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 93.7% 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.
The Nextera report, a Nextera press release, and a YouTube video all directly claim a 92.7% reduction in IP admit rate. Warning members of the public that rejecting Nextera’s services could increase their risk of hospitalization by 1200% goes far beyond reasonable commercial “spin”. It’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.