McAllen: A Tale of Three Counties

Daniel Gilden

Introduction

The challenge of constraining costs while maintaining or enhancing the quality of medical care is vividly brought to life by Atul Gawande in his recent widely-read New Yorker essay The anecdotal evidence presented in the article is compelling as a description of how physician practices can relate to excessive costs.  The assertion that the observations in McAllen also explain McAllen’s costliness is an inductive exercise that may go too far.  Physician ownership of imaging facilities, ownership interest in hospitals and more subtle forms of self-referral are all substantially present in large healthcare market areas across the country.  Is McAllen an extreme example of a bad physician culture or is there another explanation?  Our analysis of Medicare data from McAllen Texas demonstrates that exceptionally high rates of chronic disease and poverty explain much of the variation in cost.

According to Gawande, McAllen Texas has a physician culture that promotes high cost, low quality care. By comparison El Paso is portrayed as having a similar patient population to McAllen with lower costs of care.   Grand Junction, Colorado, however, the antithesis of McAllen according to the article, is credited with having a physician culture that promotes low costs and high quality.  Ultimately Gawande warns that by failing to change the physician culture nationally, “McAllen won’t be an outlier.  It will be our future.”  But is McAllen really an outlier, a harbinger of physician income-enhancing practices run amok?

A fair comparison between McAllen and Grand Junction would include a more precise analytic methodology than could be offered in Dr. Gawande’s article.  Such an analysis is important: the correct diagnosis of the health care cost crisis is an essential step in selecting an effective prescription.  If McAllen is not an outlier and Grand Junction is not a paragon, then the solution is not to simply tamp down variation by exporting Grand Junction values to McAllen.  If the physician practices reported by Dr. Gawande in McAllen lead to explainable patterns of costs according to current norms, then those practices are part of a national phenomenon right now, not in a nightmare future.

An analysis of the Medicare population in the three counties can place Dr. Gawande’s observations in a more complete context.  Medicare beneficiaries enjoy a standardized benefit package, and detailed data are available on the services they receive.  We can use cost data for Medicare enrollees in the three counties to test Dr. Gawande’s assertions regarding McAllen’s and Grand Junction’s comparative health care costs.  Medicare fee-for-service claims provide us with service level payment and patient health status information; Medicare monthly enrollment data details HMO affiliation, Part B premium assistance and beneficiary demographics.  The Centers for Medicare and Medicaid Service supplies researchers (including the Dartmouth Health Atlas team) with data of this type for Medicare policy analysis.

Accurate Medicare Cost Comparisons

The city of McAllen lies at the center of Hidalgo County, one of the costliest areas for Medicare.  The population is racially diverse, low income and exhibits high levels of chronic disease.  El Paso is similar to McAllen but with less poverty.  Grand Junction is the county seat of Mesa County, a largely white and relatively wealthy region.  In Exhibit 1 annualized Medicare fee-for-service payments for the counties of McAllen, El Paso and Grand Junction show wide divergence in the total Medicare spends per beneficiary.2

Exhibit 1: Annualized Payments per Medicare Beneficiary by County of Residence, 2006

County Medicare Enrollees Medicare Payments
McAllen, Texas 63,770 $12,384
El Paso, Texas 85,478 $6,163
Grand Junction, Colorado 22,887 $4,436

The payments in McAllen’s county are twice as high as in El Paso’s and nearly three times as high as in Grand Junction’s but adjustments are required to the statistics to make the comparison fair.  These adjustments should include normalization for Medicare coverage type and population health.  Relatively few McAllen area Medicare beneficiaries are enrolled in HMOs (2%) in comparison to Grand Junction (42%) and El Paso (16%).   Medicare publishes costs only for services paid on a fee-for-service basis; some services supplied by cost-based HMOs (more common in Grand Junction than in either McAllen or El Paso) are included and some are not.  As a result the cost of care for counties with high numbers of Medicare HMO enrollees is under reported.  In addition, while all eligible individuals receive hospital insurance under Part A of Medicare, beneficiaries must pay a monthly premium to receive outpatient coverage under Medicare Part B, or are enrolled by Medicaid if they are poor enough to meet the state’s income requirement.  The percent of the population in the different counties without full Part A and Part B benefits varies.  In Grand Junction almost twice as many beneficiaries do not have Parts A & B coverage compared to McAllen (4% versus 8%).  The outpatient expenses of this population are not included in Medicare expenditure reports.  In Exhibit 2 HMO enrollees and Medicare beneficiaries without full Medicare benefits are removed from the comparison.

Exhibit 2: Comparative Annualized Payments per Medicare Beneficiary by County after Managed Care and Medicare Part A&B Adjustments, 2006

County Medicare Enrollees Medicare Payments
McAllen, Texas 59,665 $13,150
El Paso, Texas 67,133 $7,656
Grand Junction, Colorado 12,355 $5,579

When the analysis is restricted to cost and enrollment data only for Medicare fee-for-service beneficiaries covered by both Part A and Part B, Grand Junction’s beneficiary annual costs rise by almost 25%.  The difference between McAllen and Grand Junction beneficiary costs falls, but McAllen Medicare costs, now for populations with the same coverage, are still well over twice those for Grand Junction.

County Socio-Demographic Characteristics

The dissimilarities between the McAllen and Grand Junction county populations are extensive.  The socio-demographic characteristics of a population affect its access to care, ability to pay out of pocket for uncovered care and rates of disease associated with diet and life history.  The costs of Medicare co-pays and deductibles can be substantial barriers to access, and history of health care coverage and access to preventive care vary substantially based on socio-demographic variables.  Low-income individuals often reach Medicare enrollment age with a lifetime history of access and cost barriers, a potent mixture.  Barriers to access to care can lead to expensive hospital care for conditions normally treated on an outpatient basis.

Grand Junction Medicare enrollees are 98% white and only 11% require assistance in paying for their Medicare Part B premium (a proxy for low income status).  In contrast McAllen and El Paso are both 26% Hispanic, and a higher proportion of Medicare beneficiaries rely on Medicaid to pay for Part B — 36% in El Paso and 48% in McAllen. To assess how socio-demographic factors affect Medicare costs, Exhibit 3 compares costs for beneficiaries with and without Part B premium assistance.

Exhibit 3: Comparative Annualized Payments by County and Need for Premium Assistance, 2006

County Premium Assistance-No(not low income) Premium Assistance-Yes(low income)
McAllen, Texas $10,012 $16,518
El Paso, Texas $6,709 $9,374
Grand Junction, Colorado $4,853 $11,425

Expenditures are consistently higher for low income beneficiaries, but McAllen is still more expensive than Grand Junction for both income groups — more than 45% more expensive for low-income beneficiaries and more than twice as expensive for those not receiving premium assistance.  However, the Grand Junction advantage is not as great for the low-income population as for higher income beneficiaries.  Could it be that a good part of the McAllen “excess” is simply due to its larger proportion of low-income Medicare beneficiaries compared to Grand Junction?

But socio-economic differences in themselves cannot explain cost differences. What makes the low income population so much more expensive to care for? And why is El Paso, which also has a large low-income Medicare population, so much less costly to Medicare than McAllen?

Population Health

Exhibit 4 uses estimates of population rates of disease derived from Medicare hospital and physician claims to reveal that the prevalence of chronic disease is substantially higher in the McAllen Medicare beneficiary population than in Grand Junction or El Paso; and that the proportion of the McAllen Medicare population with more than two of these conditions is a whopping 52%, in comparison to 23% in the Grand Junction area and 34% in El Paso.

Exhibit 4: Disease Prevalence by County, 2006

McAllen El Paso Grand Junction
Single Selected Condition Rates per 1,000
Diabetes 422 330 145
Ischemic Heart Disease 443 252 211
Heart Failure 168 107 74
Cerebro-Vascular Disease 202 93 56
Chronic  Respiratory Disease 266 190 169
Arthritis 405 290 239
Dementia 107 57 51
Parkinson’s 20 15 12
Multiple Conditions Population Percentage
None of the Selected Conditions 23% 36% 46%
One Condition Only 22% 27% 30%
Multiple Conditions 55% 37% 24%

Many of the disease rates for the McAllen population are more than double those for Grand Junction.  If the Medicare population in McAllen is truly that much sicker wouldn’t we expect the payments to be greater?  A comparison of expenditures for Medicare enrollees without a diagnosis of diabetes or heart disease in the last year shows that costs for these standard populations are statistically very close (Exhibit 5).

Exhibit 5: Medicare Monthly Payments per Patient without a Diagnosis in the Year for Diabetes or Heart Disease, 2006

Row Labels Medicare Enrollees Monthly Per Person Payments
McAllen, Texas 28,680 $3,147
El Paso, Texas 47,960 $2,564
Grand Junction, Colorado 11,160 $3,307

By eliminating diabetes, ischemic heart disease or heart failure from the population payment measures the Grand Junction advantage is completely removed.  Grand Junction is just as costly as McAllen for populations without one of these conditions.

Even though diabetes and heart disease are both costly and highly prevalent in McAllen, beneficiaries experience a wide range of costly illnesses, and patients with multiple conditions are difficult to treat.  We used a more sophisticated risk adjustment method to take into account an array of concurrent conditions.3 Beneficiaries in the top risk scores, the sickest patients, make up 27% of the McAllen, 16% of the El Paso and only 12% of the Grand Junction populations. Average Medicare payments were then computed for each risk group in each county (Exhibit 6). The effect on costs of accounting for this measure of illness burden is dramatic.

Exhibit 6: Annual Medicare Payments by Risk Level

Graphic for Daniel G post

Taking into account the disease combinations eliminates the apparent low cost difference across the full range of disease risk scores. If the disease levels in the McAllen population were magically made to match the Grand Junction disease distribution, but experienced McAllen-level costs, annualized Medicare payments would fall from $13,150 to $6,145.  The morbidity-adjusted per beneficiary payment rate for McAllen is 10% higher than the $5,579 Medicare per beneficiary annualized payments observed in Grand Junction, substantially less than the observed 300% payment differential seen in the unadjusted data.

Discussion and Implications

McAllen is different from many areas of the United States: it is sicker and poorer.  The observed differences in the rates of chronic disease are highest for those conditions rampant in low income American populations: diabetes and heart disease. Further, Medicare beneficiaries in McAllen have significantly higher rates of co-occurring chronic conditions. As a result the costs of caring for McAllen Medicare population appears high in comparison to other areas but not abnormally so.  McAllen suffers from a tremendous burden, but it not caused by its physicians: the care they provide leads to costs that are substantially comparable to the other counties in the article once adjustments are made for the magnitude of the health problems they face.  The disturbing pattern of physician practices uncovered by Dr. Gawande sounds a warning not because it foretells a McAllen-like future but because it portrays the on-going crisis that affects both McAllen and Grand Junction and it is national in scope.  Physician culture is only part of the McAllen story.

Patients with chronic disease, especially those with multiple conditions, are extremely costly to treat.  Cost savings will not be realized by denouncing and penalizing medical systems because they treat patient populations with high rates of disease.  Instead health care reform must develop policies that support streamlining and coordinating care for beneficiaries with multiple chronic conditions, wherever they reside. Policies that support lifetime continuity of coverage, disease prevention and early treatment, could reduce healthcare costs for populations who now reach Medicare eligibility with a history of under-service.  Physician culture has a role to play: Accountable Care Entities are intended to reduce barriers to access by facilitating care coordination. The high costs of care in places like McAllen will not be dramatically reduced by transforming physician ethics and organization if the roots of the crisis are in the interaction between class, demographics and chronic disease.


Notes:

1)  The payment amounts and beneficiary counts are from CMS claims and enrollment data that includes a 5% sample of the Medicare population.  The data is hosted by JEN Associates Incorporated of Cambridge Massachusetts, a CMS MRAD contractor.

2)  A risk score ranging from 1 to 13 was computed for each beneficiary using diagnoses found on Medicare physician and hospital claims.  Beneficiaries with scores greater than 9 are not observed in the Grand Junction 5% data in numbers sufficient for analysis.  The grouping and scoring system was developed by JEN Associates Inc. of Cambridge Massachusetts for Medicare and Medicaid program planning and evaluation applications.  Diagnoses are selected based on correlation with future hospitalization, nursing home entry and death and grouped according to a disease’s functional impact.

Daniel Gilden is a health services researcher with 20 years of hard core quant experience.He’s the President of JEN Associates which provides highly specialized analysis of Medicare and Medicaid data. He contacted THCB regarding the fuss about the  McAllen, TX “overuse” story. In his calculations the data suggests something very different from the “practice variation” theory–the patients really are sicker. As this goes counter to decades worth of work by Wennberg et al, we invited Daniel to share his data and methodology with THCB. And we invite those of you who like this kind of research but may disagree with Daniel’s analysis to respond. Finally it’s worth noting that if his conclusions are true this has huge implications for overall health care policy…Matthew Holt

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AJonathan PaulMcAllen PatientAlan McCrindleNervous and Uninsured Recent comment authors
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A
Guest
A

From Mr. Gilden’s Conclusion:”Policies that support lifetime continuity of coverage, disease prevention and early treatment, could reduce healthcare costs for populations who now reach Medicare eligibility with a history of under-service. ” Indeed, it seems logical that diseases treated earlier might be less costly to manage (and, lead to a healthier population!), and patients whose first visit with a doctor ever comes only after reaching the Medicare eligibility age have likely more untreated festering conditions. Hence, increasing access by Medicare for all and similar are definitely a good thing. (And Romneycare in MA, and the Heritage plan now called Obamacare… Read more »

Jonathan Paul
Guest

Hey,
I recently came accross your blog and have been reading along. I thought I would leave my first comment. I dont know what to say except that I have enjoyed reading. Nice blog. I will keep visiting this blog very often.
Thank you
🙂
Keep blogging

McAllen Patient
Guest
McAllen Patient

Thank you for a copy of what is a very interesting article. The McAllen Renaissance Hospital is and was created by an investment group comprised of locals, who have a real interest in health care “outcomes” for people of the Rio Grande Valley. The scenario as I saw it over the last thirty years; In 1975 came La Plaza Mall with the highest retail sales per square foot in the country. · Then came the upper class from Northern Mexico who wanted to spend more time in McAllen to make their purchases; retail and medical. · Then came the older… Read more »

Alan McCrindle
Guest

My observation is that there is some unacknowledged “circularity” in the logic underpinning this argument that it is the low income environment with consequently greater rates of chronic health problems that is driving the cost difference in McAllen. While there is evidence at the global and local level that the single most important driver for social outcomes such as physical and mental health, obesity, education, imprisonment, trust and community life – see research at http://www.equalitytrust.org.uk/ or you can read the book – The Spirit Level: Why More Equal Societies Almost Always Do Better – this raises the question – “What… Read more »

Nervous and Uninsured
Guest

Really interesting discussion. Here’s a good short article on how immigration reform might actually be the secret key to paying for universal healthcare: http://bit.ly/VkAq0

Tom Leith
Guest
Tom Leith

AJ Brazier writes: > if armed with a tax credit equal to whatever > would be spent under the auspices of a “public > option,” We can’t know in advance what would have been spent, can we? Your tax credit amounts to an algorithmic third-party rationing mechanism. It sounds here like you want medical insurance to work like old-fashioned disability policies: if you lose an eye you get $1K but if you lose both you get $10K, this kind of thing. So now we’d say if you have one artery 50% blocked you get $5k, if you have two arteries… Read more »

Happy Hospitalist
Guest

You did a fine analysis guys and gals. But I have one question, which I think would help clarify your research. You excluded the costs of DM, heart disease and heart failure and found that the expenditures per beneficiary were pretty similar. So I ask you, what is the expenditure per beneficiary across all three counties in patients with DM, heart disease and CHF. These are the diseases that create the proceduralization of America. If you can show me that the expenditures are similar across all three counties in this population in data that is adjusted for premium assistance, I… Read more »

AJ Brazier
Guest
AJ Brazier

Deron: What is the basis for competition, and how does one determine value in *any* market? The fact of the matter is that there is no single criteria that forms the basis for competition in any market, nor is there an objectively sound means of determining what constitutes “value” for all participants. Whether it was Thag weighing the trade-off’s inherent in swapping a hunk of primo mammoth flank for an ivory hair-piece with which to win the affections of the cave-lady down the way in the ancient past, or an academic stat-compiler fretting over the choice between uprgrading to this… Read more »

Deron S.
Guest

AJ – In the competitive market that you envision, what is the basis for the competition? How does one determine value?
Also, you are confident that you would be a good healthcare consumer. Are you equally confident that the rest of the masses would be?

AJ Brazier
Guest
AJ Brazier

As a consumer of healthcare, I have both the temerity and the impudence to suggest (in these lofty rhetorical environs, no-less) that I am in a better position to evaluate whether or not I am *actually* ill and – if armed with a tax credit equal to whatever would be spent under the auspices of a “public option,” a HSA account, and a high-deductible plan developed in the context of a nationally competitive market – that I would also be a far better judge of whether or not any portion of the medical care I’m offered in response to a… Read more »

Marc
Guest
Marc

How did you risk adjust? If you count diagnoses in physician/hospital claims, a place that orders more things and hospitalizes more people will have more diagnoses entered to justify tests and procedures. Did you try to different adjusters? Did you try to elimate “rule-out” claims from the physician files? This is key to your argument that McAllen has sicker people. In other words, it would be useful to know the method you use to calculate the rates in Exhibit 4.

Deron S.
Guest

Alex – Your points are very important, as we need to hear from all points of view on this. The reality is, unhealthy lifestyles are becoming the norm in our society. Anyone that thinks the rise in obesity rates and the rise in healthcare costs are unrelated is taking a naive view of things. Any healthcare reform initiative that does not adequately address prevention, wellness, and health education will fall well short of successful. The allocation of $19 billion to HIT and $1 billion to prevention in ARRA was very telling. It is a classic example of how government produces… Read more »

Jon Skinner
Guest
Jon Skinner

John Graham has raised the question: How do Medicare Advantage (HMO) enrollment rates affect the Dartmouth Atlas comparisons in the fee-for-service population? Good question. First, the concerns raised by Mr. Gilden, that HMO enrollment rates affect the average cost in a region, misses the point. The differences are trivial, and in any case are mitigated by the fact that McAllen and El Paso — the two comparison regions — differ by just 14% in their HMO enrollment. Even if HMOs in El Paso cost 25% less than in the fee-for-service population, this would bias the regional comparisons by $264 —… Read more »

Tom Leith
Guest
Tom Leith

Joe,
The definition of “necessity” is one of the unsettled points regardless of cost.
t

Alex
Guest
Alex

I’m a radiologist in McAllen. I don’t know a lot about epidemiology or statistics. But when I compare the patients I’ve seen here to other big metropolitan areas I’ve worked before, the number of positive studies I read every day is significantly higher. I have no control on what it’s ordered and why, but it doesn’t look like doctors are ordering unnecessary studies here… I wish I had a few easier cases to read to give my mind a break sometimes. I’ve seen the most cases of osteomyelitis (diabetic), arthritis, stroke, advanced cirrhosis, complex tumors/masses (late detection), just to name… Read more »