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
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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
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
Categories: Uncategorized
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 are a first step in this direction).
Hey,
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Thank you
🙂
Keep blogging
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 Winter Texan who found it hard to return to the distance colder climate for their health care needs.
· Then came the local real estate developers who supplied this market.
· Then came the local lending institutions that supplied the developers.
The 1980’s,
· Then came the need for developers to associate with the industry with the greatest cash flow at the time; doctors.
· Such doctors became very active in medicine and developed excellent skills, some returned to study business administration to better understand banking practices, and investment practices along with business practices in health care administration.
The 1990’s,
· Regional hospitals controlled the inpatient and much of the outpatient services in the region by recruiting doctors, which were place in their adjacent doctor facilities. The local Edinburg General Hospital was sold.
The 1990’s to present,
Local skilled and educated doctors looked for their own solutions to the application of technologies when investing in their real estate and their banks to better provide for the special health care needs for people of the Rio Grande Valley. Leaders emerged and banks grew. Then came culturally sensitive medical facilities, which provide “state of the art” care for people of the Rio Grande Valley.
Now doctor recruitment in the region is related to construction of large single family homes, medical malls, banking and finally an inpatient health care facility which is rapidly growing for the purpose of satisfying special health care needs of the RGV.
I know these peoples who are hard workers and proud of their most recent accomplishments in health care; fewer amputees in clinic due to diabetes, people who wear their scars after open heart surgery like tattoos, as a few examples.
Check out the ER at Renaissance.
A National Health Care system will fail in these regards; our regional health care problems are difficult to measure and almost impossible to manage. A successful delivery system will need to give special attention and funding for this area.
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 drives inequality and the resulting poverty and poorer health outcomes ?”.
A simple answer is systems, cultures, behaviours and individual mindsets that value the individual and competition over the group and co-operation lead to relative inequality.
Medicine historically fits the profile of a “self sacrificial”, group, community orientated activity – the values that drove doctors were related primarily to helping the patient maximise their health. In contrast the individualistic free market system views the patient as a revenue and profit centre to be maximised.
The original New Yorker Article made the observation that high cost medical care was correlated to doctors who valued patients as profit centres – the prevailing value system of neo-liberal free market capitalism. Low cost care and quality of care was correlated to community values.
In other words the same values system and culture etc. that has been responsible for transforming doctors and medicine into entrepreneurial profit maximisers has been responsible for the increasing inequality, diet, lifestyle and community breakdown factors that are driving the increased incidence of chronic physical and mental health. And, it is the same value system that has the whole country with a debt level, commensurate to the level of obesity, that threatens to collapse the whole system and leave masses in chronic poverty for decades.
The solution of the health problem and the sustainability of the USA requires no less than a total transformation of consciousness, values, culture, systems and behaviour that internalises previously externalised costs.
This value system will recognise a health system as a system that actually focuses on raising health through a personalised approach, where people take responsibility and action for their health and the doctor’s role is primarily one of educator and facilitator – as opposed to the current sickness model where the patient is passive and the Doctor is the expert whole doles out standardised treatments to suppress symptoms after the patient is already sick.
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
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 blocked 70% you get %25K, if your appendix bursts you get $2k, if you get diabetes you get $100K one time in a lump sum to cover any and all associated drugs, devices, surgeries, consultations and so on for the remainder of your life. Go forth, negotiate, purchase! Or not.
The upside of this sort of contract is what you said it is; it puts you in charge of what to spend on what and is simple to conceive and administer. Maybe Nate can tell us whether it is legal to write a contract like this today.
I think you overestimate the ability people have to negotiate at the point of service. If you arrive in an ED with an acute MI, will you negotiate a price? Probably not. If you are conscious, you’ll sign something saying “treat me NOW and bill me current prices!!” If you are not conscious that will be the implicit contract. This scenario by the way represents around 50% of hospital admissions.
Under a high deductible/HSA scheme you have a better chance avoiding the price negotiation problem because (presumably) you’re in a network with negotiated rates in effect even for spending below the deductible. There is a lot right with this sort of idea iff (that’s not a misspelling — it means ‘if and only if’) the HSAs are fully funded, especially for poor people.
A ‘public’ downside of this financing mechanism is that it will do little or nothing to contain the rate of medical inflation. Once you hit the deductible, you are completely price insensitive, and this is where the bulk of the spending is. The only thing I can think of that can help with this is to move the price competition to the level of the “plan” — you choose your level of protection AND you choose the wonks who will make coverage decisions. This basically is Enthoven’s idea and is pretty much what’s done in Holland and Germany.
Lastly, maybe you are smart enough to know when you need medical attention and whether the sort of attention offered is appropriate, but most people are not. You’ll have to grapple with the RAND study on this topic in order to make the case that a broad competitive market (easy entrance and exit, prices driven to marginal cost of production, Pareto efficiency, and the rest) is even possible for medical services. Personally I wish it were possible, but I don’t think it is. The best I think most of us can do is to choose our administrators.
Every bit of this is quite thoroughly (if not systematically) discussed in the archives of THCB. There are many permutations.
t
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 would believe that culture of care plays no role in McAllen. From what you’ve shown me, I’m not convinced. All you’ve shown me is that healthy people don’t cost money no matter where you go. And poor people cost more money everywhere.
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 year’s special Bono Edition(TM) MacBook Air or a year-long supply of extra strength Levitra to prop up his flagging libido in the present – all such determinations are inherently subjective and only rational and justifiable inasmuch as they satisfy the criteria used by the person making the choice. Woe to anyone who finds themselves trapped in a system where a centralized bureaucratic mechanism attempts to supplant that by means of equally arbitrary value judgments derived from a compilation of statistical aggregates and passed through the filter of third-party incentives that are at odds with the interests of their ostensible beneficiaries.
Would I be a “good” healthcare consumer? Don’t know, don’t care – unless the person making that determination is me, in which case – I’m sure I’ll do just fine. A better question might be what arrangement would best enable me to make such determinations? The same one I use with my mechanic. He tells me what he thinks is wrong, what all of my options are, and what they’ll cost. He informs, I decide. If I don’t trust his judgment or his motives, I go elsewhere. Under a high-deductible/HSA scheme, that covers the vast majority of the medical decisions that I’ll ever have to make. I’ll leave it to those enamored of comprehensive third-party payment mechanisms to argue that their centralized decision-making/funding apparatus of choice will actually outperform this model in terms of price, efficiency, and patient satisfaction.
How about everyone else and their capacity to be “good” healthcare consumers? It requires zero false humility for me to proclaim with 100% confidence that they could not possibly care less what AJ Brazier thinks about the methods they use do determine how, when, and on what they spend their health-care dollar. Anyone who would do otherwise is a fool, an idiot, even – rivaled only by those who would concede that power to a claque of well-intentioned academics and bureaucrats who have succumbed to the fatal conceit that the combination of statistical aggregates, near utopian faith in the power of centralized administrative choreography, and hubris that they possess render them uniquely fit to make such determinations on everyone else’s behalf.
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?
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 particular set of symptoms is warranted and thus worth paying for, or not.
Arguing about which algorithmic third-party rationing mechanism with incentives that are neither consistent with nor subject to the discipline of the consumer’s interests is like arguing whether life was better under Fascism or Communism. Both camps offering testimony here seem to suffer from an overlapping set of delusions in which they’ve taken for granted that entities that can impose price controls on providers can also control the underlying costs responsible for generating the ultimate prices of goods and services (like, say, the spot prices for stainless steel, flat panel displays, microchips, polyethylene tubing, etc), and that you can efficiently coordinate supply and demand by substituting a centralized bureaucratic mechanism in the place of dynamic pricing in a competitive market.
My only hope is that if, as it turns out, we’re abandoning consumer driven models entirely on the Long March towards Better Healthcare for All – someone will think to structure the centralized rationing scheme so the folks devising it will be compelled to subject their own care to its discipline. If Jon Skinner is just as likely to be turned away when his diagnosis is ambiguous and the costs of treating whatever he might have exceed the algorithmically determined benefits*…just like the rest of us…then at least the schadenfraude will be satisfactory, even if my health-care isn’t.
*To whom, exactly, one wonders.
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.
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 superficial solutions to the difficult problems.
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 — a drop in the bucket relative to the overall difference of $7441.
The real concern, unmentioned by Mr. Gilden, is that HMOs tend to enroll healthier patients, meaning that the fee-for-service patients who remain could be sicker. That Grand Junction is so inexpensive is thus all the more surprising. Indeed, research shows that having an HMO in town tends to reduce costs for everyone, a finding consistent with HMOs changing the culture of health care.
Granted, proving that McAllen is an outlier doesn’t get us any closer to fixing the U.S. health care system. But it does tell us that any health care reform needs better methods of measuring population health than commercial claims-based “risk adjusters.”
Joe,
The definition of “necessity” is one of the unsettled points regardless of cost.
t
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 a few. I’ve complied such a great number of cases in one year that I could go lecture at my training program any time and make my professors’ lectures look like a medical school Radiology 101 conference.
The rate of contrast injection cancellation due to diabetes and renal insuficiency is high. We cancel MRIs very often due to overweight patients that don’t fit in the magnet. In Florida we were doing twice as scans per MRI per day than we do here just as a comparison.
The education and cultural deficiences are serious here. When talking to my clinical colleages I’m told most patients don’t know for example the differences between carbohydrates, proteins and fat (not even mention trans fats!). Every day women show up to the hospital complaining of abdominal distension to find out they are 35 weeks pregnant.
Just to think about…
Tom, If your auto mechanic charged you 30 percent more to fix your car than was necessary (e.g. he replaced your muffler with a gold plated one instead of a regular one), would you mind or just decide that what is much higher than necessary cost to you is just his making a better living?
OK Deron, it seems that for you, “the problem” is “cost”. But one man’s cost is another man’s living, and besides that a focus on cost may well ignore benefits. Shoot, it even costs to figure out what the benefits are! Then there are a host of other considerations, chief among them competing notions of equity.
Our friend Jason The Healthcare Economist has a good summary online here:
http://healthcare-economist.com/2009/06/22/healthcare-economist-manifesto/
What he’s doing is starting with policy alternatives and looking at the problems each solves or exacerbates. He’s very open-ended and fair-minded.
t
I appreciate Mr. Gilden sharing this with us, and Dr. Skinner’s responses. However, Mr. Gilden brings up a basic accounting issue that Dr. Skinner did not address: If Medicare HMO payments are accounted differently than Medicare FFS, and Dartmouth researchers have not adjusted this, doesn’t this pose a big problem?
On the other hand, Mr. Gilden suggests that the variance is not geographic, but socio-economic. Isn’t there a whole school of thought (mostly in public-health faculties) forever complaining about “disparities of access to care” by SES? What say they to this sort of analysis? If anything, the policy response indicated by Mr. Gilden’s analysis is that people of lower SES should have their Medicare access cut back significantly!
Finally, I can see the problematic circularity in using diagnoses created by doctors to measure the appropriateness of medical intervention, but I don’t really see any way around it, unless you conduct a RCT with two “hit squads” of outside doctors randomly assigned to communities for a week and randomly giving people check ups!
“Frank, if must wear tinfoil, next time please be polite enough to bring some for everyone.”
—
You do not appear to need anything. Except, like Michael Moore, a brain that works. Way to go.
Frank, if must wear tinfoil, next time please be polite enough to bring some for everyone.
CHAS. DICKENS’ VIEW
WORST OF TIMES
“The McAllen-El Paso paradox is not about risk adjustment, it is about profit-driven health care.”
BEST OF TIMES
“This is about a local health care system optimized to maximize Medicare billing.”
AMERICAN INDIAN SAYING
“If you think the federal government can make life better, ask an American Indian.”
IMHO — Mr. Obama and his Chicago pals are fully capable of running health care, right into bankruptcy and chaos. They have the skills — BHO went to Harvard Law.
I am no statistician, but it seems that to allow the treatments to define the disease is not a very solid way to assure that the McAllen patients are sicker. Right or wrong, this study says to me that we need to redefine how we treat and try to prevent disease. If the author is actually correct, we will be anteing up 25% of GDP to pay for the chronic diseases burden that our current system does little to prevent.
Tom – I think we know what the main cost drivers are and what we need to do to address them. My personal favorite is the reallocation of RVUs from overused procedures to primary care services. It’s the perfect first step because: 1) it wouldn’t cost a dime, 2) it doesn’t reflect political ideology in any way, 3) it would help reduce overutilization, 4) it would help alleviate the primary care physician shortage, and 5) it would help us restore the all-important doctor-patient relationship to something close to what it used to be by allowing docs to spend more time with patients.
Is it even on Obama’s radar screen? If not, why? Damn lobbyists!
Maybe we should undertake an exercise to compile the best ideas from THCB readers and writers. I envision everyone submitting their thoughts on what the top three cost drivers are? Round two would be for everyone to submit solutions to those cost problems. I think it would be an interesting exercise and a nice break from the same old conversations.
Deron S. writes:
> If we consolidated the best from THCB over just
> the last 12 months, we’d have a great healthcare
> system in place by now.
waxing philosophical:
What do you mean by this? Who’s “we” and what are “the best ideas”?
Answering these questions is the whole point — it is a giant political task to come to anything resembling a consensus about what problem should be solved, much less who should solve it, or how. Oh, and “a consensus” isn’t “whatever the Congress produces”.
The American Civil War did not settle much and I think we can all see right here on THCB that it really isn’t over.
t
Here are facts worth noting.
McAllen was the seventh best performing city in the US (economically) in years 2007 and 2008 according to the Milken Institute.
The cost curves between McAllen and El Paso started diverging in 1992. Is not that when Hillarycare was being introduced? Perhaps that had a profound impact on the behavior of McAllen doctors? I commend them for keeping the HMOs out of town.
Is anyone else getting bored with hearing the same things over and over again? We just keep rehashing the same arguments repeatedly. While I enjoyed Gawande’s article, it was far from revolutionary and it certainly was not a complete picture. I hope we figure out the solutions to our woes soon, because we need to talk about something different. It’s a great illustration of why government should not be responsible for a problem of this magnitude and complexity. While they engage in zero sum politics, we all get to sit around and chat. If we consolidated the best from THCB over just the last 12 months, we’d have a great healthcare system in place by now.
I resonate with Dr. Gawande’s analysis for two reasons. The first is personal. My elderly parents got their health care in Boca Raton, FL, where the incessant ordering of unnecessary, unethical and revenue-producing interventions were painful, risky, complicating, ineffective and frustrating.
The second is professional. I work for The Permanente Medical Group (TPMG), Kaiser Permanente’s medical group in Northern California. My views are my own and don’t represent my employer.
TPMG recognizes that the sickness of the population reflects the approaches to care. We have a pre-paid, integrated system rather than the fee-for-service, fragmented model practiced in McAllen. In our financial model it is cheaper to improve the health of the population we serve rather than order unnecessary, costly interventions. Here are two examples of our successful efforts to improve the health of our patients, reduce costs and improve quality:
TPMG implemented a program to reduce the rate of death from heart disease. It is now 30% lower in our Northern California population than in the unaffiliated population in Northern California. To do this we defined the core patients to have one of more of the following disease states: diabetes, coronary artery disease, stroke, peripheral vascular disease, aortic abdominal aneurysm and/or chronic kidney disease. The program ensures that the highest risk patients (those with coronary artery disease (CAD) or certain other vascular diseases) receive recommended medications and aggressive risk factor management to help slow the atherosclerotic process and prevent future cardiac and cerebral vascular events.
Second, we now have a 9% rate of smoking among our 3.2 million patients, compared to the rest of Northern Californians, where the rate is over 15%. If you look back a decade or so, the two rates were almost the same. Lowering the smoking rate brings down the cost of care of ill health created or exacerbated by smoking.
We did not recruit non-smokers, instead we changed behavior. That is what happens with the right culture and incentives.
If Nate’s assertion that, “Medicare and Medicaid have 10% fraud rates” how would that affect billing levels in McAllen, given their higher Medicare/Medicaid rates. And how much would that skew the numbers in addition the the over billing/treatment?
One additional lagniappe: The 2008 Dartmouth Atlas (John E. Wennberg, lead author) compiled treatment patterns for people in their last 2 years of life. These data are available on the web; the Texas report is at http://www.dartmouthatlas.org/data/download/perf_reports/TX_HOSP_perfrpt.pdf
The great thing about these data is that they provide information about individual hospitals. For example, we find out that in El Paso, patients treated at the Del Sol Medical Center accounted for $1,219 in ambulance expenses. This is averaged across all patients in the sample, and not just those who required ambulance rides. This was the most expensive hospital; the others were closer to the national average of about $775.
Now let’s look at the same ambulance expenses for McAllen hospitals: $5,199 for the Mission Regional Medical Center, $4,576 at the McAllen Medical Center, and $2,404 at the Rio Grande Regional Hospital. This is not about risk adjustment and sicker patients or longer distances to travel (many patients in El Paso come from New Mexico). Nor is it about immigrants (who are not included in the dataset) or about snowbirds (whose spending is largely allocated to their home states). This is about a local health care system optimized to maximize Medicare billing.
In the beginning of my above post, I referred to Mr. Gilden’s last sentence.
I have to wholeheartedly agree with the last sentence, based on my (rather rich) anecdotal experience.
Utilization varies widely from group to group, hospital and hospital, and even within these structures, from provider to provider. However, I could imagine that McAllen is an outlier … but one finds similar incentive structures and associated problems nationwide.
While market based solutions could be part of the solution and seem to be favoured by many experts I am currently reading up on this), I can only emphasize that overutilization is a culture phenomenon, both physician- and general (or: patient-) culture.
Rarely, in my experience, is cost effectiveness taught in residency; a resident gets rarely, if ever, criticized for ordering a superfluous (noninvasive) test; but he/she will get praised for testing for highly unlikely diagnoses and criticized for the opposite.
And, more importantly, while in actual practice: THERE IS CURRENTLY NO INCENTIVE TO PRACTICE EFFICIENTLY, BUT THERE ARE MULTIPLE INCENTIVES BEING WASTEFUL (i.e. financial incentives, patient satisfaction and the litigational threat/so called “tort signal).
A disclaimer: I’ve worked with the Dartmouth Atlas group for many years. For those who believe in the rationality of the US health care system, I can understand how difficult it is to digest the finding that Medicare enrollees in McAllen account for twice as much spending per capita as those in El Paso, even after adjusting for differences in age, sex, and race. By “adjusting” for illness, Mr. Gilden appears to make the undigested bit of potato go away.
Unfortunately, as many of the readers have already pointed out, the “adjustment” mechanism used by Mr. Gilden depends on what doctors do. Physician in McAllen need to diagnose an illness to bill Medicare for its treatment. Nor are Mr. Gilden’s later arguments persuasive — doctors are likely to both overdiagnosis and overtreat given a specific diagnosis.
So then what can one use to measure underlying illness? One approach is to look for diseases where there is little or no discretion in how it’s diagnosed. Hip fractures are a good example – nearly every person with a hip fracture ends up in the hospital, and no competent physician would diagnosis something else as a hip fracture. According to the Dartmouth Atlas data (www.dartmouthatlas.org), age-sex-race adjusted hip fracture rates are 7.8 in El Paso, and only 6.3 in McAllen. So here McAllen looks healthier.
When we look at mortality rates for cardiovascular disease from 2004 Texas data, they are slightly lower in McAllen (Hildago County), 235 per 100,000, than in El Paso, 252 per 100,000, and both are below the state average of 299. Cancer deaths in McAllen are lower (131 versus 162). Anyone who tries to argue that cardiovascular deaths in McAllen are lower because they spend so much on health care gets an automatic D-.
The most interesting part of the story has been ignored so far. In 1992, Medicare expenditures in the two regions were nearly identical. So what caused McAllen spending to triple during 1992-2006? Not disease – the cardiovascular mortality rate grew at about the same rate in McAllen as in El Paso. One cannot explain the divergence over time by appealing to changes in reliable measures of health status.
The McAllen-El Paso paradox is not about risk adjustment, it is about profit-driven health care.
The discussion of the validity of using diagnoses from Medicare claims as a proxy for illness is involved. Having substantiation of age adjusted disease rates is an important component of a fully developed argument. One point I would make is that if McAllen is over-diagnosed and therefore only presents as ‘sicker’, and in fact, costs are driven by over-treatment then I would expect two contrasting measures: 1) the population costs more on average overall; 2) the cost per treating a diabetic (for example) in McAllen should be lower than in comparison to counties with more accurate reporting of disease. Even with excessive physician visits and testing, a false-positive McAllen diabetic would be cheaper to care for than a true-positive Grand Junction diabetic. The other point I would make is the score adjustment for disease worked well across all levels. I would expect that over diagnosis would lead to McAllen appearing less expensive by level if the diagnostic score was based on misrepresentation. The argument that over diagnosis leads to over treatment is interesting as it relates to physician care – less so for acute care. I certainly would not expect the level of agreement between the different counties to be perfectly balanced by a combination of over diagnosis and over treatment. The effect of the diabetes-heart disease edit is also informative in understanding if there is general over diagnosis and over treatment since one would expect a cost differential that was driven by more than these two conditions.
The inpatient episode payments per beneficiary drive the payment analysis. The episode rates are high in McAllen – but so are the average days per episode. If the hospital numbers were being gamed –people who are less sick than in other areas are being admitted – then I would expect a shorter LOS for equivalent payments. If the admission rate is at an expected level after taking into account higher patient morbidity then the McAllen costs are not excessive.
I do believe that the interaction of diabetes and heart disease explains much of the difference that is reported. I do not want to make this argument to obscure the value of Gawande’s work – I think he is more right than he knows. I do not disagree with the need for a very thorough review of the incentive structures that physicians, hospitals and home health agencies are subject to (and creatively react against). Cost containment efforts for different provider types frequently work at cross-purposes and are in many cases counter-productive. I am concerned that the McAllen argument leads to a false conclusion that overly focuses on bad actors in specific locales as opposed to structural faults that are pervasive.
Education is positively correlated with health. Lower levels of educational attainment, lack of HS graduation for example could also indicate lower level of health status thus potential higher costs. So it should be easy to compare educational attainment of people over 65 for these areas.
WHY IS V’BILITY ALWAYS FORGOTTEN
Finally! Someone with the cojones to point out that communities — even those nearby — can be radically different in physical make-up.
Yes, there is physician culture. Yes, there is self-dealing (look at Chicago politics, Democrat investment bankers).
But statistically-crude comparisons between populations do NOT help.
Nor does ignoring the too many promises made to too many people, just to get elected. Look how fiscally conservative Europe and Asia have become — they can see the financial problems ahead.
And what about the role of self-responsibility? Why do the healthy have to financially subsidize smokers, alcoholics, drug addicts, and fatties?
Finally — someone who sees the obvious. Do not let Obama-bots bury him.
don’t forget accountable care patients (you know – patients accountable for maintaining or improving their health!)
Here are some additional facts, not influenced by physician or hospital claims data:
a. The McAllen MSA is the poorest in the nation. Per-capita income in the McAllen MSA is $18,316, less than half the national average. Per-capita income in El Paso is well below the national average but still 45 percent greater than in McAllen. Per-capita income in McAllen is 44 percent less than in Grand Junction.
b. The poverty rate in McAllen is 34 percent, nearly triple the national average of 13 percent. The poverty rate in El Paso is well above the national average but still 18 percent lower than in McAllen. The poverty rate in McAllen is nearly three times what it is in Grand Junction.
c. At 116 physicians per 100,000 population, the McAllen area has the lowest rate in the entire country and 43 percent fewer physicians than the U.S. average. The number of physicians per 100,000 residents in El Paso is well below the national average but still 24 percent higher than in McAllen. Grand Junction has twice as many physicians per 100,000 population as McAllen. (When there is poor availability of routine ambulatory care, patients are far more likely to get their outpatient care in hospital emergency rooms, where costs are high and diagnostic testing is more frequent, and they are far more likely to have costly hospital admissions.)
tim,
of course the relationship is nonlinear. The question is whether a (purportedly) increased burden of disease justifies exponential increases in spending.
Not to pile on, but after years of combing through claims data for these kinds of populations, it is in fact a garbage-in, garbage-out proposition. Just as treatments in non-acute situations (i.e. something other than acute MI or a car accident) can often be a factor of subjective clinical judgments, so can chronic disease diagnoses.
That said, if I read the above piece correctly — the author ends up in the same place as Gawande. Either way you slice it, Accountable Care Organizations look like an interesting mechanism for containing Medicare spending.
A common criticism of Gilden’s analysis is his use of chronic disease rates derived by claims and the potential endogeneity of physician behavior to the appearance of chronic disease in claims. To validate Gilden’s rates of disease, I queried data on cardiovascular disease, arthritis, and diabetes in Texas, McCallen, and El Paso for the population 65 and over in 2007 (McCallen data was not available before 2007):
Rates of Chronic Disease Age 65 + in Texas,2007
Texas McAllen El Paso
Cardiovascular disease 25.3 26.9 14.9
Arthritis 54.6 53.2 46.8
Diabetes 23.2 29.2 25.2
The Texas DHHS data indicates that rates of arthritis are higher than those reported by Gilden while rates of diabetes are substantially lower than those reported by Gilden. Comparing arthritis and diabetes rates between McAllen and El Paso, the DHHS data indicates that diabetes rates are 15.9% higher in McAllen (27.9% higher according to Gilden) while arthritis rates are 13.7% higher in McAllen (40% higher according to Gilden). According to the DHHS data, rates of cardiovascular disease appear to be 80.9% higher in McAllen relative to El Paso: while cardiovascular disease is not specifically classified in the Gilden analysis, his analysis indicates much higher rates of Ischemic heart disease, heart failure, and cerebro-vascular disease.
The Texas DHHS data, relying on self-reported diagnosis of various conditions, may also be endogenous to physician behavior, which may result in inflated rates of chronic disease diagnoses in McAllen relative to El Paso. Nonetheless, the Texas DHHS data does appear to support Gilden’s assertion that McAllen Medicare beneficiaries are sicker than those in El Paso, although the Gilden analysis may overstate the magnitude of the difference.
Interestingly,this article actually proves Gawande is more right than he knows…adds more… disagreeing–physician are not only the bad actors driving the problem — shows…actually, its multi layer, structural across providers and endemic…
Twice the rate of arthritis, Parkinson’s, and dementia in McAllen as in Grand Junction (Exhibit 4) – hmmmm?
The rationale so commonly used in health care that, ‘my patients are sicker than yours,’ is fraught with problems. Proof requires comprehensive data analysis, not just claims data and not restricted data such as Medicare. What are the rates of utilization across all patients and across all payors in these communities and what is the true clinical data to back up specific diagnoses?
If there are practicing physicians out there who don’t think that our over utilization contributes at least x___ percent to excess health care costs, please raise your hand. One of our Physician Assistants said it perfectly the other day, ‘Just ask me, I’ll show you how to save a million dollars a year in this department alone.’ Sadly, no one is asking. This isn’t about claims data, this is about fixing the skewed incentives and wide spread inefficiencies in health care. Everyone is talking broad strokes – our PA is looking correctly at the nuts and bolts.
I have learned a lot from the above discussion and one lesson that sticks on the refrigerator door is that even medical informatics (compared to pure financials) also assumes a normalized physician culture which by my 40+ years in the industry is just not the case. There are those that treat the need, others treat for the greed. It is always an 80/20 proposition.
Additionally I would like to point out that our use of “practice norms” for service unit price and # of units is highly inflated compared to the 40+ better performing countries because of the rapid diffusion of medically unnecessary technology in all practice venues (Imaging, diagnostics, pharma, etc) by both the physician culture and encouraged by expectations of the public (patients).
Physicians who own (remember 80/20) an “income enhancing ancillary” consistently lower their own threshold of medical necessity for referral. It just is. Statistics proving the otherwise are flawed.
McAllen has rates of home care several times the national average (noted in the article). However, it also has some of the lowest hospice rates in the nation and very high Hispital Care Intesity scores.
http://cecsweb.dartmouth.edu/atlas08/datatools/bench.php?comparestateids=&compareids=45086%2045175%2045265&benchids=99999&benchstateids=&geotype=STD_HSA&method=1&year=2006&evtlist1=HHAPAB_REI%20&evtnum1=1&evtlist2=&evtnum2=0&evtlist3=&evtnum3=0
http://cecsweb.dartmouth.edu/atlas08/datatools/datatb.php?&stateids=45&geoids=45175%2099999&geotype=STD_HSA&year=2006&evtlist1=HSP_REI%20&evtnum1=1&evtlist2=&evtnum2=0&evtlist3=&evtnum3=0
http://cecsweb.dartmouth.edu/atlas08/datatools/hci_s2.php?state_id=45
There is no good way to normalize these numbers. They are outliers any way one may slice it.
“It does seem that McAllen has an older and somewhat poorer population. But you have not shown that it is twice as old and twice as poor.”
“Twice as old”? Really?
I’d assume there is a non-linear relationship between age and disease.
This debate will continue. On one side are those of us for whom Gawandes accounting of the way the health “system” works just resonates – as with Jeff’s post. On the other side are those who believe that “my patients are sicker” and we are just trying to beat up on the poor doctors. Statistics can be used to support both sides. But because of the complexity of health care and the vagaries of the data – especially determining cause/effect with claims data – there is no clear answer. I happen to fall with the first group, in part because of what I have observed, and in part because I have followed the Dartmouth data for so long.
If we could assume that both sides are right – that there is unwarranted variation and that population health does play a large role, then perhaps we could actually address both reasons in terms of potential solutions. I suspect if we did that we might actually find that the solutions are the same.
Using hospital and physician claims to estimate disease prevalence is really problematic in this situation.
For example, is there really more “diabetes” in McAllen? Maybe, but maybe the coders/physicians are counting everyone who has ever had a (nonfasting) blood sugar over 99 mg/dL as “diabetic” because a greater disease burden justifies a greater level of services and intervention.
It does seem that McAllen has an older and somewhat poorer population. But you have not shown that it is twice as old and twice as poor. That’s what’s hard to swallow. Gawande would not have been able to write a story about a town that spent 24% more or even 30% more than its neighbor.
So the refutation to this analysis is that the health profiles of the three counties are actually the same, it’s just that the doctors in McAllen are diagnosing things (perhaps fiction) that are not being diagnosed in Colorado? And we know this…as an article of faith?
Arun nailed it. I completely buy the adjustment for SES, which is not directly endogenous to physician behavior. But claims-determined comorbidities are absolutely endogenous to physician behavior.
Therefore, if you’re trying to “adjust” physician behavior using a quantity that is a result of physician behavior, you shouldn’t be surprised if unadjusted differences vanish. You’ve basically just adjusted for the outcome of interest.
Put another way, would the same patient “diagnosed” with diabetes based on claims data in McAllen also be “diagnosed” with diabetes in Grand Junction? This is an open question, especially since most claims-based algorithms for diagnosing diabetes include “rule-out” diagnoses reported by doctors (see E-patient Dave’s post on importing his claims-based health records for how this happens) as well as tests such as hemoglobin A1c…which I can certainly order on any patient I please, regardless of whether he or she actually has diabetes.
If somebody did a formal study examining geographic variation in the relationship between true comorbidities and claims-based comorbidities, it would be very interesting to know the result.
i guess the bottom line is that healthcare ‘reform’ needs to take place at all levels. But it doesn’t seem like there is much ‘re-forming’ being done, is there? Especially when much of the talk is about costs, costs, and more costs. When will we discuss healthcare because of health, and not money?
wow don’t dare attack the ideology. Statistical studies showing it’s all the doctors fault, we need reform, etc etc get published in the New Yorker and spread to the ends of the earth, another study countering there might be more to it then just provider practices gets bashed for being near sited? If the first study had accounted for any of the work Mr. Gilden had done then his response would not have been needed. What point was missed the purpose of this study was to show their might be other factors. It was the narrow, and possibly ideological, New Yorker essay that missed the point. In their rush to make a specific point they over looked numerous other potential points. To address one of those is in no means missing the point.
I strongly doubt Jeff or Healthcare Guru would have complained about the point if Mr. Gilden’s analysis had supported the New Yorker and shown no difference in health or financial status.
Thanks for the post. It approaches the issue with a critical eye, which is refreshing.
Unfortunately, there is at least one major hole. Because doctors in McAllen perform more tests they’re likely to identify a greater burden of disease. If I screened everyone in my practice for diabetes, for example, the number of patients with diabetes and pre-diabetes would likely go up dramatically. If I referred every patient of mine with chest pain for coronary catheterization the number of patients with ischemic heart disease would sky rocket.
As a result we’re left with a chicken or egg conundrum, which will be hard to crack. Are increased costs truly due to sicker patients? Or are they the result of inappropriate testing, which will inevitably identify illness, even when it’s not clinically relevant?
The real question, then, is whether folks in McAllen are any better off for all our spending. I think the folks at Dartmouth have shown nicely that the answer to that is no.
Oh, and those same statistics can “prove” that defensive medicine does not exist and does not cost money.
Sometimes it’s like the guy fixing your car – he can’t make a definitive diagnosis, so he replaces parts to see what works. We may need a similar approach to health care reform, rather than keep on fiddling in Rome.
One can use statistics to prove anything; that is one reason why comparative effectiveness research will not be the panacea some think it is, either. However, I do not need statistics nor even MacAllen, Texas to know that physician entrepreneurship has exploded – I saw it in my own practice group (which is one reason I left the group) and in the practices of the physicians around me. This post is a classic case of Nero fiddling while Rome burns.
The articles provides lots of data. But agree with Jeff, misses the point. No need to repeat the above points; just another thought. How do we know that the sickness level is not artificial?
rgds
ravi
blogs.biproinc.com/healthcare
http://www.biproinc.com
As someone who has consulted nationally in perhaps forty healthcare markets, and conducted Atul-like interviews with literally thousands of physicians, this analysis is a classic case of missing the point. What would McAllen’s costs have been without the physician owned hospital with the marble lobby and gilt edged procedure suites, without the physician owned MR and PET scanners, etc.?
Physician communities differ substantially not only in the amount of clinical “opportunities” afforded by a sick population but also by the rapacity with which those opportunities are monetized. Let’s perform the same analysis for, say, Broward County, Florida, or Las Vegas, or Baton Rouge, Louisiana, or Los Angeles’ San Fernando Valley where there are far fewer poor people and see what the numbers show. Physician culture is a very important part of the story. Our learned health services researcher needs to cast his nets a little wider. We’re waiting for the real story. . .
As a social scientist, I can also tell you that poor people are more likely than wealthy people to accept what their physician tells them they need as gospel.
The physicians in places with large number of sick and uneducated people have a remarkable opportunity to “mine” their patients. That’s what Atul was writing about. It is not clear that little delegations of “accountable” doctors are going to change the rapacious behavior of their colleagues. That is why we have a legal system, and fraud and abuse laws.