Institute of Medicine
The National Academies
A geographic value index would adjust payment to all providers within a defined area based on aggregate measures of spending and quality. The committee sought to determine empirically whether providers within a defined area behave similarly (e.g., exhibit similar patterns of service use across sub-regions, clinical conditions and quality measures). Consistent with a body of literature, analyses commissioned by the committee observed variation in health care spending at every geographic level (Hospital Referral Regions, Hospital Service Areas, Metropolitan Statistical Areas) studied, and additional research found variation among hospitals within Hospital Referral Regions, among physicians in the same group practice, and even within individual providers when treating different conditions. Further, Hospital Referral Regions do not consistently rank high or low across quality measures, nor is there a consistent relationship between utilization and various quality measures. These preliminary observations suggest that a geographic value index would reward low-value providers in high-value regions and punish high-value providers in low-value regions.
Health policy leaders suggest that, to improve value, payment reforms need to create incentives to encourage behavioral change in the locus of care (provider and patient), and thus payment should target decision-making units, whether they be at the level of the individual providers, hospitals, health care systems, or stakeholder collaboratives. Payment reforms contained in the ACA (e.g., value-based purchasing, accountable care organizations, bundled payments) and being tested in the commercial market and Medicaid, do target decision makers rather than geographic areas. Because these reforms are relatively new, there is little evidence to date about their effects on the value of care. Nevertheless, the results of the subcontractors’ work for this study suggest that tying a decision-making unit’s payment to its actions, as these reforms do, is preferable to induce desired changes in care. Further, because post-acute care, particularly home health and skilled nursing, is a major source of unexplained variation in Medicare spending, reforms that address incentives to overuse post-acute care, including fraud in that use, could have a large impact on health care efficiency.
By Don McCanne, M.D.
Health care spending tends to fall under a Bell curve. Most of it falls in the middle, but some falls under the low end (low-cost) and some falls under the high end (high-cost). The Dartmouth studies have confirmed the geographical nature of this distribution. Thus much attention has been directed to devising methods of recovering the allegedly excessive spending in the high-cost regions. This report casts doubt that such an effort would be productive.
To begin with, the Bell curve or Gaussian distribution (normal distribution) is to be expected even when resources are being used properly. Further, this variation is found not only between geographic regions, but also between hospitals within the same regions, between physicians within the same group practices, and even by the same physicians managing different conditions. Thus measures designed to reduce spending only in geographical regions at the high end will be too blunt because they would reduce not only high-cost care of lower value, but they also would reduce legitimately high-cost care that is providing full value.
The authors of this Institute of Medicine report suggest that payment reforms instead should target decision makers rather than geographical areas. The decision makers include individual providers, hospitals, health care systems, and stakeholder collaboratives. Health payment reforms of the Affordable Care Act are designed to do just that. These include measures such as accountable care organizations, value-based purchasing, and bundled payments. Of course, adjusting payments based on these and similar reforms are much more complex administratively than merely adjusting payments based on regional spending levels.
It is questionable as to whether or not such payment systems could ever be effective in significantly improving value in the entire health care system since most impacts of the payment models are effective only at the margin, if even there. Further, Gaussian distributions would apply to these new models as well, making it likely that payment adjustments would be inappropriate for some, even if appropriate for others.
Think of the Bell curve again, but for decision makers rather than geographical regions. Many have suggested that 30 percent of health care represents wasteful spending. What if you lop off the upper 30 percent of care under the Bell curve? First you have to believe that you can identify low-value care in advance – a highly unlikely scenario. Then you have to assume that all care in the lower 70 percent provides value whereas that in the upper 30 percent does not – a preposterous assumption.
What about the lower 30 percent of the curve. Does it really represent high-value, low-cost care? Or does it represent care that is not being delivered (and therefore not measured), even if it should be. Shouldn’t we be directing more efforts to be sure that we are meeting patient needs, even if it could increase health care spending?
We are looking for ways to slow down the outrageous increases in spending for what is often mediocre care. These feeble measures that are designed to tweak decision makers are complex and likely will cost as much to administer as any meager savings that they could realize. Some of the ideas may be worth pursuing, such as value-based purchasing, but we should not deceive ourselves that these are the grand solutions for our excessive spending.
All other wealthy nations provide care for everyone at much lower costs, and they have done it without playing these pseudo-wonk policy games. We can’t rely on silly, little tweaks. We need fundamental reform of our health care financing system. We need a single payer national health program.