Regional differences in the cost of health care are due to differences in both the price and volume of medical care. Since, Medicare sets prices, there should be little variation in prices…right?
Actually, Medicare payments have geographic adjustments based on a number of factors. For instances, the hospital wage index gives pay hospitals more in areas with higher labor costs. Similarly, Medicare pays physicians more in high cost areas through the geographic practice cost index (GPCI).
In order to compare differences in volume across regions, one must also make the following adjustments
- additional payments to hospitals above the standard rates in the inpatient prospective payment system including graduate medical education, indirect medical education, and disproportionate share payments.
- additional payments to physicians above the standard rates in the physician fee schedule in provider scarcity areas and health provider shortage areas.
- additional payments to rural hospitals above standard rates in the inpatient prospective payment system, including special payments for sole community hospitals, small rural Medicare-dependent hospitals, and critical access hospitals.
- beneficiaries’ health status, as measured by the MSA’s average risk score from the CMS–hierarchical condition category (HCC) risk adjustment model.
- the rate of beneficiaries’ enrollment in Part A and Part B of the Medicare program—in some areas, the percentage of beneficiaries with only Part A or Part B coverage differs significantly from the national average.
After taking these factors into account, a recent MedPAC report finds that although raw per capita spending is 55% higher for beneficiaries in the area at the 90th percentile than for beneficiaries in the area at the 10th percentile, medical utilization use in higher use areas (90th percentile) is only about 30% greater than in lower use areas (10th percentile). Approximately, 45% of the FFS population lives in areas that have service use within 5 percent of the national average.
The metro area with the highest service use was Miami. In fact, Miami’s medical service use was twice the level of the services provided in the metro area with the lowest utilization levels (non-metropolitan Hawaii). One reason for this difference is that “per capita spending on durable medical equipment and home health care in Miami–Dade County were both more than seven times the national average and dramatically above spending in neighboring counties.”
- Source: MedPAC (2009) “Measuring Regional Variation in Service Use: Report to Congress,” December 2009.
- Hat Tip: Gooz News.
A more recent MedPAC report that uses BASF and MedPAR data finds that that “…46 percent of FFS beneficiaries live in areas that have service use within 5 percent of thenational average. In contrast, only about 25 percent of FFS beneficiaries live in areas where rawspending is within 5 percent of the national average.” These figures are comparable, but slightly less dispersed that the estimates from the 2009 report. The ratio of MSAs in the 90th percentile are 1.55 times as high as those in the 10th percentile. Service use in the 90th percentile, however, is only 1.30 times as high as service use in the 10th percentile MSAs. These results are similar when comparing spending and utilization among decendents and non-decendents. The largest variation in spending actually comes from post acute care services (compared to acute inpatient and ambulatory services). For instance, although McAllen, TX has serivce utilization that is 3.2 times as high as the national average, beneficiaries living in McAllen use 7 times as much home healht services as the national average. Another study found that average home health cost in North Dakota was $2,396 versus $7,761 in Nevada.
Other findings include:
- Variation in service use is similar across MSAs and nonmetropolitan areas
- Level of service use has a slightly inverse relationship to growth in service use
- There is variation in spending within MSAs as well as across MSAs
Source: MedPAC. “Regional Variation in Medicare Service Use.” January 2011.
Beautifully analyzed, interpreted and explained.