With funding from the National Institutes for Health and not-for-profit foundations, the goal of the Dartmouth research team has been to improve our understanding of the causes and consequences of variation in the way health care is delivered around the country. Why do some primary care physicians order more than twice as many CT scans as their colleagues in the same practice? Why are the rates of coronary stents three times higher in Elyria, Ohio, compared with nearby Cleveland, home of the famous Cleveland Clinic? And most importantly -- what do these differences mean for patients? The aim of the research is to advance the science of health care delivery -- to understand what actually happens to patients and what can be done to make care better.
During the past several years, the Dartmouth research has drawn attention from policy makers, politicians and stakeholders in health care reform. While many of the findings are broadly accepted and their implications are already being translated into practice, some confusion about the Dartmouth work remains. In this summary, we provide brief responses to the questions that have been raised.
The Dartmouth Atlas shows a more than two-fold variation in per capita Medicare spending in different regions of the country. Do these findings take into account differences in the rates per procedure that Medicare pays? We have recently implemented price-adjustments in our Atlas measures. As it turns out, price doesn’t matter much, except in New York City which is something of a special case. Adjusting for price differences leads to only a modest decline in overall variations. It is utilization -- the amount of care delivered to patients -- that explains most of the regional variation in Medicare spending.
Regions where Medicare spends more have more poor people. Doesn’t poverty explain the differences in spending? In a recent New England Journal of Medicine paper, using a sample of 15,000 Medicare beneficiaries, we found that
poverty explained little of the variation in health care spending across regions – at most 4%.
So why do some critics still believe that income matters? It is well known that poverty goes hand in hand with
poor health, and we know sicker people generally need more care. Yet people with low income also suffer from limited access to care, so they don’t always get the treatments they need.
Do more expensive regions and hospitals have sicker patients? On average, expensive regions have sicker patients, but as we have shown, their higher illness levels explain only fraction of the overall differences in regional variations. A recent study by MedPAC suggested a larger role for illness in explaining regional variations, but their adjustments suffer from well-known biases: people are more likely to be “diagnosed” with a disease when their physician or hospital treats them more intensively. This bias makes patients in high-intensity areas appear sicker than they really are. The most reliable approach to addressing the problem of illness-adjustment -- following cohorts of similar patients over time -- continues to show more than twofold variation in utilization across the
Dartmouth compares the care of patients in the last two years of life at different hospitals, but doesn’t that method fail to take into account the possibility that some hospitals are better at preventing death than others? Two issues are confounded here. The first question is whether end-of-life measures accurately predict how intensively hospitals treat patients with other conditions such as heart attacks. As we show, they do. The second is whether higher intensity hospitals achieve better outcomes. The Dartmouth research that has looked at this question focused on patients with specific conditions, such as hip fractures and heart attacks, and followed them for several years to see how they fared. On average, higher spending was not associated with better outcomes.
Is there any evidence that spending more leads to better outcomes? The key question is: spending more on what? Dartmouth research comparing spending differences across both regions and hospitals found that most of the spending was due to differences in use of the hospital as a site of care (versus, say, hospice, nursing home, or the doctor’s office) and to discretionary specialist visits and tests. Higher spending on these services does not appear to offer overall benefits. Other Dartmouth research suggests that hospitals spending more on effective care do in fact get better outcomes.
Several other recent studies have found that some higher spending hospitals do have better outcomes. For example, a recent paper by Michael Ong and others looked at heart failure patients cared for at six California hospitals. They found that patients cared for in the most expensive hospitals had lower mortality. We also found this strong association for their six hospitals using our own heart attack data, but when we looked at all California hospitals, the association between spending and outcomes no longer held. Other studies have shown small positive benefits associated with specific types of services. More importantly, many health systems are able to provide high-quality care at low cost, suggesting that we don’t need to spend more to get better outcomes.
Does Medicare spending track spending in the rest of the health care system? The available evidence suggests that hospitals and regions that provide more care to Medicare patients also provide more for their non-Medicare patients. But in under-age-65 insurance markets, prices per procedure can vary wildly across regions -- so total per capita regional spending in the under-65 markets may not be closely associated with per capita Medicare spending in those markets. This suggests we should look for savings in each sector of the health care system.
The Atlas is often cited as a source for the estimate that 30% of the nation’s spending is unnecessary -- what is the
evidence? The Dartmouth approach was to ask how much might be saved if all regions could safely reduce care to the level observed in low-spending regions with equal quality; we find estimates ranging from 20-30%, but view these as an underestimate given the potential savings even in low cost regions. At least three other groups have come to 30% waste estimates: the New England Healthcare Institute, McKinsey, and Thomson Reuters.
How should reimbursement to regions and hospitals be based on the Atlas work? The Atlas measures of cost are
reliable, but should not be used to set payment rates until hospitals and their associated physicians can be organized in ways that allow them to improve patient care. Current Atlas measures do provide useful insights to regional health systems and to individual providers who wish to consider how they might reduce overtreatment, improve care, and curb spending.
The key take-home message is that we believe that there is enormous scope for improving the efficiency and quality of US health
care. The Dartmouth research suggests that improvements in both cost and quality can be achieved by supporting new models of payment that reward providers for improving quality, managing capacity wisely, and reducing unnecessary care.