Why is this information important? What are the implications?
Health care spending is consuming an increasingly larger proportion of GNP every year, but there is little evidence that the amount we are spending is producing better outcomes for populations or for individual patients. Other countries spend far less per person and have better health outcomes. One way to address the question of why is to study which parts of the system appear to be producing "excess" levels of intervention, which are extremely costly but provide no additional benefit over other parts of the system that operate far more efficiently. Some researchers estimate that up to 30% of current spending on health care is wasted. Finding that waste and eliminating it would help provide financial security for the Medicare program without loss of value to the people it covers.

How are the methods used in this project different from other studies I've read?
The Dartmouth Atlas Project uses a methodology, commonly known as small area analysis, which is population-based. The focus of small area analysis is on the experience of the population living in a defined geographic area or the population that uses a specific hospital. Other studies have used a "turnstile" approach, focusing on the number of procedures or hospitalizations in the hospital, without reference to the size of the population served.

Why does the Dartmouth Atlas Project (DAP) focus on Medicare data? Are there similar variations in utilization and spending in the under-65 population?
The Centers for Medicare and Medicaid Services (CMS), the federal agency that collects data for every person and provider using Medicare health insurance, makes available a uniform national claims database for research purposes. There is no counterpart to this database for the commercially insured population. However, similar studies we have done using state all-payer data in Pennsylvania and Virginia, and Blue Cross Blue Shield data in Michigan, have shown similar variations among the under-65 population.

Why don't you have data for Medicare enrollees who are members of health maintenance organizations (HMOs)?
Health maintenance organizations receive capitated payments from Medicare - a fixed annual amount per enrollee - in exchange for which the HMO must provide all required services. Since HMOs do not submit individual claims to Medicare, we must exclude members of HMOs from our claims analyses.

What explains the differences in efficiency among different regions? Is it supply driven?
The supply of such resources as hospital beds and specialist physicians does drive utilization - where there are more hospital beds per capita, more people will be admitted (and will be readmitted more frequently) than in areas where there are fewer beds per capita. Economically, it is important for hospitals to make sure that all available beds generate as much revenue as they can, since an unoccupied bed costs nearly as much to maintain as an occupied bed. Similarly, where there are more medical specialist physicians per capita, there are more visits and revisits to medical specialists. Other reasons for the variations in efficiency are related to practice style - the way physicians in the region practice medicine (using more or fewer prescriptions or tests, for example).

What do you mean more health care is not necessarily better?
The DAP has observed, over the course of its research, that death rates in areas where there is less capacity and less utilization are not higher than death rates in areas where there is much higher capacity and utilization - that is, the additional investment in hospital and physician resources does not "pay off" in increased longevity. Studies by Dr. Elliott Fisher et al have indicated that there is higher mortality in high-resourced, high-utilization areas than in low-resourced, low-utilization areas. One explanation for this phenomenon is that the risks associated with hospitalizations and interventions - infections, medication errors, and the like - outweigh the benefits.

Evidence points out that more aggressive care in managing patient populations with chronic illness does not necessarily lead to longer length of life or improved quality of life. Are you insinuating that we shouldn't do everything we can to save a life?
Ironically, research has found that in patients with chronic illnesses, more aggressive interventions result in shorter life expectancy, probably because of the risks associated with hospitalization. This indicates that the best strategy for extending the life of people with chronic illness is to focus on those activities that provide a survival benefit - better control of diabetics' blood pressure, for example - rather than on "heroic" end-of-life care.

Your study points out that frequent use of services is not associated with either better performance on technical measures of care or marginal improvements in survival and functional status. How do you convince people they don't need additional care and how do you convince doctors not to recommend it?
A recent study reported that almost three-quarters of Americans say they have declined interventions that were recommended by their physicians, because they thought that it was unnecessary or the benefits did not outweigh the risks or side effects. Other studies have confirmed that informed patients want much less surgery, on average, than surgeons are inclined to perform. Making patients aware of the risks and trade-offs associated with treatment choices is one good way of reducing demand for such things as hospital admissions, redundant or unnecessary testing, and surgery when there are other options. Because physicians are reimbursed for activities, the system encourages them to do more. Paying physicians to spend more time advising patients about treatment alternatives (for example, lifestyle changes and medications, rather than bypass surgery), without penalizing them economically for doing less, is another important strategy for reducing utilization.

How do you determine how much care is too much?
By accurately measuring at what point more inputs do not result in better outcomes.

Whose fault is it?
Probably the most important driver of how health care resources are established and used is the current reimbursement system. Hospitals and doctors are paid for activities - hospitalizations, procedures, tests - and are economically punished for using less-invasive, less-costly strategies of care.

This research suggests savings that can be realized within the Medicare system. Don't we need to look at the whole picture to truly realize savings?
Obviously more information about the non-Medicare population would add to our knowledge about what is going on in the system and how it could be improved. Lacking that information, however, we can say two things. The first is that, even if we redirected only Medicare into high-quality, high-efficiency patterns of resource allocation and utilization, we would realize tremendous gains in quality and reductions in spending. The second is that, in several state-based studies of all health insurance claims (both Medicare and commercial) we have determined that the variations in resources and quality in the non-Medicare populations closely resemble those in the Medicare population. So the experience of Medicare enrollees is a reliable predictor of the experience of the non-Medicare population.

However, a hospital's ranking in terms of per capita spending may vary substantially for commercial payers based on market-negotiated (rather than CMS-set) unit prices and the greater spending on non-chronic conditions such as pregnancy. The best strategy for addressing these limitations would be for all payers and self-insured employers to work together to produce resource input and utilization data for cohorts across Medicare, Medicaid and commercially insured patients.