Nextera’s Next Era in Cherry-Picking Machine Design

Note: revised and redated for proximity to related material. Original version June 27, 2020.

In June of 2020, Nextera HealthCare had a hot new brag:

These results were not risk adjusted. But they desperately needed to be.

The St Vrain Valley School District had this health benefit structure for its employees during the period studied:

The school district’s 10% coinsurance rate for the PPO predates the arrival of the Nextera option. The school district also has a Kaiser Permanente plan that includes 10% coinsurance. The school district created the unique 20% coinsurance rate for Nextera DPC patients to help fund the added primary care investment involved. Here’s how that benefit structure impacts employees expecting various levels of usage in an coming year.

As the image above shows, Nexera reported $5,000 per year is as an average utilization level for an employee member of the district; an employee expecting $5000 in utilization can gain over $900 dollars by rejecting Nextera. Every penny of that advantage for the employee comes out of the employer’s hide — and then it shows up in Nextera’s table as a Nextera win. A employee with moderately heavy utilization – but still only about twice the average and still far short of her mOOP— might even hit the jackpot of shifting $1787 from her pocket to the employer, simply by rejecting Nextera. Heavier utilizers, those who surpass their maximum out of pocket – will all gain at least $750 by rejecting Nextera.

This benefit design pushes a large swath of risky, costly patients away from Nextera.

But that tells only part of the story. As if pushing unhealthy patients away by increasing cost-sharing does not do quite enough to steer low risk patients to Nextera, a difference between employee share of premiums specifically drives children into the Nextera cohort. A Nextera employee pays $1600 less per year to add coverage for her children than she would pay to have the same kids covered in the non-Nextera plan. About 24% Nextera population is under 15 years old, versus about 13% for the other group. On the other hand, those 65 and up are four times more likely to reject Nextera. The overall Nextera population is about 6.5 years younger on average as a result.

And notice that even after Nextera starts with a younger, healthier pool, those who elected Nextera will face vastly more cost-sharing discipline under their benefit plan than their PPO counterparts. They can be expected, in aggregate, to consume less. This is known as induced utilization. Per the Milliman team, this should be considered by those evaluating the impacts of DPC.

If the employer’s claims costs are adjusted for both (a) the youth and health risk difference between Nextera and non-Nextera populations, and (b) the confounding effect of induced utilization, Nextera’s cost savings brag will likely be shredded.

Indeed, we have good reason — from the recent Milliman study and from Nextera’s own previous study of the exact same clinic — to suspect that a population risk-adjustment of more than a third is quite likely. Adjust the Nextera brag by that third and the savings will not simply vanish, they will turn into increased costs.

In this regard, moreover, a 2016 Society of Actuaries commissioned report, explained that all the available risk adjustment models failed to completely compensate for adverse selection. Ironically, their selection of a “highly adverse” population for evaluating the performance of the major risk adjustment methodologies was one with a claims cost history that was 21% higher than the average. In Nextera’s earlier self-study of the same clinic, the prior claims cost history of the non-Nextera cohort was an astronomically adverse 43% higher than the Nextera cohort.


Update: October 22, 2020. So now Nextera has published an extended account of its SVVSD program. It’s here here.

(It was “there” before Nextera sent down the rabbit hole it’s claim that a Johns Hopkins research team had done the cherry-picking analysis; that claim persists in this slide.)

A video version, here.

I reply here , here , here and here.

Medi-Share gives its Christian take on DPC downstream cost savings: $31 — a year.

Christian Care Ministry (“Medi-Share”), whose 400,000 members account for more than a quarter of health cost sharing members nationally, recently acted to allow some of its members to receive credit for their entire direct primary care membership fees up to $1800 per year.

That there is a certain synergy between DPC and health cost sharing plans is testified to in countless instances of mutually interested cross-promotion. But in the end, these are separate economic entities with their own bottom line financial needs.

Precisely because direct primary care entities refuse to work with actual insurers, we do not have much data from insurance companies from which we glean what their actuaries think DPC might be worth.** But a multi-billion dollar, 400k member cost-sharing entity, even if “non-insurance”, needs actuarially skilled professionals to make ends meet. So, when a major cost-sharing ministry rewards direct primary care members with a financial incentive, that may tell us what insurance companies will not.

Tell us what you really think, Medi-Share!

Only one of Christian Care Ministry’s options offers DPC benefits. That plan comes with a $12,000 annual Annual Household Portion (“AHP” is ministry-speak for “deductible”), but it allows its members to apply the full amount of their direct primary care fees toward that AHP. That could be as valuable as lowering an annual deductible from $12,000 to $10,200.

And we can easily estimate the actuarial value of that reduction. Here’s a screen shot from the Colorado ACA plan finder for 2020 for the premiums paid by a 38 year old Coloradan for two Anthem plans that differ only by $2150 in deductible. It costs $2.62 a month to reduce an annual deductible from $8150 to $6000. Necessarily, a reduction of $1800 a year cost less. As well, a reduction of any amount of deductible downward from a higher starting point will have a lesser value than that same amount from a lower starting point, i.e. , Medishare’s $1800 reduction downward from its $12,000 AHB is actuarially worth less than an $1800 reduction down from Anthem’s $8,150.

So there it is. $31 a year.


Wow. In a DPC with a $90 a month fee you’ll be spending twice as much on primary care as the average person using fee for service, but your downstream care savings are estimated by Medishare to be worth a whopping $3 a month on downstream care. It’s like getting one $1500 ED visit for free — every forty years or so.


** On the other hand, we do have the word of the former CEO of the now-defunct Qliance DPC to the effect that, for some presumably nefarious reason, insurance companies were not appropriately responsive to Qliance studies that claimed 20% overall cost savings.

HSA breaks for DPC defeat the purpose of HSA breaks

HSAs are intended to encourage more cost-conscious spending by placing more of the health care financing burden on out-of-pocket spending by the users of services, as opposed to having the costs of those services incorporated in payments shared over a wider group of plan enrollees regardless of service use. H/T Blumberg and Cope. HSAs are a legislative response to a problem in health care economics that occurs when “consumer demand for health care responds to the reduced marginal cost of care to the individual”. As clarified by Mark Pauly in 1968: when the cost of the individual’s excess usage is spread over all payer-members of a group, the individual is not prompted to restrain her usage.

In direct primary care subscription medicine, there is a marginal cost of zero for every medical service the individual consumes. All demanded units of DPC covered medical services are paid by monthly fees collected from each member, regardless of that members service use.

That’s precisely opposite to the reason for HSAs.

The HSA tax break exists to get patient-consumers to commit to putting more “skin in the game” through a specified, high level of deductible; the legislative designers forbade participants from “taking skin out of the game”, i.e., from defeating the legislative purpose by taking a second “health plan” that reduces that commitment and the effective burden of that deductible. This is why it is perfectly clear that secondary coverage (e.g., as a dependent on a spouses plan) is HSA-disqualifying.

The undefined words “health plan that is not a high-deductible health plan” in the HSA legislation should be interpreted to include any health payment arrangement, including direct primary care, that lowers the burden of high deductibles and defeats the purpose of the legislation. IRS’s interpretive discretion does not extend to undermining the intent of HSA legislation.

DPC advocates’ brag about how “there’s never a deductible”, no matter how many covered primary care services a patient actually utilizes. That’s exactly why paying DPC fees is incompatible with the reason for HSAs.


A benefits attorney retained by some DPC clinics has opined that the IRS should allow DPC subscribers to use HSA because DPC “complements” high deductible insurance. But Congress obviously intended a very specific health care payment model for complementing the coverage provided by high deductible insurance coverage — high deductibles!

DPC from 30,000 feet, on September 2020

  • Even with all the overhead reductions that come from not taking third party payment and/or from not billing on a fee for service basis
  • Even with those reductions transformed to increased primary care access that results in clear reductions on ED visits and other urgent care needs
  • Still, Direct Primary Care with panels of 600 patients per PCP, priced at $75/adult/$40/kid per month, does not financially outperform traditional, third-party paid, fee-for-service based primary care. (Search “Milliman” in this blog.) (Maybe 2-3%. Search “Anderson” in this blog.)
  • That $75/$40 is what it takes for a 600 patient panel to support a single PCP at average family physician compensation.

In other words, the DPC model has not miraculously enabled PCPs to “punch above weight” overall. Subscriptions for 38 minute visits, loosely scheduled to allow same day visits, and facilitate 24/7 access end up costing about as much as the existing FFS alternatives.

Perhaps, the whole DPC package makes the patient healthier in some way that does not show up as a financial savings. This is unproven. But DPC docs have not been content with one unproven overall claim. From its beginning, DPC has insisted on two unproven claims: better overall health and lower overall costs. The most clear recent emphasis has been on lower cost. The most clear recent evidence has been to the contrary.

So now they just fake it.

Helping those patients most dependent on DPC means defeating the DPC/HDHP/HSA “fix”.

Plus, two more reasons to reject the “fix”.

Direct Primary care clinicians and advocates often point out, accurately, that they serve a broad socio-economic range of patients. The range is well illustrated by a pair of oft-appearing themes, “concierge care for the middle class” and “affordable care for those who fall between the cracks”. In turn, the themes are reflected in two almost polar opposite insurance profiles for each of which DPC presents a solution: those in the middle class with sound, high-deductible insurance policies and those with low incomes for whom standard health insurance of any form is beyond their limited means.

The uninsured are not a tiny sliver of DPC subscribers. A recent survey put their numbers at about a quarter of DPC patients, and many DPC docs say 30-40% in their own practice. Indeed, a January NPR piece on the use of DPC by HDHP holders immediately prompted the DPC Alliance to vigorously advise the public that the economically disadvantaged are the “focus” of quite a few direct primary care practices.

The middle class HDHP group predominantly join DPC for mixed reasons of economy and concierge-like convenience, making a relatively good situation even better. Many of them — surely those with the most discretionary spending ability — are able to save. The low income uninsured on the other hand, enter DPC subscriptions to make the best of a bad situation, and they have essentially nothing to bank.

The Primary Care Enhancement Act and similar initiatives seek to provide substantial tax subsidies for direct primary care subscription fees, but these flow only to those who have BOTH high deductible health insurance plans AND enough spare income to facilitate actual savings accounts. But this kind of “fix” does less than nothing to those on the other side of the income/insurance divide; for them, the “fix” actually makes things worse.

Economics 101 teaches that government subsidies increase the price of the subsidized goods or services. The middle-class DPC members with insurance may, or may not, see net benefit from a subsidy; since the supply of family physicians is tight, most of the subsidy will probably flow to the providers as increased subscription fees. In any case, what low income DPC members will get from a “fix” is higher subscription fees.

Already priced out of standard insurance and forced into direct primary care, they will be pressed even harder. And some will find themselves forced out of direct primary care.

Subsidies for middle class savers (and/or their DPC physicians) may or may not be warranted by the purported virtues of direct primary care. But subsidies that are directed toward DPC’s financially soundest subscribers should not come at the cost of pushing DPC’s most financially desperate and loyal patients out of their best chance of quality care. Almost any other way of investing federal resources in DPC would be more fair and better targeted.

Do no harm.


But wait, there’s more.


Bonus # 1: The DPC/HDHP/HSA fix aggravates an income inequity among the insured population that is already baked into the DPC cake.

The signal feature of the DPC world is that direct primary care clinics do not take insurance, so entry is overwhelmingly on a cash only basis. DPC is effectively unavailable to anyone who is insured but does not have the financial resources to buy an additional layer of primary care services that neither draws insurance reimbursment not get credited against a deductible. By the same considerations, DPC becomes increasingly available as the income ladder is ascended.

When that socioeconomic reality is coupled to DPC emphasis on small patient panels and easy access, the resemblance of DPC to concierge medicine undercuts any argument for relaxing HSA rules on DPC. In fact, the HSA break amounts to a regressive subsidy that supplements funds being spent on DPC; this has the effect of growing the rate at which DPC becomes increasingly available as the income ladder is ascended. An HSA break brings DPC closer to concierge care.


Bonus # 2: the DPC/HSA fix aggravates the rural health care provider shortage

DPC advocate claims of being all things to all men sometimes take the form of, “DPC is the best hope for primary care in rural areas.” But the effect of a DPC/HSA fix will be to drive DPC physicians toward areas where middle class HDHP savers are in large proportion and away from rural areas where there are plenty of the poor and disproportionately few in the middle class.

DPC is way different than you paying Neflix. Notes

The State of New York has the financial capital of the country (arguably the world), has the most insurance companies in the country, and was the biggest state for the longest time. For these reasons it is generally looked to for leadership in the law on financial subjects primarily governed by state law. Here’s their statute.

(a) In this article:  (1) “Insurance contract” means any agreement or other transaction whereby one party, the “insurer”, is obligated to confer benefit of pecuniary value upon another party, the “insured” or “beneficiary”, dependent upon the happening of a fortuitous event in which the insured or beneficiary has, or is expected to have at the time of such happening, a material interest which will be adversely affected by the happening of such event.

(2) “Fortuitous event” means any occurrence or failure to occur which is, or is assumed by the parties to be, to a substantial extent beyond the control of either party.

Every state has the idea of fortuity, contingency, unforeseeability, something substantially beyond the control of the parties.

Many states, probably most, do indeed regulate service contracts/extended warranties for home and automobiles as insurance. Many regulate prepaid legal services as insurance.

Not Netflix, because it is sold on the basis that the subscriber’s utilization level is substantially within the subscriber’s control.

I can watch every night as I wish. For a DPC visit, I need to have a medical need to attend.

Other ways in which Netflix differs, from a policy perspective.

Netflix expressly reserves the right to change permitted utilization and pricing at any time for any reason, can vary server capacity, can vary program quality (its payment for licenses probably depend on many times a show is streamed).

DPC has explicit and implicit guarantees of quality and quantity, there’s a professional standard for determining need for a visit and quality of what has to be performed.

Marginal costs for Netflix supply are low, inputs are readily expandable, high utilizers have at best modest effect on supply or quality available for synchronous use by others; significant economies of scale; elastic supply.

DPC visits by patient X fully excludes patient Y from synchronous use (or MD from golf course); high marginal cost; supply vastly less elastic.

Way different social value for failure of the vendor to deliver.

Netflix: disrupted video streaming

DPC: disrupted access to health care

Netflix server outage in Seattle: 20K viewers each spend 5 minutes switching to Hulu

Qliance closes doors: 20K patients in Seattle hunting for PCPs accepting new patients; not getting med refills or timely A1c; trying to add health care plans outside of enrollment periods.

Systemic effects: If Netflix diverts TV addicts from Hulu, who cares. If DPC diverts a relatively healthy sub-population from, say, ACA compliant individual market policies that are guaranteed issue that would make ACA guarantees for those with pre-existing conditions more expensive.

If Netflix usage was essential to life and if the need for Netflix usage surged owing fortuitous viral infection, it might be wise to regulate Netflix

Finally, in considering whether or not DPC should be regulated as insurance, consider a DPC that finds itself with 50 spaces to fill and has to determine whether to make a pitch at/to

(a) an architecture firm full of middle-class and up college graduates working mostly at home this coming fall or

(b) a small meat-packing firm full of low income low education folk working indoors in close quarters.

Then consider DPC writ large, with clinics competing for business. Reread the foundational works of health care economics, and tell me why DPCs won’t end up as a primary care microcosm of underwriting, cherry-picking, death-spirals, and all of that.


DPC subscriptions transfer financial risk.

Identifying DPC nonsense does not require a law degree.

Watch out. Near you is a direct primary care advocate begging a legislator or regulator to make his medical practice less accountable. He is stomping his feet very, very hard and he’s shouting “This is not insurance”, “There is no risk being transferred”, or “My practice is not a ‘risk-bearing’ entity”.

This is not rocket science.

Question Set #1:

A. The day before I enter into a direct primary care contract, am I at risk of falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object?

B. The day after I enter into a direct primary care contract, am I at risk of falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object?

Answer Set #1

A. Yes.

B. Yes.

Question Set #2

The day before I enter into a direct primary care contract, am I at financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object?

The day before I enter into a direct primary care contract, is any direct primary care physician at financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object?

Answer Set #2

A. Yes.

B. No.

Question Set #3

A. The day after I enter into a direct primary care contract, am I at financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object?

B. The day after I enter into a direct primary care contract, is my direct primary care physician at financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object?

Answer Set #3

A. No.

B. Yes.

Question Set #4

A. If on the day before I entered into a direct primary care contract, I was the one at financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object and on the day after I entered into a direct primary care contract, my direct primary care physician was the one at financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object, had there been a transfer of the financial risk of having to bear the costs of primary care services needed to treat the consequences of my falling while out on a walk, spraining my ankle, and wounding myself by falling on a sharp object from me to my direct primary care physician?

B. How many heads of direct primary care advocates just exploded?

Answer Set #4

A. Yes.

B. Many.


The State of New York has the financial capital of the world, has the most insurance companies in the country, and was the biggest state for the longest time. For these reasons is generally looked to for leadership in the law on financial subjects primarily governed by state law. Here’s how they define an insurance contract.

(a) In this article:  (1) “Insurance contract” means any agreement or other transaction whereby one party, the “insurer”, is obligated to confer benefit of pecuniary value upon another party, the “insured” or “beneficiary”, dependent upon the happening of a fortuitous event in which the insured or beneficiary has, or is expected to have at the time of such happening, a material interest which will be adversely affected by the happening of such event.

(2) “Fortuitous event” means any occurrence or failure to occur which is, or is assumed by the parties to be, to a substantial extent beyond the control of either party.

Every other state has the same core idea of an obligation dependent on a fortuity.


Bonus round (advanced players only).

A. A municipality in the western corner of South Carolina self-insures to cover the costs of its employees’ health care. To meet part of its commitment to its employees it engages a group of primary care physicians who call themselves Western South Carolina Capitated Access MD. The employer pays them a fixed monthly fee for each employee who wishes to be a clinic patient in exchange for as much primary care as each such employee may need during the covered period. Is that capitation?

B. A municipality in the western corner of South Carolina self-insures to cover the costs of its employees’ health care. To meet part of its commitment to its employees it engages a group of primary care physicians who call themselves Western South Carolina Direct Access MD). The employer pays them a fixed monthly fee for each employee who wishes to be a clinic patient in exchange for as much primary care as each such employee may need during the covered period. Is that capitation?

Answers:

A. Yes.

B. Yes.


For pretzel lovers: For DPC advocates’ views on risk, capitation, and direct primary care, see this tweet thread and this one. For more DPC advocate double talk in this genre, extended to address adverse selection, try this masterpiece. See discussion here.

DPC cherry-picking: the defense speaks. Part 2.

Update: In the fall of 2020, KPI Ninja released the first study that relies on it’s new risk information technology. I find it sadly opaque.

Recap of Part 1

The direct primary care community has long tried to support claims that DPC reduces overall health care costs by 20% to 40% with non-risk-adjusted cost-reduction data drawn from employment health plans that allowed employees to elect between DPC and FFS primary care options options. But the first and, so far, only time that independent, neutral, certified professional actuaries looked hard at such a program, careful risk-adjustment showed that the savings claimed were merely an artifact of heavy selection bias. A DPC poster child, the Union County employer program — previously lauded for its claimed 23% cost reduction — was shown by Milliman Actuaries to have had a DPC cohort so young and healthy that it explained away all the observed cost savings.

Any reasonably informed employer or policy maker facing claims about the cost-effectiveness of direct primary care should insist that DPC provider boasts be scrutinized for evidence of selection bias.

In my last post, I noted that the DPC advocacy community has not even bothered to address the simplest of selection bias indicators, the younger average age of DPC cohort members compared to their FFS counterparts. I also noted that Milliman Actuaries have an age/gender risk-adjustment model1 and considered using it for the Union County study.

I further noted that in its Union County study, Milliman relied on a more complex model (“MARA-Rx”) which consider age, gender, and various therapeutic classes of prescription medications used by DPC and FFS group members. Milliman’s Rx risk-adjustment methodology, like its other risk adjustment models, was developed and validated as a health care cost predictor using health care cost data for millions of patients. There is nothing I can see, and nothing in the literature, to suggest that the Rx model has any inherent features that would unfairly penalize a DPC cohort in a studied DPC option employer health plan. As yet, no one in the DPC community has objected to Milliman’s use of the Rx methodology to assess the Union County DPC program, or to its future use in evaluating any other similar program.

There are even more complex and expensive methodologies, like MARA-Cx, that add diagnostic data harvested from payment claims to the factors used in MARA-Rx. In the Part 1 post, I also mentioned an arguably surprising difference in approach to selection among risk-adjustment methodology between Milliman Actuaries, who have no financial interest in the direct primary care movement, and KPI Ninja, a data-analytics group closely connected to the direct primary care movement. Both Milliman and KPI Ninja concurred that risk adjustment methodologies like “Cx” are likely to understate risk score for DPC cohort members because direct primary care physicians do not file claims.

KPI Ninja pointedly laments this “donut hole” in the claims-based data. But there is no anti-DPC donut hole in Rx based risk adjustment methodology.2

Although it possesses a fully-validated claims-based risk adjustment methodology (“MARA-Cx”), Milliman’s common-sense response to the data donut hole problem was to set that Cx methodology aside and determine risk-scores for the Union Count cohorts using only the Rx age/gender/prescription drug methodology. Like Milliman, KPI Ninja has access to risk-adjustment software engines that have equivalents, in a package known as ACG®, to both Rx and Cx. Unlike Milliman, KPI Ninja seemingly rejects Rx methodology and, instead, embraces Cx type methodologies that have the very donut hole KPI Ninja laments.

Why complain about the donut hole in Cx, then reject Rx which has none, and then return to and embrace Cx? Might it be precisely because KPI Ninja knows that Rx based risk adjustment will produce results that are sound, but not happy, for its cherry-picking DPC clients? On the other hand, when convenient, a donut hole can first be performatively disparaged as biased, then filled with custom data products developed by KPI Ninja to tell stories more to DPC’s liking.


Context: DPC docs feel coding makes their patients sick.

Direct primary care practitioners avoid third-party health care payment of claims and the (often digital) paperwork that accompanies it. While the logic of subscription practice renders coding procedures for reimbursement unnecessary and, therefore, a target of scorn, D-PCPs also disdain the type of recording of diagnostic codes that attend claims for third-party reimbursement.

Here’s what Dr Jeff Gold, a co-founder of the Direct Primary Care Alliance, had to say in a post entitled, “ICD-10: It’s Nice Not Knowing You.”

This is nothing more than another layer of bureaucratic red-tape that does nothing to enhance the quality or cost of your care, but rather furthers the disease process. All it does is waste more of your physician’s and office staff’s time – time that should be spent working towards your care. . . .

Luckily for us [Direct Primary Care doctors], we have nothing to do with this nonsense. [Emphasis supplied.]

ICD-10: It’s Nice Not Knowing You

Tell us how you really feel, Dr Gold.

DPC doctors, in other words, not only decline to file claims and code their procedures, they also hold industry standard diagnosis coding in fiery contempt. As a result, the donut hole problem can not be solved by simply collecting DPC patient diagnosis codes from their direct primary care physicians.


Enter KPI Ninja — with balm for DPC’s abstinence

Missing data reduces population risk score. Meaning it will look like you are treating healthier patients in the eyes of those who use these risk scores (employer data vendors, brokers, health plans) … aka they can argue that you are cherry picking.

KPI Ninja Blog Post: Claims vs. EHR data in Direct Primary Care

While the details remain murky, KPI Ninja seemingly plans to meet cherry-picking charges by filling the donut hole with information somehow scoured from such EHR records as direct primary care doctors may have.

But how?

In theory, KPI Ninja could develop a way to reverse engineer a DPC’s EHR entries and other information to generate the diagnostic codes upon which the DPC physician would have arrived had she not thought that participation in diagnostic coding was wasteful. How proceeding “backwards” to arrive at codes would result in any less waste is difficult to image, so that effort strikes me as misguided.

In any event, validation of a reverse engineering model would likely require resources beyond those of KPI Ninja and the DPC advocacy community. It would also likely require the participation of a control group of D-PCPs willing to do extensive coding.

However, for physicians like Dr Gold who have identified ICD-10 coding as “furthering the disease process”, such participation in a coding control group would be an ethical violation; it would “do harm”. Furthermore, if Dr Gold is correct, the members of a patient panel studied in such an experiment would have to give informed consent.

Furthermore, to whatever extent EHR mining for diagnosis codes omitted by a D-PCP produces fully accurate risk codes for members of a DPC cohort, the same mining techniques should be applied to the EHRs of FFS patients to correct any omissions by FFS-PCPs. What’s sauce for a DPC goose is sauce for an FFS gander.

Finally, fair implementation of a model in which diagnosis codes for risk scoring are derived from DPC-EHRs for comparison with diagnosis codes from FFS-claims would require safeguards against the DPCs deliberately larding EHR’s with entries that result in up-coding, just as FFS-claims data is subject to procedures to check up-coding. Again, goose/gander.


Perhaps, KPI Ninja merely has in mind developing a direct method of converting mined EHR data into risk factors that are not directly commensurate with those from diagnosis-based risk models, but that are instead presented to inquiring employers and policy-makers as an alternative model of risk-adjustment.

Precautions would still apply, however. If EHR data on, say, biometrics or family history is brought in demonstrate that the DPC population is less healthy than average, a knowledgeable employer should insist on counterpart data from the EHRs of FFS patients.

A recent addition to KPI Ninja’s website suggests their emphasis may rest on pre-post claims comparisons. It will of course be important to include pre- and post- data on DPC patients and their FFS counterparts. That will be somewhat revealing if the pre-choice claims data for the two populations are similar. But if the results of the Milliman study are representative, that will most likely not be the case.

In the more likely event of a higher level of prior claims in the FFS population, any “difference in difference” analysis of pre-post claims between DPC and FFS populations will still require an attempt to see whether the FFS higher “pre” claims might be accounted for by intractable chronic conditions. Such a finding would impeach any inference that DPC group pre-post gains can simply be projected onto an FFS group. And such a finding seems likely, if the Milliman actuaries were correct to ascribe selection bias to the tendency of the ill to stick with their PCPs; a “sticky” relationship to a PCP seems quite likely to correlate “sticky” chronic health conditions that bind the patient and the PCP.

Further explication from KPI NInja as to how its plans will work was said to be forthcoming. I appreciate the insights they have given in the past, and look forward to learning from them in the future.


There are many risk adjustment software packages available from neutral academics, accountants, and actuaries. They can be expensive; even access to the packages supplied by CMS for use by insurers participating in the Affordable Care Act run a bit over $2 per enrollee per year. Importantly, some of the packages rely on proprietary algorithms, but nonetheless tend to be generally transparent. In most cases, however, these packages come from neutral academic or actuarial sources.

Per se, I fault DPI Ninja neither for its close connection to the DPC industry nor for offering to DPC clinicians the best “risk adjustment” bang that can be generated from the least record keeping buck. To the extent that DPI Ninja delivers DPC data that is generally transparent in its methods and assumptions, that work will speak for itself. Should DPI Ninja lay on data produced by secreted assumptions and methodology, however, it should expect that its business relationship to DPC will affect the credibility of that data.3

Update: In the fall of 2020, KPI Ninja released the first study that relies on it’s new risk information technology. I find it sadly opaque.


For completeness, two parting thoughts.

First, none of foregoing is intended to deny that membership in a direct primary casre practice can significantly reduce usage of emergency departments. Of course it can! The question is what does it cost to avoid such visits. It is very rare for United States Presidents to go to emergency rooms as there’s always a doctor within a few hundred feet. DPC docs are easier to reach at odd hours and are more available for same day visits. They have fewer patients, and that costs a lot more money per patient.

Second, I have discussed in many posts the many sources of selection bias. Use the search item in the menu to find example using words like “selection”, “bias”, or “cherry”. It’s real and the only truly debatable proposition is whether DPC advocates who deny it are unintentionally fooling themselves or deliberately fooling you.


1 A college freshman IT student could probably develop an age/sex risk adjustment engine and apply it age/sex data from paired DPC/FFS cohorts over a weekend. If DPC clinics don’t report age/sex/risk comparisons with their FFS counterparts, it’s because they know full what the results would show.

2 It may even be that Rx metholodogy favors DPCs.

I expect to hear soon that Rx risk adjustment discriminates in favor of “bad”, overprescribing PCPs by making their patients seem sicker than those of “good” doctors who never overprescribe. But this can become an argument that Rx discriminates against DPC if, and only if, it is also assumed that DPC has fewer “bad” overprescribers than does FFS. There is no clear factual basis for assuming, in essence, that DPC doctors are simply better doctors and prescribers than their FFS counterparts.

If anything, DPC self-promotion suggests that Rx data would be skewed, if at all, in the opposite direction. DPC advocates regularly claim that DPC avoids expensive downstream care by better discovering illness early and managing chronic conditions better, by coaching patient compliance and by lowering the cost of medications. Another recurrent theme among DPC advocates is that FFS doctors rely too heavily on specialists; but, if true, FFS cohort patients would be more likely that DPC patients to have over-prescription “wrung out” of their regimes. In these ways, applying a risk adjustment methodology based on prescription medication data, DPC’s own bragging suggests that any donut hole is likely to make the FFS cohort appear healthier.

3 The following fairly new statement on KPI NInja’s website does not bode well, suggesting both secrecy and a predetermination of an answer favorable to DPC.

“We analyze historical claims data from self-insured employers by utilizing our proprietary algorithms to identify cost savings and quality improvement opportunities. Get in touch to learn more about how we can help show your value to employers!”

DPC cherry-picking: the defense speaks. Part 1.

Jump to Part 2.

Within days of the Milliman report warning of the “imperative to control for patient selection in DPC studies [lest] differences in cost due to underlying patient differences [] be erroneously assigned as differences caused by DPC”, the first rumbling of resistance from the DPC advocacy community emerged. This was a suggestion, addressed to one of its authors, that the Milliman study may have treated the direct primary care employer unfairly.

KPI Ninja also reached out to me. After some initial misunderstanding on my part, and subsequent examination of KPI Ninja’s online published material on this subject, I reconstruct my understanding of KPI Ninja’s argument in the immediately upcoming section. For reasons discussed in the next following section, I have concluded that KPI Ninja’s argument, although not without insight, simply does not apply to the risk-adjustment methodology used in the Milliman study itself. Thereafter in this post, I begin to respond more broadly to the KIP Ninja critique and to the not-yet fully visible “remedy” it is apparently developing. I will conclude in a subsequent post.


KPI Ninja’s Donut Hole Concept

Some data used in some risk-adjustment methodologies are diagnostic data harvested from claims, including both primary care and downstream care claims. The risk that manifests itself in downstream claims properly counts in evaluating a patient’s risk, whether the patient is a DPC or an FFS patient. But a problem can arise (a”donut hole” in KPI Ninja’s lexicon), in situations where some PCPs have success at averting downstream claims. If the patient is in an FFS practice, the practice is scored as bearing any risk factor appearing in the primary care claims submitted by the FFS PCP. FFS practices, in essence, get fair credit for their good work in avoiding downstream claims. On the other hand, D- PCPs do not file primary care claims; as a result DPC patients risk factors go unrecorded when not reflected in downstream claims; DPC docs therefore do not get proper credit for their good works.

In the upshot, DPC patients look relatively less risky than they really are. On this analysis, risk-adjustment by claims dependent methods of two equally risky panels of DPC and FFS patients will inevitably disfavor DPC.1


The Milliman study of DPC used risk-adjusment that had no donut hole.

There are ways of evaluating population risk that do not depend on harvesting diagnostic data from physician claims, methods for which there is no claims associated donut hole. Milliman itself, based on experience with millions of people, developed and validated at least two methodologies that do not require claims data: one (age/sex) determines risk factors based only on the age and gender characteristics of the populations being compared; a second (Rx) adds, to age and gender, additional patient information about the usage of different therapeutic classes of prescription drugs. Under the Rx methodology, claims are not looked at; DPC and FFS docs get the same “null credit” for every prescription drug avoided through their primary care work.

Of course, Milliman also has a claims based risk-adjustment methodology (Cx). For its study of Union County’s direct primary care option, Milliman carefully considered using the Cx methodology and, precisely because they identified the donut hole, expressly rejected it. Milliman also considered using its age/gender risk adjustment methodology , but decided to use its more granular RX methodology.2


Simple, lost cost risk-adjustments are affordable for modestly sized employers

The beauty of an age/gender risk-adjustment is that it is straightforward. Nor is it doomed to failure by its simplicity. Over three-fourth of persons under the age of 65 lack any diagnosis consider significant for risk adjustment carried out under the Affordable Care Act. Nor is it likely to be expensive; it is definitely not rocket science. A college freshman just learning how to use a spreadsheet could fire it off in an hour, if pointed to a readily available table, and a data set with each employee’s age and gender.3

In its own published “research”, one of the larger DPC groups (Nextera) used raw total claims from an immediate pre-DPC period as a basic risk adjustment methodology for employer DPC and non-DPC groups claims data for the period following the creation of the DPC option. Those choosing Nextera had vastly lower prior claims.4

Dan Malin, a TPA exclusively serving small employers, addressed a 2019 DPC Summit forum on employer DPC with about 100 attendees present. He claimed that his firm could calculate the medical consumption of that group for a coming year to within five or six percent by having each fill out an ordinary health insurance application.


Has an employer-option DPC cohort ever been OLDER than its FFS counterpart?
Or ever entered a DPC option with a HIGHER prior claims experience?

But DPC advocates could go some of the way long way toward reassuring ordinary employers by demonstrating measurable similarities between cohort members being studied. Say, for example, that a DPC group had virtually the same claims as an FFS group in a claims year prior to creation of a DPC option. Unfortunately, for some reason, whenever these type of comparison have been made, the DPC cohort has turned out to to have had a history of smaller pre-DPC claims. This might be because, as Milliman warned, direct primary care is a cherry-picking machine.

As one DPC thought leader has pointed out, “larger direct primary care companies like Qliance, Paladina, and Nextera have repeatedly reported 20% plus savings for employers using the DPC model. Many smaller employers have found similar savings [].” If those selecting DPC were equally likely to be older or younger than their FFS counterparts, the chance that even as few as ten5 such studies would each have had younger DPC populations would be less than 0.1%.

Alas, for some reason, there are no known reports of a DPC cohort being older than its FFS counterpart. Also, perhaps for some related reason, it often appears that employer DPC cohorts are younger than their FFS counterparts.

In some cases, DPC advocates make an effort to show that a presumably large percentage of a DPC cohort have multiple chronic conditions, but reliably matched data from the corresponding FFS counterpart cohort has not, to our knowledge, been reported. Indeed, a DPC advocate promoting the very poster-child clinic studied by Milliman once sarcastically dismissed the idea of cherry-picking by pointing to the chronic conditions of the DPC’s patients — while noting that “control group data is not available”. Really! Since Milliman presented that very control group data in May, we’ve heard no comment by that author.


Does any of these methods have any significant built in distortion against direct primary care? Does direct primary care make younger? Did receiving direct primary care in one year lower claims costs for the preceding year?


Link to Part 2.


Footnotes

1 A masterful extention of that argument came in a tweet from one DPC thought leader, who was asked about the lack of risk-adjustment in a just-published savings claim for his own DPC practice. He invited the inquirer to consult DPI Ninja “or spend $100,000 to prove them right or wrong.” Is this how he plans to answer employers who’ve read Milliman’s advice for employers?

2 Interestingly, Milliman recorded that adjustment using Rx in this particular case was more favorable for DPC than using age-sex adjustment.

3 Virtually every direct primary care clinic in the country has chosen an even simpler path when using age only to establish a variable, usage-anticipation- component for its monthly fee DPC schedule.

4 The employees who chose Nextera’s direct care had, on average, historical prior claims that were 30% less than those who declined direct primary care. Interestingly, Nextera sought to rely on a “difference in difference” analysis, but intertemporal claim comparisons of that sort fail if, for example, the declining groups higher “pre” claims can be accounted for by intractable chronic conditions, something that seems entirely likely.

5 At the moment of commencement of DPC Summit 2020, a least ten such studies of employer option DPC have been publicized. At least one additional study seems likely to appear on July 18, 2020. I wonder if the study results reported will include a comparison of the average age of the two cohorts.


Link to Part 2.

Milliman: A $60 PMPM DPC fee buys an employer a zero ROI.

An actuarial study brings employer direct primary care to a turning point.

Milliman’s actuaries insisted that DPC cost reduction data without risk adjustment is essentially worthless. A second prong of Milliman’s analysis suggested that the direct primary care model is associated with a 12.6% over-all reduction in health services utilization*. Then, working from that number, Milliman went on toward a third suggestion: that an employer who buys into DPC at an average price of $60 PMPM would likely have an ROI of zero.

That is not a very good deal for either an employer or a DPC practice.

For an employer, entering into a break even deal would mean foregoing other investment opportunities, while incurring inconvenience of change and probably a loss of good will from a number of employees who might be, or feel, forced or financially pressured into a narrow primary care network. Why bother?

For a DPC provider, $60 PMPM works out to $432,000 per year for the patient panel of 600 members that DPCs like to brag about. But an average PCP compensation package in, say, Anderson, South Carolina comes to about $276,000. That leaves about 36% of revenue for all overhead. That’s not much.

The American Academy of Family Physicians tells us that overhead for family physician practices runs around 60% of revenue. The most recent peer reviewed study of the subject (2018) indicated billing and insurance (BIL) costs for primary care came out 14.5% of revenue. A somewhat earlier peer reviewed study came near this, finding that physician practices had BIL costs of about 13% of revenue. Even if, say, 15% of revenue can be eliminated in direct pay, D-PCPs could still expect overhead to be 45% of revenue.

In the direct primary care employer clinic, moreover, billing costs do not fall to zero; patient rosters need to be kept up to date, matched to employer records, and processed. In addition, most direct primary care physicians also provide a significant measure of separately paid goods and services for which an employee, employer, employer’s insurer, or a TPA may require documentation and billing. Moreover, much of the data attributed to billing and insurance costs in an FFS setting has a counterpart in direct primary care collection of metrics needed to demonstrate value to an employer.

Accordingly, even for a non-insurance direct primary care clinic, overhead of 36% of revenue is scanty.

At the same time, DPC practitioners have — and regularly express — a very high opinion of themselves and the care they give. As group, they seem distinctly unlikely to settle for merely average levels of compensation.

The most profitable path forward for direct primary care is to persuade employers that paying PMPMs over $60 will do more than break even. Historical brags, based on data that was not adjusted for risk, claimed employer savings from 20% to 40%. A DPC thought leader recently published a book on employer DPC that collected references to such seven studies, including one that claimed to have reduced employer costs by 68%.

Now that real actuaries have weighed in, those days are numbered.

So now they just fake it.


* I believe that Milliman’s 12.6% figure vastly overestimates the reduction in health services utilization association with direct primary care. As explained here, DPC may even result in an increase in health services utilization. Is it really plausible that taking a scarce resource — the time of PCPs — and spreading it thickly over tiny patient panels would NOT result in net economic loss?