http://www.springerlink.com/content/d647854766vt4688/fulltext.pdf

The test of our progress is not whether we add more to the abundance of those who have much.  It is whether we provide enough for those who have too little.   Franklin D. Roosevelt, 1937  

ABSTRACT   Geographic variation has been of interest to both health planners and social epidemiologists. However, while the major focus of interest of planners has been on variation in health care spending, social epidemiologists have focused on health; and while social epidemiologists have observed strong associations between poor health and poverty, planners have concluded that income is not an important determinant of variation in spending. These different conclusions stem, at least in part, from differences in approach. Health planners have generally studied variation among large regions, such as states, counties, or hospital referral regions (HRRs), while epidemiologists have tended to study local areas, such as ZIP codes and census tracts.

To better understand the basis for geographic variation in hospital utilization, we drew upon both approaches. Counties and HRRs were disaggregated into their constituent ZIP codes and census tracts and examined the interrelationships between income, disability, and hospital utilization that were examined at both the regional and local levels, using statistical and geomapping tools.

Our studies centered on the Milwaukee and Los Angeles HRRs, where per capita health care utilization has been greater than elsewhere in their states. We compared Milwaukee to other HRRs in Wisconsin and Los Angeles to the other populous counties of California and to a region in California of comparable size and diversity, stretching from San Francisco to Sacramento (termed “San-Framento”).

When studied at the ZIP code level, we found steep, curvilinear relationships between lower income and both increased hospital utilization and increasing percentages of individuals reporting disabilities. These associations were also evident on geomaps. They were strongest among populations of working-age adults but weaker among seniors, for whom income proved to be a poor proxy for poverty and whose residential locations deviated from the major underlying income patterns.

Among working-age adults, virtually all of the excess utilization in Milwaukee was attributable to very high utilization in Milwaukee’s segregated “poverty corridor.” Similarly, the greater rate of hospital use in Los Angeles than in San-Framento could be explained by proportionately more low-income ZIP codes in Los Angeles and fewer in San-Framento. Indeed, when only high-income ZIP codes were assessed, there was little variation in hospital utilization among California’s 18 most populous counties. We estimated that had utilization within each region been at the rate of its high-income ZIP codes, overall utilization would have been 35 % less among working-age adults and 20 % less among seniors.

These studies reveal the importance of disaggregating large geographic units into their constituent ZIP codes in order to understand variation in health care utilization among them. They demonstrate the strong association between low ZIP code income and both higher percentages of disability and greater hospital utilization. And they suggest that, given the large contribution of the poorest neighborhoods to aggregate utilization, it will be difficult to curb the growth of health care spending without addressing the underlying social determinants of health.

 So how is it doing? The clinic has installed electronic medical records, offers care coordination and documents its “quality standards.” But with three physicians, two PAs and 20 other staff to care for 6,300 patients, it’s going broke. And that’s with extra support from a foundation that got it up and running, extra fees from patients to cover the overhead (“concierge lite”), which of course poor people couldn’t afford anyway, and extra income from sales from dietary supplements (“but only those backed by evidence”).

We have a crisis in America. There are too few physicians to provide all that is needed and too little money to pay for it. And this can’t be solved by excluding poor people from the system. 

We trust primary care physicians to care for us. Why not end this Medical Home experiment and trust them to innovate.

Most readers will recognize that this is not a new story. It was THE story during health care reform. Enthusiasm surrounding it led to provisions in the law supporting the creation of new structures, such as medical homes, accountable care organizations (ACOs) and value-based purchasing, which experts believe will reduce spending. Doctors will be paid for better outcomes, and hospitals will be penalized for excessive readmissions. Several private insurers have joined in adopting these strategies.

The Grand Junction story first emerged in a New Yorker article by Atul Gawande in 2009. Soon thereafter, President Obama paid a visit, and with roaring enthusiasm declared, “Hello, Grand Junction! You know that lowering costs is possible if you put in place smarter incentives; now you are getting better results while wasting less money.” The President thought he had found the gold to pay for reform. But it was fools gold. Quality efforts can take the edge off of costs, but the real cost-driver is the severity of illness, and that’s determined mainly by patients’ income and education. Poor people are sicker, and they cost more, especially when they live in ghettos full of other poor people who see no way out and whose children grow up never finding an exit.

Low-costs are not unique to Grand Junction. Costs are low in rural areas across the entire northern tier, a vast expanse that covers one-third of the nation but includes only 6% of the population and less than 1% of the black population. Poverty exists in this region, but except for a few Indian reservations, there are no poverty ghettos. So how does Grand Junction stack up against other communities in this region? It’s about average. And when adjustments are made for the severity of illness, costs in Grand Junction are very similar to those in poor communities in the Deep South.

I have cared for poor patients since I was an intern at the Boston City Hospital 50 years ago. But it was not until I was a medical dean in Milwaukee 30 years later that I studied poverty systematically. Two characteristics of Milwaukee drew me to the problem. First was its high degree of racial and economic segregation, which confines most who are poor, black or Latino to a narrow “poverty corridor.” And second was its high health care utilization, higher than elsewhere in the region and 30% higher than in Grand Junction. In trying to understand why, it became clear that the “poverty corridor” accounted for the difference. Without it, Milwaukee was like other communities in the region, including Grand Junction. Poverty made all of the difference.

Manhattan has proved to be much more complicated but no different. Its health care utilization is almost 50% greater in than in Grand Junction, but it is three times as great in Harlem, and without Harlem, Manhattan and Grand Junction are almost identical. As in Milwaukee, poverty made all of the difference. In fact, utilization is even lower than in Grand Junction in the largely-affluent area along Central Park and south to Greenwich Village. So, if the President wants a model for the nation, here it is. But, of course, that’s ridiculous. The reason for low utilization in there has nothing to do with care coordination and everything to due with the absence of poverty.

Nonetheless, viewers who watch the “Good News” story should be impressed that systems with better coordinated care are better and probably cheaper, possibly by as much as 10%, although a recent report from the Congressional Budget Office pegs that number lower. But the untold story is even more important. It’s that poverty, which is uncommon in Grand Junction, is a major breeding ground for poor health, and that poverty ghettos, like those in Milwaukee’s inner city and in Harlem, are cauldrons of high health care spending.

Unfortunately, providers and insurers know this already – they always have. They know that the poorest patients have the poorest outcomes and the most readmissions and that these patients cost double or triple. So the best way to save money and boost performance is to avoid caring for them. That’s what providers do when they relocate to the suburbs or create barriers to access or simply close their doors.

So the untold story is that there are immense social and economic consequences associated with the high health care costs of poverty. Addressing them will be painfully difficult, all the more so if they are not acknowledged and discussed. Solutions will require changes both within the health care system and in the social infrastructure beyond. But most of all, it will demand attention to the root causes of poverty. That’s why the untold story must be told.

The Affordable Care Act was based on homogeneity. Not only would its provisions be disseminated equally, but smoothing the peaks and valleys of health care utilization would liberate the funds necessary to finance it. Under reform, Newark would come to resemble Grand Junction CO, and Mayo would be the model for Manhattan. No longer would Los Angeles, home to the nation’s largest concentration of poverty, consume more resources than Green BayWI, where poverty is infrequent. Regional variation in income and poverty could be ignored all together. The problem is “practice variation,” and health care reform will fix that.

Of course, the US  is not homogeneous, and poverty cannot be ignored. In fact, the principal cause of geographic variation in health care utilization is geographic variation in poverty. And now the hilly terrain of health care is coming more sharply into focus.  Over the course of a few short days, from December 15^th to 18th, that message sprung from three separate sources.

First was an observation in the New England Journal by David Blumenthal, the most qualified member of the Obama health care team and the first director of its health information effort. Dr. Blumenthal noted that “good legislation does not guarantee successful implementation. Never before had a country as large, complex, politically decentralized and diverse as theUnited Statesattempted to create a nationwide electronic health information system.” The nation is too varied.

On the same day, the Wyden-Ryan plan for Medicare was announced. While defined contribution plans, including this one, have the potential to skew benefits away from the poor, a Wall Street Journal editorial endorsing it correctly noted that one of its benefits is that “it relies on local information and adjusts with the behavioral and organizational responses that will vary from region to region.”

And the very next day, HHS Secretary Sebelius announced that the Obama administration would no longer insist on defining a single uniform set of essential health benefits for the nation because “coverage that works inFloridamay not work inNebraska.” The New York Times observed that “the move would allow significant variations in benefits from state to state.

The consistent message is that there is a great deal of geographic variation in America. Its hilly terrain includes peaks and valleys of costs, outcomes, preferences, poverty and needs. Reforming health care in an imagined nation of sameness must give way to reforms for an economically and demographically varied nation, and real solutions must be sought not only within the system but within the structure of the terrain in which our patients live.

It is true. The ACA does blame “ill-incentivized health care” for excess readmissions, ignoring the reality that readmissions are most strongly associated with poverty (an ill-advised social condition). Misidentifying causal factors leads to faulty conclusions, and faulty conclusions breed faulty regulations and payment incentives. And so it is in the ACA. Thanks to Kocher and Adashi for illuminating this outrage.

This notion may seem shocking, since it is generally believed that low-income patients receive less health care. After all, many have little or no health insurance, and most have poor access to primary care. Isn’t it the wealthy whose access is best and who use the most? The answer is yes to the first, but no to the second. Access is better for the wealthy, but they use less because they need less. They have better underlying health, and they have social environments that are more conducive to attaining and sustaining health. It is the poor whose health status is poorest and whose needs are greatest.

That doesn’t mean that the care they receive is always efficient, timely or convenient. Nor that it is as effective as the care received by more affluent patients. Inequality exists throughout. But the principal inequality is in their underlying health status. It is worse among the poor, and only some of the difference can be narrowed, even with the best care.

The reasons are well known. They begin in early childhood with poor nutrition, inadequate education and unhealthy behaviors, often accompanied by physical and emotional abuse. The impact of these early experiences often persists into adult life, where the web of causation expands to include inadequate housing and transportation, poor access to proper foods and weak family and social support systems. Their effects become magnified in dense urban environments, with their complexities, segregation, discrimination and threats to personal safety, and further compounded by chronic unemployment.

It is not surprising, therefore, that the poor have more disease and disability, both physical and mental. Nor should it be surprising that, as a result, they have more and longer hospital admissions, more readmissions, more out-patient visits and higher health care spending. Yet this added care is still not commensurate with their greater burden of illness, and despite it, the gap in life expectancy between poor and rich continues to widen.

One reason many believe that low-income patients receive less rather than more care is that they did receive less forty years ago, both in the US and Britain. It was not until the late 1980s that parity was reached, and health care spending among low-income patients has grown disproportionately ever since. Among Medicare enrollees, the poorest one-fifth now use about 30% more than the richest. This difference is even greater among working-age adults. At the extremes, health care utilization in urban poverty ghettos is more than double the rate of affluent suburbs. Indeed, if utilization throughout such regions were at the levels of their wealthiest enclaves, overall spending would be 25-30% less. This decrement is similar to Sir Michael Marmot’s estimate that about one-third of health care spending in England can be attributed to income-inequality.

Unfortunately, some policy-makers have misinterpreted the increaseutilization by the poor as wasteful care in regions that use more, and this has led to policies that disproportionately penalize providers who disproportionately care for the poor. The reality is that income inequality leads to high health care spending and that this draw on resources is unsustainable, all the more so as poverty rates continue to rise.

Not all who are demonstrating on Wall Street may have specific recommendations, but the message that I get from them is that a more equitable America would work better. That certainly is true for health care. Costs are higher and outcomes poorer in countries where income inequality is greater, and the US is #1. This is not to say that our system doesn’t have other problems, from over-regulation to over-utilization, nor that better ways to care for the poor cannot be found. What it does say is that, no matter what else is done, the US will not be able to afford the high health care costs of income inequality and that the only durable solutions are to deal with its root causes.

First, using the conventional approach to measuring physician supply (AMA Masterfile), they  counted the number of primary care physicians and found no significant correlation with either Medicare spending or mortality. This directly contradicts earlier claims by Shi & Starfield that areas with more primary care physicians have lower mortality and by Baicker & Chandra that areas with more primary care physicians have lower Medicare spending, both of which are widely quoted. But we now know that neither is true. In fact, they never were.

Like the current study, Shi & Starfield had also failed to find a correlation between mortality and the total supply of primary care physicians, both family practice (FP) and general internal medicine (GIM). The correlation they found was only with FPs, although they called it “primary care.” However, as I’ve explained, this correlation exists because FP training programs (and therefore FPs) are more prevalent in the upper-Midwest, where minorities are sparse, poverty ghettos are rare and mortality rates are low. FP supply has nothing to do with it, and we now know that primary care supply doesn’t correlate with mortality. It never did. Ouch!

The same for Baicker & Chandra’s claim that areas with more primary care physicians have lower adjusted Medicare spending – about 30-40% lower. The current study shows that this isn’t true. In fact, it never really was. Baicker & Chandra’s claim was based on a statistical shell game that I exposed in Health Affairs. They responded that I was wrong, and Susan-the-Editor (and Dartmouth board member) responded with feminine furry, but it turns out that I was right. As the current Dartmouth study shows, areas with more primary care physicians do not have lower adjusted Medicare spending. Ouch again!

Now for the big story. In addition to using the AMA Masterfile, the Dartmouth team counted primary care physicians a new way. They measured how many primary care services were billed and then converted services into the number of FTE physicians that would, if working full-time, be able to supply them. But forget about the conversion. Stick with the measure. It’s a good measure. It measures services per beneficiary. The Dartmouth team found that areas with more primary care services also had more total clinical services (primary care plus specialty care), and these areas also had more Medicare spending. It is areas like these that the Dartmouth group previously called “high spending areas,” where patients were no sicker and didn’t get any better despite all of that added spending. This gave rise to the mantra about the unwarranted use of supply sensitive service needlessly consuming 30% of the health care budget. But the current study found that patients in the high-spending areas were sicker. And despite being sicker, their mortality was lower. Mortality was lower in areas with more physician services and more Medicare spending. More was more. OUCH!

That’s the exact opposite of Elliott Fisher’s conclusion that more care is associated with higher mortality. According to Fisher and colleagues, this added care is not only wasteful. It’s dangerous. Only a few years ago, David Goodman (senior author of the current study) said, ”more physicians will make health care worse.” And Susan-the-Editor said ”the greater the amount of health care you provide, the more likely it is to kill you,” somewhat awkward syntax but quite damning. And now the Dartmouth team has shown that more health care is associated with lower mortality. Ouch, ouch and ouch again. Three strikes and you’re out.

So how did the new paper spin these observations? It concluded that “a higher level of primary care physician workforce was generally associated with favorable patient outcomes.”  Therefore, medical homes, train more, pay more, bla, bla, bla. But the workforce wasn’t measured. All that was measured was primary care services. And primary  care services where greater where specialty services were greater, and these areas had more Medicare spending. The real conclusion is not about primary care. It’s about medical care. Medicare beneficiaries who received more medical care had better outcomes, even when they are sicker. MORE was MORE.

In publishingcthe same conclusion two years ago, I said ”let the simple truth that health care quality is better in states with more physicians, both primary care and specialists, sweep away the myths and permit greater clarity as planners work to solve the crisis in physician supply that now confronts the nation.” Possibly this latest study from Dartmouth will allow us to do just that.

The full report is available online. The brief summary below, which quotes from it, attempts to capture its major themes.

Geographic Variation in Health Care: Changing Policy Directions     by Jill Bernstein, James D. Reschovsky and Chapin White

As the debate in Congress about health care reform began in late 2008, the Congressional Budget Office (CBO) highlighted work from the Dartmouth Atlas project, which estimated Medicare spending would fall by close to 30 percent if spending in higher-cost areas of the country were somehow reduced to the level of low-cost areas. In policy circles, the idea took hold that modifying payment policies in high-cost areas could reduce unwarranted, inefficient spending. 

Some sources of geographic varia­tion in health spending are warranted, such as input price and the burden of illness. Moreover, if higher spending produced higher quality, it might be warrant­ed, while ineffective or inappropriate treatments are not warranted. Over time, as research methods have improved, less geo­graphic variation in health care appears to be unexplained, and there is no sound way to attribute the remaining, unexplained variation to any particular cause.

Dartmouth researchers have associated the unexplained portion of geographic variation with the supply of specialist physicians or hospitals, potentially leading to incorrect inferences about the causes of geographic variation—so-called supplier-induced demand. However, recent studies indicate that health sta­tus is a more important factor driving variation in spending than previously believed and that demographic and economic factors, as well as the structure of local health care markets, shape patient preferences and provider practice styles in far more complex ways than early analyses suggested. High spending might reflect inadequately measured health status or some other factor, such as poverty.

Growing evidence suggests that failing to adequately address these complexities may overstate both the extent and implications of geographic variation in health care spending and use.

Some policymakers have used the Dartmouth work to assert that “more is not better.” However, a growing body of research supports the opposite conclu­sion. For example, several recent studies found that patients admitted to higher-intensity, costlier hospitals had better inpatient and post-discharge survival rates. Still other stud­ies indicate greater total spending results in better health sta­tus and survival rates.

These findings raise questions about whether narrowly targeted geographic policies can drive critically important system-wide improvements in efficiency and quality of care.