KPI Ninja’s Nextera study: a “single blunder” introduction

The KPI Ninja report on Nextera’s school district program claims big savings when employees chose Nextera’s direct primary care rather than traditional primary care. But the analysis reflects inadequacy of a high order. Here’s a starter course of cluelessness, actually one the report’s smaller problems.


The report ignored the effect of an HRA made available to non-Nextera members only. But $750 in first dollar coverage gets a cost-conscious non-Nextera employee a lot of cost-barrier-free primary care for her chronic condition. And, unlike the dollars the SVVSD spends at Nextera, every HRA dollar the district covers for a non-Nextera employee still applies to her deductible.

Is Nextera the best choice for her?

If she’s a math teacher at Longmont High, the odds are extremely high that she’ll figure this out, then reject Nextera.

No one, not even a KPI Ninja, can make sense of the SVVSD’s programs without considering the profound effect of the HRA — shifting costs, shifting utilization, and shifting member plan selection.

Fun – duh – mentals of plan comparison

You cannot accurately assess cost differences between plans without addressing significant differences in plan benefit design.

You cannot accurately assess utilization differences between plans without addressing significant differences in plan benefit design.

You cannot accurately assess selection bias between plans without addressing significant differences in plan benefit design.

A $750 HRA is a significant difference in plan benefit design, large enough to seriously affect a $913 savings claim.

The KPI Ninja report failed to address the HRA. For that reason alone, one might think it reasonable to disregard the report in its entirety.


But that might be too fair to KPI Ninja and Nextera. There’s lots more and it gets worse. The KPI Ninja/Nextera report is nonsense piled high.


The HRA issue and many others are discussed at length in these five posts:

KPI Ninja/Nextera report: every single cost comparison has an 10% “benefit design” error describes how in his “School District Claims Analysis“, the actual Analyst overlooked key differences in how the actual “School District” pays actual “Claims“.

KPI Ninja’s Nextera Risk Measurement Charade focuses on the study’s major failure on population health measurement issues. While Nextera and KPI Ninja bragged of risk adjustment performed by an academic research team, neither the team and nor the risk adjustment were real.

Nextera did not reduce inpatient hospital admissions by 92.7% focuses on a single astonishing utilization claim from the Nextera report, that might reflect a severe error in basic data collection — one that just by itself would account for every penny of the claimed savings. Or is it just cherry-picking at the Olympic level?

KPI Ninja’s Nextera analysis: more than enough problems collects many of the study’s other problems relating to design, data limitations, induced utlitization and so on. There are many deep cutting deficiencies in the Nextra report.

Nextera’s Next Era in Cherry-Picking Machine Design focuses on the need for any report on the SVVSD plan to reflect the differences in benefit design. Although updated recently to bridge to the published report, its core content predates the published report by months, and it was shared in early summer 2020 with both KPI Ninja and Nextera.

Engage.



By some reckoning, this is the 100th post on dpcreferee.com.


Nextera did not reduce inpatient hospital admissions by 92.7%.

Abstract: KPI Ninja’s report on Nextera’s direct primary care plan for employees of a Colorado school district clinic claims profoundly good results: nearly $1000 per year in savings for every Nextera clinic member and a staggering 92.7% reduction in inpatient hospital admissions. Both claims rest on the proposition that a population of middle-aged. middle-class, white-color, healthy Colorado teachers, spouses, and children families experience an inpatient hospital admission rate of 246 per 1k, 30% greater than Colorado’s Medicare population.

In their path-breaking report on Direct Primary Care to the Society of Actuaries, the team from Milliman Actuaries described a model framework for an employer direct primary option. They concluded that DPC was a break-even monetary propositions when DPC monthly fees were set at an average of $60 PMPM, $720 PMPM. That modeling was based on data from the first, and still unique, wholly disinterested, actuarially sound analysis ever performed on a direct primary care clinic; the particular clinic had long been treated by the DPC community as a darling poster child; and Milliman Actuaries have an impeccable reputation.

Just months after the Milliman report, Nextera set out to entice potential employers and members with a brand new report from its analyst, KPI Ninja. That case study claimed that Nextera saved the Saint Vrain Valley School District $913 PMPY. But if Milliman was anywhere near correct when it set $60 PMPM as a break even, zero savings proposition, then a $913 PMPY savings for an even more pricey Nextera clinic looks too good to be true.

A bottom line so at war with the expectations of informed experts, like the world class Milliman Actuaries, is a red flag. It prompts close examination of the data and the analysis on which it rests.

And there it was: data on the non-Nextera population’s hospital utilization that is far too bad to be true.

If we take KPI Ninja’s risk measurement at face value, both the Nextera and non-Nextera populations were quite healthy, with both populations with likely to have medical costs well less than half those of a national reference data population (ACG® risk scores less than 0.400). This makes sense for a school district population with its likely surfeit of white collar, middle class workers. The district is also in Colorado, which has relatively low hospitalization rates compared to the nation at large — a recent report by the Colorado Hospital Association pegs the statewide rate at under 80 inpatient admissions per 1k. The KPI Ninja report puts Nextera’s own IP admit rate at a plausible 90 per 1k (not particularly laudable as it is double the IP admit rate of the DPC studied by Milliman).

On the other hand, the KPI Ninja report puts the non-Nextera inpatient hospitalization rate at 246 per 1k. That large (1590), relatively healthy, and teacher-heavy population of school district employees and their families, tracked for a full year, were presumably hospitalized at more than 3.2 times the rate of average Coloradans. Indeed, the 246/1k admissions rate KPI Ninja reports for the non-Nextera cohort, comprising mostly white collar adults and their children, with an average population age in the thirties, is nearly 30% higher than the admission rate for Coloradans receiving Medicare, a group more than three decades older.

Pooling all the patients studied by KPI Ninja from both cohorts yields a blended IP admit rate of 195/1k which is still higher than the Medicare IP admit rate of 190/1k. Given the age and gender mix in the two cohorts, application of national statistics (AHQR’s HCUP data) would predict IP admission rates of 88 (Nextera) and 96 (Non-Nextera).

That all those middle-aged adults and their kids have the same IP admit rate as a Medicare population does not pass the smell test.

There appears to be a massive error at work here, and there is enough of it to explain away all of Nextera’s $913 claims cost brag without breaking into a sweat.

Consider an alternative: what if Nextera cut inpatient hospital admissions by a “mere” third, starting from a presumptive non-Nextera IP admission rates of 136 per 1K. 136/1k is still an outsize IP admit rate for a commercial population. 136 per 1k would still be more than double the highest reported IP admit rate appearing in ANY prior study of direct primary care. And that highest report (58/1k) came from the study by the professional and fully independent Milliman actuaries.

Moreover, within the landmark Milliman study, the DPC was found to have only an IP admission rate reduction for DPC of 25%. The 136/1k I propose here for the non-Nextera corresponds to a Nextera rate reduction effect of a full one-third. Even with that generous upgrade for Nextera over Milliman, and assigning hospital costs per admission for non-Nextera patients calculated from the Nextera report ($8317), use of 136/1k wipes out every penny of the $913 cost reduction claim.

Of course, it did occur to me that perhaps the difference in hospital utilization might be accounted for if the non-Nextera population were significantly risker than the Nextera population, i.e., as if the Nextera population had been cherry-picked in the way the Milliman report anticipated. I had suggested as much in my June post reacting to an initial release of Nextera’s raw data.

But the CEO of Nextera has expressly told us by Youtube video that the Johns Hopkins ACG® Research Team found the risk difference between the populations to be statistically insignificant. In that statement, Dr. Clinton Flanagan was completely incorrect, but let’s indulge that falsehood for a moment, yet still try to account for the insanely high IP rate for non-Nextera patients.


The 90/1k IP admission rate for Nextera’s own members is nearly identical to the national average for a group of like age and gender (88/1k per HCUP, see above.) This suggests that Nextera-care is pretty ordinary, so we cannot attribute Nextera’s 90 to 246 “win” on IP admit rates to Nextera’s special magic.

So, how did the non-Nextera cohort come to have 246 IP admits per thousand?

Does the very act of eschewing Nextera cause bad health luck — cancers, infectious disease, car crashes, moose attacks, etc?

Here’s an idea of how much bad luck might be needed to explain that 246/1k IP admission rate. From data in the table at the bottom of page 10 in KPI Ninja’s report, assuming the data are correctly described, it can be computed that only 50 unique individuals in the 1590 member non-Nextera cohort had an IP admission. If the IP admit rate is indeed 246 per 1k, then the full cohort would have had 391 admits. That’s an average of almost eight admits per year for each of the 50 patients who had one or more admissions. That’s a heck of a lot of bad health luck.

If not bad luck, then perhaps bad doctors. Is the fee for service primary care physician community in the Saint Vrain Valley incompetent?

One thing that has always struck me is how the DPC community drifts so easily into impugning its fee-for-service competitors. Attributing a 246 per 1k hospital admit rate to the patients of the local FFS community libels those practitioners.

A Nextera press release, and a YouTube video both directly claim a 92.7% reduction in IP admit rate. For over seven months, Nextera also included claim that in a since retracted version of its lengthy report. Warning members of the public that rejecting Nextera’s services could increase their risk of hospitalization by 1200% goes far beyond reasonable commercial “spin”. That’s misleading medical advertising that warrants investigation and sanction.

Apart from extreme cherry-picking, the most likely explanation of a seemingly insane IP admit rate is that data describing a dominating stack of school district money has been mishandled.

A reported 246 per 1k admit rate for any cohort of middle-aged, middle class, white-collar workers and their children is just too bad to be true.


The KPI Ninja report has numerous additional weaknesses, including a failure to adequately address population risk measures, benefit design, study design, and data limitations.

That red flag flies high. Nextera’s claims of $913 savings, a 92.7% reduction in inpatient hospital admissions, and both without cherry-picking are too good to be true.

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 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 its 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!”