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Trends in Inpatient Hospital Prices, 2008 to 2010
Jeff Lemieux, MA; and Teresa Mulligan, MHSA

Trends in Inpatient Hospital Prices, 2008 to 2010

Jeff Lemieux, MA; and Teresa Mulligan, MHSA
A comprehensive presentation of intensity-adjusted hospital price levels and growth rates, including national detail on more than 350 types of hospitalizations, and regional and local averages.
These estimates used MarketScan sample weights to correct for geographic differences between the MarketScan sample and national totals. By contrast, the average price per admission on the unweighted MarketScan data was $12,747 in 2008 and $15,111 in 2010, a growth rate over the 2-year period of 8.9%. Thus, the application of the sample weights slightly raises the average national price level and lowers its rate of growth compared with using unweighted data. Our analysis indicates that the main impact of using the sample weights is to correct for differences in the geographic distribution of enrollment between the unweighted MarketScan data set and national totals. This is because there are substantial differences in the levels and rates of growth of hospital prices by region. However, other differences between the unweighted MarketScan data and national totals produced only negligible changes in the price estimates. For example, the average age of the MarketScan data set’s population is slightly younger than the national average age of people with private commercial insurance coverage in the MEPS data set. However, these slight age differences did not seem to noticeably affect the price estimates.

Table 4 lists prices for the 20 highest volume admission categories in the MarketScan data. Since the mix of DRGs is not relevant for within-DRG price changes, we provided an intensity adjustment for these data based on changes in the numbers of procedures only. The highest volume DRG was for vaginal delivery without complicating diagnoses (version 28 DRG 775). Prices per admission in this category rose from $4806 in 2008 to $5543 in 2010, an unadjusted price increase of 7.4% per year. The number of procedures per admission grew by 1.9% per year during this period. Therefore, our estimate of the intensity-adjusted price increase of admissions for uncomplicated vaginal delivery is 5.4% per year in 2008-2010.

Among the highest volume DRGs, the admission category with the most rapid intensity-adjusted price increase during the 2008-2010 period was spinal fusion (except cervical) without major complications or comorbidities (version 28 DRG 460). The price for this type of admission rose from $33,240 in 2008 to $44,126 in 2010, an unadjusted annual price increase of 15.2%. After adjusting for intensity growth via the number of procedures per admission, we estimate that price increases averaged 14.9% for this category of admissions in 2008-2010.

Using the US Census definitions of Metropolitan Statistical Areas, we were able to show the estimates of price changes for rural areas and many of the largest metropolitan areas (Table 5). Average prices per admission in rural areas rose from $12,541 in 2008 to $14,811 in 2010, an unadjusted price increase of 8.7%. After adjusting for intensity, price increases in these areas ranged from 5.8% per year (using risk scores) to 6.8% per year (using DRG weights and number of procedures). Thus, price increases in rural areas were fairly close to the national average.

However, some metropolitan areas showed much higheror lower-than-average price increases, even within the same state. For example, we estimate that intensity-adjusted prices in the Houston, Texas, metro area grew by only 0.8% to 2.8% annually, while intensity-adjusted prices grew by 6.3% to 6.8% in the Dallas, Texas, area and 8.3% to 8.5% in the San Antonio, Texas, metropolitan area.

The Appendix Tables 1-8 contain detailed price estimates by DRG, state, and Metropolitan Statistical Area, including the background information used to compute intensity adjustments.

DISCUSSION

We estimate that unadjusted prices for inpatient hospital care rose by 8.2% per year during the 2008-2010 period in a large sample of 45 to 49 million enrollees under age 65 years with commercial health insurance. Based on changes in patients’ risk scores and changes in the mix of admissions and the numbers of procedures performed, we estimate that approximately 1.3 to 1.9 percentage points of the unadjusted 8.2% growth in prices could be attributed to increased intensity per admission. Thus, we estimate that intensity-adjusted price increases ranged from 6.2% to 6.8% annually in the 2008-2010 period.

The MarketScan data are broadly consistent with 2 other emerging sources of data on inpatient hospital prices: the Health Care Cost Institute (HCCI), which reports aggregated hospital prices based on data collected from 3 large health insurance plans,14 and the states of California and Oregon, which make available some basic information on transaction prices for commercial payers.15 Using the MarketScan data, we estimate that unadjusted hospital prices grew by 6.5% in 2009-2010; in the HCCI data set, unadjusted inpatient hospital prices grew by about 7.4%. However, HCCI’s estimated intensity adjustment (3.3%) in 2010 was larger than our adjustment (0.9% to 1.6%) in that year. Thus, HCCI’s estimate of intensity-adjusted hospital prices (4.0%) is somewhat lower than our estimate of 4.9% to 5.5%. Our estimate of the average price for inpatient hospitalizations in California in 2009 ($20,592) is roughly equivalent to the average from California’s Office of State Health Planning and Development ($20,800), and our estimate of the growth of prices in Oregon in 2009 (9.6%) is consistent with the double-digit growth rates implied by data provided by Office for Oregon Health Policy and Research in the 2005-2009 period.

There are several important limitations with our data and approach. First, before weighting, the MarketScan data set represents about 30% of the non-elderly US population with private health coverage. However, despite the sample’s large size and the sample weighting used, there is no guarantee that the MarketScan data are representative of the entire commercially insured US population. The sample weights help adjust for demographic and regional differences between the MarketScan data and the national totals, but there may be other factors unique to the MarketScan data that are not corrected by weighting. Therefore, we would not assert that even the weighted data are necessarily representative. However, we do believe that the weighting provides a helpful improvement in the accuracy of our estimates.

A second question is whether the intensity adjustments are sufficient or overdone. By combining DRG weights and procedures, we may be overestimating intensity growth, since the extra procedures may have been associated with the move toward more complex DRG codes. However, using risk scores as a proxy for intensity produces results similar to using the DRG severity weights in combination with procedure counts.

There may be other ways of thinking about intensity that we cannot measure. For example, if more patients stayed in individual hospital rooms, as opposed to double rooms, would that qualify as an intensity gain? It would not show up under the number of procedures or in the severity of DRG codes, but one could argue that the additional cost of single rooms represents a service enhancement rather than a price increase. Likewise, a higher nurse-to-bed ratio might enhance safety and service, but unless the additional staffing were reflected in DRG severity, procedures performed, or patients’ risk scores, our method would not capture the additional services.

Finally, prices for individual DRGs, states, and localities may be affected by specific clinical, social, regulatory, or economic factors that could explain some price levels and changes. Likewise, it is possible that temporal changes in the composition of MarketScan enrollment itself could affect price trends in some localities. We did not publish information for states or localities where the MarketScan enrollment changed substantially between 2008 and 2010. However, for the states and localities we do show, we did not undertake a systematic study of the underlying enrollment composition. Therefore, some local price changes could result from an enrollment effect not captured in our study of risk scores, procedures, and DRG distributions.

On balance, we believe our results support the general proposition that US hospital prices rose rapidly in the 2008-2010 period. A key advantage of the MarketScan data is that price changes and levels can be disaggregated by admission type and by many states and localities. We believe the MarketScan data set is large enough to provide helpful benchmarks across these dimensions. We hope that the specific price information we present in the appendices will help facilitate future research on why prices are increasing and why price levels and price growth rates may differ across admission types and geographic locations.

Author Affiliations: From America’s Health Insurance Plans (JL, TM), Washington, DC.

Funding Source: None.

Author Disclosures: Mr Lemieux and Ms Mulligan report employment with AHIP, a national trade association for health plans, including Medicare Advantage Plans.

Authorship Information: Concept and design (JL); acquisition of data (JL, TM); analysis and interpretation of data (JL, TM); drafting of the manuscript (JL); critical revision of the manuscript for important intellectual content (JL); statistical analysis (JL, TM); and supervision (JL).

Address correspondence to: Jeff Lemieux, MA, SVP, Center for Policy and Research, AHIP, 601 Pennsylvania Ave, NW, South Bldg, Ste 500, Washington, DC 20004. E-mail: jlemieux@ahip.org.
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