Delivering high-quality health care in a way that is financially sustainable is a pressing issue in the United States. Per-person health care spending is much higher in the U.S. than in other industrialized nations, but quality of care is not notably superior.1 Pressure to spend more will increase as the population grows older and new tests and treatments are developed. Inevitably, rising spending on care will be passed along to federal and local governments, businesses, and the public.
Health care quality and spending are national concerns, but health care delivery is local. Quality of care and spending vary widely across geographic areas, and more spending is not always associated with higher quality of care or better health outcomes.2
The Affordable Care Act may be best known for its expansion and reform of health insurance coverage, but the law also introduced reforms to improve the way health care is delivered, including testing new delivery models and spreading successful ones, encouraging the shift toward payment based on the value of care provided, and investing in agencies and institutes that lead and support efforts to reconfigure how care is delivered and paid for.3 A forthcoming series of case studies conducted by the Fund finds that the engagement of local leaders is critical to harnessing these reforms to improve access, quality, efficiency, and outcomes for communities.
To motivate and guide local leaders, the Commonwealth Fund developed an online tool, the Quality–Spending Interactive (QSI)—an easily accessible source of comparative information. This tool can help leaders identify peer communities, benchmark performance, and learn from those that achieve higher-quality care at lower costs. We updated the tool in June 2017 with the most recently available Medicare data, representing health care utilization and spending in 2015.
What is the Quality–Spending Interactive?
This tool portrays what is sometimes called the “relative value” of care—the amount spent per level of quality achieved. We used publicly available data on quality and spending for the population age 65 and older with traditional fee-for-service Medicare to generate this version of the tool. We started with Medicare because the data offer standardized quality measures and a standardized approach to calculating spending. In the future we hope to include data for commercially insured and Medicaid populations.
How does the tool work?
The tool enables comparison by state or local areas called hospital referral regions (HRRs). The starting point is a graph called a scatter plot that shows overall quality and total Medicare per-capita spending on care relative to the median. (Note that prescription drug spending, which required a distinct dataset, is omitted from our “total spending” estimate.)
The default view is of states, but this can be changed to local areas in “view location type.” Relative quality performance is measured along the vertical axis (Y-axis) and relative spending per person is measured along the horizontal axis (X-axis).
Each dot on the chart represents relative quality and spending within a state or local area, and hovering over the dot reveals the percentage difference (higher or lower) between the state or local area’s quality and spending and the median quality and spending for all states or local areas.
What else can I view beyond overall quality and total Medicare per-capita spending?
Four different provider settings can be selected: hospitals, doctors’ offices, nursing homes, and home health care. For each setting, per-beneficiary spending estimates have been calculated, adjusting for regional wage differences. Quality measures specific to each setting can be viewed individually. We also created a total composite quality score for each setting, which is the average of the component quality measure scores.
How do I interpret the scatter plot?
In general, states or local areas located in the upper left quadrant of the scatter plot—shaded green—spend less and achieve higher quality. Those in the lower right quadrant—shaded red—spend more and achieve lower quality. The upper right quadrant represents higher spending for relatively higher quality while the lower left quadrant represents lower spending for relatively lower quality.
How do I use the tool to compare two areas?
To illustrate, let’s start with a look at total spending and overall quality in Seattle, Washington. To select Seattle, move the region toggle to “HRRs” and type Seattle, or a local zip code, into the search box to the right. You’ll see Seattle, in the middle of the upper left quadrant, performs relatively well, with 18 percent lower spending and 18 percent higher quality than the median for all local areas.
Yet, Seattle could do better. Moving our cursor directly up, we find that Santa Barbara, California, achieves 34 percent better quality than the median, for about the same level of spending as Seattle. Residents of Seattle would enjoy a 16 percentage point jump in quality of care, on average, if their local area performed as well as Santa Barbara.
To look at a more extreme example, moving the performance of Miami, Florida—in the lower right quadrant, to the level of Honolulu, Hawaii—in the upper left quadrant, would reduce spending from $12,871 to $5,585 per person and improve quality of care by 59 percentage points on average for the residents of Miami.
If all other communities could match the performance of the best community, would that be sufficient?
There are caveats to the comparison approach. The tool compares state and local-area quality and spending to the median for all states or local areas. But we know that for the U.S. as a whole, quality is not optimal and spending may be higher than necessary (compared with other countries, for example).4 We know also that populations in some areas are not as healthy on average as those in other areas because of poverty, lower education, and other social and economic factors. For example, should we expect high-poverty areas to achieve the levels of quality per dollar spent that are achieved in wealthier areas? The answer is not clear. Finally, the Institute of Medicine has found that even within local geographic areas there is variation in quality and spending among provider organizations and populations.5 This means that even the highest-quality, lowest-spending areas may have room to improve.
The tool we have developed is a first step. We plan to explore adding quality and spending data on commercially insured nonelderly populations.6 The ultimate goal is to offer leaders comparative information on quality and spending that can be used to motivate and guide efforts to improve quality and affordability in every community.7 We welcome feedback on how you might use the tool in your own work.
1 U. E. Reinhardt, P. S. Hussey, and G. F. Anderson, "U.S. Health Care Spending in an International Context," Health Affairs, May/June 2004 23(3):10–25.
2 E. S. Fisher, D. E. Wennberg, T. A. Stukel et al., "The Implications of Regional Variation in Medicare Spending. Part 1: The Content, Quality, and Accessibility of Care," Annals of Internal Medicine, Feb. 18, 2003 138(4):273–87; E. S. Fisher, D. E. Wennberg, and T. A. Stukel et al., "The Implications of Regional Variation in Medicare Spending. Part 2: Health Outcomes and Satisfaction with Care," Annals of Internal Medicine, Feb. 18, 2003 138(4):288–98.
3 M. K. Abrams, R. Nuzum, M. A. Zezza, J. Ryan, J. Kiszla, S. Guterman. “The Affordable Care Act's Payment and Delivery System Reforms: A Progress Report at Five Years,” The Commonwealth Fund, May 2015 (http://www.commonwealthfund.org/publications/issue-briefs/2015/may/aca-payment-and-delivery-system-reforms-at-5-years)
4 E. A. McGlynn, S. M. Asch, J. Adams et al., "The Quality of Health Care Delivered to Adults in the United States," New England Journal of Medicine, June 26, 2003 348(26):2635–45.
5 J. P. Newhouse and A. M. Garber, "Geographic Variation in Health Care Spending in the United States: Insights from an Institute of Medicine Report," Journal of the American Medical Association, Sept. 25, 2013 310(12):1227–28.
6 J. A. Romley, S. Axeen, D. N. Lakdawalla et al., "The Relationship Between Commercial Health Care Prices and Medicare Spending and Utilization," Health Services Research, June 2015 50(3):883–96.
7 C. H. Colla, W. L. Schpero, D. J. Gottlieb et al., "Tracking Spending Among Commercially Insured Beneficiaries Using a Distributed Data Model," American Journal of Managed Care, Aug. 2014 20(8):650–57.