer or who are currently pregnant should be allowed to purchase “insurance” in the marketplaces.  Is there a national consensus about this?  We are not sure.  Should there be a two-tiered system, so that those who knowingly free ride are forced to obtain care at “lower quality” providers (perhaps some county hospitals fit the bill)?  We are not sure of this either.  Is anyone asking these hard questions besides us?  We are sure they are not.

The remaining question then is how we fund the redistribution system that we have created. In the terms of the simple numerical example above, we fund the $50,000 in medical expenditures for the free-rider by charging higher premiums to the responsible customers that purchase insurance when they are healthy.  This is similar to what happens in the ACA.  These higher premiums are paid for through two primary mechanisms. For the subsidized portion of the marketplace, the increased premiums are paid via general tax revenue. However, the unsubsidized portion of the market (those earning more than 400 percent of the poverty line) are forced to pay for both the portion of the premium that relates to their risk of medical expenditures as well as pay what is effectively a tax to support individuals who chose not to purchase insurance until they were sick.

This is terribly unfair.  The ACA marketplace is a small sliver of the total insurance market and as a result we are asking quite a bit of the higher income marketplace enrollees (who are not necessarily high income in the broader population). In the process, we are driving the healthiest of these individuals out of the marketplace. They either will seek employer based options or go without insurance. And why wouldn’t they leave?  They have the ability to eventually enter the market if they get sick.  Note that these healthy and higher income enrollees are the very people who have failed to show up to the ACA marketplaces in the numbers that we expected.  Given the discussion above, this should perhaps not be surprising.  We are placing a fairly high premium tax on those individuals.

Having hopefully convinced you that funding the redistributive portion of the ACA via premiums is distortionary and inefficient, we next turn to possible solutions. Like many things in healthcare, while the problem here is clear that answers are far less so. One potential solution is to create a series of heavily subsidized insurance pools for individuals who have known high medical expenditures and have chosen to previously forgo the purchase of insurance.  These are often referred to as “high risk” pools, which is itself a bit of a misnomer.  There is no risk here; these are high cost pools where we know individuals will have high medical expenditures. An advantage of such a strategy is that funding these pools via general tax revenue instead of premiums wouldn’t distort the insurance decisions of healthy high income exchange enrollees. However, putting individuals into a high risk pool doesn’t decrease their medical expenditures and therefore these pools have to be heavily subsidized. The sheer size of these subsidies is often daunting and faces political opposition. Underfunded high risk pools are certainly not a good solution – and for this reason ACA supporters are often unimpressed by this as a solution to rising premiums.

Another solution is simply to reinsure firms that offer insurance from the federal marketplace. Effectively, for expenditures over a certain threshold the federal government could agree to compensate insurers. In some ways this is the idea behind the “invisible high risk pools” that have been recently debated. Again, reinsurance involves observable transfer payments to private firms – something that while potentially efficient has drawn political ire (remember the billions in risk corridor payments the government didn’t ultimately pay insurers). This seems to have little support from the public, who view this as a subsidy to insurers (though only to make sure they don’t lose money), rather than a way to stop taxing responsible exchange enrollees.

We would note for the purposes of completeness that another (perhaps less equitable) option would be one we discussed earlier.  Allow everyone a few years to buy their way into the insurance market regardless of their current health status, and then reintroduce medical underwriting. People who choose not to participate in this market would then be allowed to receive medical care at county hospitals which would receive increased funds to cover the costs of these individuals. These funds could come from general tax dollars. We note that this to a first approximation, this system is not that meaningfully different from the current standard.

As a final note, if we want to have serious conversations about the role of preexisting conditions and the choice to purchase insurance we need to make sure that individuals are not liquidity constrained from buying coverage in the first place. For example, individuals earning less than 100 percent of the poverty line and living in the 19 states which did not expand Medicaid are effectively locked out of the insurance market because of their lack of resources. We shouldn’t see this as an expression of their preference to be uninsured or evidence of free riding.

While we both have over time been critical of various features of the ACA, one feature we have consistently praised is the creation of a viable non-employer based option for individual insurance.  The first three years of the ACA have shown that the marketplaces have failed to live up to these expectations.  Insurers have consistently claimed that individuals are gaming the system in a manner that is similar to the numerical example that we discuss above.  The resulting higher premiums are likely a driving force in the inability of these markets to attract higher income and healthy enrollees – who are necessary for a well-functioning insurance market.  For this reason, we would call on policymakers to carefully consider changes to the ACA that would improve the redistributive portions of the law.

David Dranove and Craig Garthwaite are economists at the Kellog School of Management at Northwestern University.