Interim Report of the Committee on Geographic Variation in Health Care Spending and Promotion of High-Value Care Preliminary Committee Observations (2013) / Chapter Skim
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Interim Report
Interim Report
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was asked to investigate geographic variation in health care spending and quality and to analyze Medicare payment polices that could encourage high-value care, including adoption of a geographically based value index. This index would account for both the health benefit obtained from health care services delivered and the cost of those services, as discussed later in this report.
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For instance, congressional representatives in areas generally associated with high-quality, low-cost health care argue that highly efficient hospitals and providers are penalized under the current payment system.2 Based on these observations, some policy makers believe that Medicare should adjust hospital and physician reimbursement rates based on regional performance to encourage more uniform health care system performance for Medicare beneficiaries across hospital markets (Hahn, 2009) .3,4,5 Proponents of a geographic value index theorize that regional payment adjustments would encourage all hospitals and providers within an area to coordinate care, leading to better system efficiencies across the entire region.2,6,7 Other health care experts counter that recommendations stemming from Dartmouth's research conflate the issue of improving value with that of reducing geographic variation.
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draws on language in earlier federal health care reform legislation8 and includes the following three tasks:9 (1) to independently evaluate geographic variation in health care spending levels and growth among Medicare, Medicaid, privately insured, and uninsured populations in the United States; (2)
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. The extent of geographic variation was examined within and across geographic units; across clinical condition cohorts, and over time.
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BOX 2 Definitions of Geographic Units Frequently Used in Health Services Research Hospital referral regions (HRRs) : Created by Dartmouth to represent regional health care markets for tertiary (complex)
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GEOGRAPHY AND INDEXING VALUE An important part of the committee's Statement of Task and research framework focuses on "whether Medicare payment systems should be modified to provide incentives for high-value, high-quality, evidence-based, patient-centered care through adoption of a value index (based on measures of quality and cost) that would adjust payments on a geographic area basis." To create a research framework that would generate useful information for policy makers, the committee needed to understand the dimensions of the geographically based value index, described in its Statement of Task, and related terms (see the glossary in Appendix A)
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3962) , on which the committee's charge is based, asked the IOM to consider a "value index based on a composite of appropriate measures of quality and cost that would adjust provider payments on a regional or provider-level basis."11 Thus, the committee limited its evaluation of a "geographically based value index" to a relative ratio that uses area-level composite measures of clinical health outcomes and cost to adjust individual hospital and provider payments under Medicare Parts A and B ("a geographic value index")
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system, which is designed to automatically decrease physician payments each year if their total expenditures exceed Medicare spending targets in the previous year (and vice versa) , has not incentivized providers to constrain spending growth.
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Observation 2 Substantial variation in spending and utilization exists within progressively smaller units of analysis. To determine whether provider organizations within an identified area behave similarly, the committee examined patterns of health care resource use across sub-regions, service types, and clinical condition categories, as well as condition-specific quality measures across HRRs.
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21. FIGURE 3 Bottom 20 percent of hospital referral regions and hospital service areas in drug spending.
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. Figures 4, 5, and 6, respectively, display results of analyses of variation in Medicare spending at the hospital level within each HRR for the three clinical conditions examined -- stroke, hip fracture, and heart attack -- with adjustments for input price and health status.
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SOURCE: Committee analysis of unpublished Dartmouth data.16 12
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For more than two dozen clinical conditions, Blue Cross Blue Shield of Massachusetts (BCBSMA) regularly examines variations in practice patterns among physicians within a particular specialty, comparing physicians with their immediate practice peers as well as all comparable specialists across the state.
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within the same practice group found that individual levels of utilization and quality varied across nine distinct measures associated with diabetes, cholesterol, and hypertension control; ordering of radiology tests and generic prescriptions; and rate of admissions and emergency department visits (Partners HealthCare, 2012)
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Therefore, for a geographic value index to generate fair reimbursement rates, data should indicate that performance across a wide range of quality measures is relatively consistent within an area. To test this notion, the committee performed pairwise correlations between 18 conditionspecific quality measures (Acumen, LLC, 2013a, p.
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Adjusting for age and sex at the HRR level has a negligible effect on geographic variation in spending, indicating that the age and sex distribution is similar across HRRs. Health status, by contrast, does considerably decrease spending variation between high- and low-spending regions.22 Cluster 5 in Table 2 indicates that adjusting for race and income also has a negligible effect on variation, after health status is accounted for.
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In other words, a greater number of HRRs (weighted by beneficiary-months) falls in the middle range of Medicare spending.
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SOURCE: Developed by the Committee and IOM staff based on the data from Acumen Medicare Analysis. Cluster 8 in Table 2 indicates that market factors add little explanatory power, and a substantial amount of variation remains unexplained after controlling for all predictors measureable within our data and supported by the literature.
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A geographic value index could use composite measures of health care quality and service use within a payment region to calculate the numerator and denominator of a single payment adjustment as proxy measures of value (Hahn, 2009) .23,24,25 Composite measures aggregate multiple measures of health care service use and quality at an area level.
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First, few of the correlations differ substantially from zero. Second, the methodology for risk adjustment of quality measures may not adequately capture differences in health status.
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When compared with unadjusted spending, input price adjustments slightly increased variation; inputprice-adjusted spending in the 90th percentile was 44 percent and 41 percent more per Medicare beneficiary than input-price-adjusted spending in the 10th percentile for HRRs and MSAs, respectively.29 27 To keep the presentation manageable, many of the committee's analyses present the 90th percentile of Medicare spending in Parts A and B compared to the 10th percentile for the aggregated years 2007-2009. This is approximately the ratio of average spending in the highest spending quintile compared to the average spending in the lowest spending quintile of geographic units.
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in which the individual resides. 30 Committee analysis of Acumen Medicare data.
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other.31 Based on the subcontractors' analyses, it appears that utilization of post-acute care services is a key driver of HRRlevel variation in Medicare spending, with most of the remaining variation stemming from use of inpatient services. Acute and post-acute service utilization are linked, since post-acute services are covered only after a 3-day inpatient stay, with the exception of some home health services.
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(b) Acute Care Monthly Adjusted Differences Diagnostic Monthly Adjusted Differences from the National Mean of Spending Across from the National Mean of Spending Across HRR HRR $450 $450 $400 $400 $350 $350 $300 $300 $250 $250 $200 $200 $150 $150 $100 $100 $50 $50 $0 $0 -$50 -$50 -$100 -$100 -$150 -$150 -$200 -$200 (c)
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using CMS's Chronic Conditions Warehouse database.32 The Lewin Group examined the following subcategories of post-acute care spending: skilled nursing facilities, home health, hospice, long-term care hospital, and inpa tient rehabilitation facility. To identify how much each of these post-acute care services contrib utes to variation in total post-acute care, the investigators compared the unadjusted mean of post acute care spending with the four subcomponent spending variables if each were set at its nation al mean for all HRRs.
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of all variation in Medicare spending is explained by variation in post-acute care services. Within post-acute care, the home health and skilled nursing facility categories have the strongest influence on the variation in spending.
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2. FIGURE 11 Variation in total all-services per capita Medicare spending explained by categories of postacute care spending and all other spending (2007-2009)
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Although the amount of annual Medicare spending due to fraud is, by definition, unknown (Goldman, 2012) , recent estimates indicate that Medicare and Medicaid paid as much as $98 billion in fraudulent and abusive charges in 2011 (Berwick and Hackbarth, 2012)
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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.
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. And although the literature suggests that different sources of data vary with respect to their estimation of quality, it is demonstrated that absent true clinical data, delineating patients falling within clinical conditions with claims data is difficult (Keating et al., 2003)
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