Karin Bierstein, JD, MPH
Vice President for Strategic Planning and Practice Affairs,
Anesthesia Business Consultants, Jackson, Michigan
It is no secret that the cost of healthcare services varies greatly between geographic regions. A major new study from the Health Care Cost Institute (HCCI), National Chartbook of Health Care Prices, examined price variation for 242 common medical services across 41 states and the District of Columbia and found a two- to threefold difference. The graph in Figure 1, from the accompanying article by David Newman et al. (Prices for Common Medical Services Vary Substantially among the Commercially Insured) in the April 2016 issue of Health Affairs, shows the variation among average prices in the 41 states and D.C. when each is compared to a national index figure of 1.00.
The Newman study represents one of the largest inquiries into commercial price variation in healthcare. Differences in Medicare costs are also substantial, as shown in the Dartmouth Atlas of Health Care and elsewhere. Commercial price information has been much less readily available than Medicare data. David Newman is the executive director of the HCCI and, together with his team of HCCI researchers, was able to delve into that organization’s commercial claims database containing nearly three billion paid claim lines (line item elements, i.e., separately billable services in a medical claim) processed by Aetna, Humana and United Healthcare. The researchers found that prices for 162 common services such as imaging, ultrasounds, joint replacement surgeries and cataract procedures were reportable in all 41 of the states and D.C. Their analysis revealed that the ratios of average state private health plan prices to the average national price for the 162 services varied from a low of 0.79 in Florida to a high of 2.64 in Alaska. The amount of variation between and within Metropolitan Statistical Areas was comparable.
Imaging, radiology and laboratory tests show the greatest nationwide variation. The amounts allowed by the various insurance companies (as opposed to charges) were not broken out separately for surgeons and other specialists or hospitals. Prices for knee replacements varied most in California, with a $27,243 average price difference between Riverside ($30,261) and Sacramento ($57,504). In Ohio, the average price of a pregnancy ultrasound in Cleveland was almost three times that of Canton ($522 and $183 respectively), even though the two cities are only 60 miles apart.
As Newman and his colleagues point out, “The questions that remain for researchers, policy makers and healthcare leaders are as follows: Why do prices for the same service differ markedly across distances of only a few miles, and what amount of that difference is justifiable?”
Geographic differences in salaries, rents or other cost-of-living indicators may both explain and justify some of the variation. Those indicators are certainly higher in Alaska than in the continental United States. But, as the study notes, “the remaining variation is most likely due to differences in underlying market dynamics, such as varying market power, a lack of transparency or the availability of alternative treatments.”
It is not attributable to differences in quality. A 2013 Institute of Medicine study, Variation in Health Care Spending: Target Decision Making, showed the lack of association between spending and quality in both over-65 Medicare and under-65 private insurance markets. Nor do differences in the use of technology explain the variation. The same technology is available in all states, and it is implausible that physicians in the regions with lower spending are consciously denying their patients needed care. In fact, the evidence would indicate that the quality of care and health outcomes are better in lower-spending regions and that there have been no greater gains in survival in regions with greater spending. (Fisher ES, Bynum JP, Skinner JS. Slowing the Growth of Health Care Costs — Lessons from Regional Variation. New England Journal of Medicine. 2009 Feb 26; 360(9): 849–852.)
What about the old chestnut, “our patients are sicker?” Or to put the question in more technical terms, what about risk adjustment? Regarding their own analysis, Fisher et al. stated, “It is highly unlikely that these differences in growth could be explained by differences in health. Marked regional differences in spending remain after careful adjustment for health, and there is no evidence that health is decaying more rapidly in Miami than in Salem.”
The HCCI analyzed average prices of 242 standardized groupings of diagnostic and procedure codes for healthcare services, or “care bundles.” The code or codes compromising the bundle reflect a typical collection of services consumed, bypassing the issue of variations in utilization patterns, which might indicate greater acuity among patients receiving higher quantities of services. The 2013 Institute of Medicine study, however, concluded that “variation in spending in the commercial insurance market is due mainly to differences in price markups by providers rather than to differences in the utilization of healthcare services.”
Many health policy experts believe that the healthcare delivery and payment systems are to blame. In 2009, Fisher et al. wrote that “Consensus is emerging that integrated delivery systems that provide strong support to clinicians and team-based care management for patients offer great promise for improving quality and lowering costs.” (Since no policy makers are trying to raise costs, lowering them in general would reduce the amount of variation.)
The Affordable Care Act (ACA) was intended, among other things, to reward providers for providing high quality care while holding costs down, i.e., for “value.” The law introduced various new payment systems such as shared savings programs to Medicare, with a reduction in the rate of spending growth as a result, but the commercial market has only been affected marginally.
“The current political environment makes it unlikely that reforms to control system-wide healthcare costs will be achieved at the federal level in the near future. States, however, are well-positioned to take the lead on implementing cost control and quality improvement reforms. Indeed, many states are already innovating and seeing positive results,” according to a paper by Zeke Emanuel et al. (State Options To Control Health Care Costs And Improve Quality) published by the Center for American Progress in April 2016. Emanuel and his team provide descriptions and examples of the following policy options for decreasing spending and quality:
Policy options and selected state examples
- Establish a cost growth goal
• Examples from Massachusetts, Maryland and Rhode Island
- Publish a health and cost outcomes scorecard
• Examples from Maryland and Oregon
- Adopt payment and delivery system reform goals
• Examples from Massachusetts, Maryland, Rhode Island and Californi
- Implement bundled payments for all payers
• Examples from Arkansas, Tennessee, Ohio and Delaware Institute global budgets for hospitals.
- Institute global budgets for hospitals
• Example from Maryland
- Launch all-payer claims databases
• Examples from Maine, Colorado, New Hampshire and Washington
- Expand evidence-based home visiting services
• Examples from Minnesota and South Carolina
- Improve price transparency
• Examples from New Hampshire and Massachusetts
- Integrate behavioral health and primary care
• Examples from Oregon, Washington and Colorado
- Combat addiction to prescription drugs and heroin
• Examples from Maryland, Florida, New York and Rhode Island
- Improve the delivery of long-term care
• Examples from California, Maryland, Montana, Oregon, Texas and Missouri.
- Align scope of practice with community needs.
- Institute reference pricing in the state employee plan
• Example from California
- Expand the use of telehealth
• Examples from Maryland, New York, Virginia, the District of Columbia and Pennsylvania
- Decrease unnecessary emergency room use
• Examples from Georgia, New Mexico, Indiana, Minnesota, Washington and Wisconsin
The need to reduce variation in healthcare spending that is driven by pricing power rather than by population health goals means that we are likely to see more and more states and localities implementing their own versions of the above strategies. Familiarity will make the changes easier.