Regional Variation

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Add to Your Skills Toolkit: The Oaxaca Decomposition

January 26, 2012 in Econometrics, Economics - General | No comments

Suppose you look at health care spending in two different regions and observe a significant difference.  You may want to know what the cause of this difference is.  Is it because one region has a mix of people who are sicker; or is because the reason treat patients with a given disease more intensively?

One way to answer this question is to use the Oaxaca decomposition.  This approach was originally formulated by Ronald Oaxaca. This document provides a nice overview of how to use the Oaxaca Decomposition and I apply that framework to the health spending case.

Differences in Health Spending

Assume that there are two regions: Region A and Region B. The spending for the two regions can be modeled using a linear regression framework:

  • YA = βAX + εA
  • YB = βBX + εB

The Y term represents spending and the variable X represents the patient’s health status. Health status could be measured as a vector of factors or as a single indicator (e.g., healthy or sick). The term β describes much an area spending on medical resources to treat a patient with a health status of X. Thus, average difference in spending per person the two regions is:

  • YA – YB = βAXA – βBXB

where XA is the average case mix in the area.

Determinants of Health Spending Differentials

Now the question is whether case mix or spending practices conditional on case mix is the key driver of the differences in spending between regions A and B. One can differentiate these two components using the following Oaxaca Decomposition:

  • YA – YB = ΔXβB + ΔβXA
  • YA – YB = ΔXβA + ΔβXB

In the first equation, the differences in health status (X‘s)are weighted by the coefficients for region B and the differences in the coefficients are weighted by the X’s from region A, whereas in the second, the differences in the X‘s are weighted by the coefficients of from region A and the differences in the coefficients are weighted by the X‘s of from region B.

There are basically three factors that effect health spending in the region: i) differences in health status across regions ii) differences in treatment patterns conditional on health status, and iii) the interaction of health status and conditional treatment effects. One can see this clearly below:

  • YA – YB = ΔXβB + ΔβXB + ΔXΔβ
  • YA – YB = H + T + HT

The equations above show the health status effect (H), the treatment effect (T) and the interaction (HT).

The specification chosen for the Oaxaca decomposition determines whether the interaction effect is placed with the health status effect or the treatment effect.  More precisely:

  • YA – YB = ΔXβB + ΔβXA = H + (HT + T)
  • YA – YB = ΔXβA + ΔβXB = (H+ HT) + T

In effect, the first decomposition specification incorporates the interaction term with the treatment effect whereas the second specification places the interaction term together with the health status effect.

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Regional Variation in Medicare Spending

September 18, 2011 in Supply of Medical Services | 1 comment

What causes regional variation in spending and outcomes?  Previous research claimed that physician treatment norms in different areas account for much of these differences.  Recent research, however, claims that most of these regional differences are caused by geographic differences in health status.  Reschovsky et al (2011) find the following when examining a sample of Medicare beneficiaries linked to 2004–2005 Community Tracking Study Physician Survey:

Nonetheless, a key finding from this work is that key conclusions from prior small area analyses (e.g., Fisher et al. 2003; Center for the Evaluative Clinical Services 2007) that much of the variation in cost of treating Medicare beneficiaries is driven by supply-induced demand (e.g., “supply-sensitive care”) cannot be supported when one comprehensively controls for health status and conducts analysis at the beneficiary level. Zuckerman et al. (2010) reaches a similar conclusion. Medical specialists serving as USOCs and the proportion of medical specialists in the county were the only two supply-side variables with positive effects on costs consistent with other research (Fisher et al. 2003; Baicker and Chandra 2004). However, the strength of the medical specialist results, though not trivial, would explain little of the geographic variation documented in the Dartmouth Atlas. The supplies of hospital beds had significant positive effects among high-cost beneficiaries, but elasticities suggest that the magnitude of the effect is extremely small: doubling hospital bed supply would increase costs by <2 percent.

Physician choice of treatments may still have some impact on cost for certain procedures although the latest research seems to indicate that its affect on regional variation for total spending is small. Further, over time, the physician discretion may decrease in the Internet age due to 1) patients being more informed of their treatment options and 2) physicians gaining easier access to information on best practices. Nevertheless, the most recent research clearly indicates that patient health status is the key driver of medical spending.

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Regional Variation in Elective Surgery

April 11, 2011 in Supply of Medical Services | No comments

A recent report by the Dartmouth Atlas team finds significant geographic  variation elective surgery.

“…if you have heart disease and live in St. Cloud, Minnesota, you are half as likely to undergo cardiac bypass surgery than if you live in Detroit Lakes, and more than twice as likely to undergo back surgery than if you live in Rochester. If you have gallstones and live in Wadena, you are three times more likely to have your gall bladder removed than if you live in Minneapolis.”

More interesting, however, is what causes the regional variation.  Significant regional variation only occurs when there is a lack of professional consensus on the correct treatment for any condition.

“For example, there is considerable disagreement among surgeons about the need for back surgery, its effectiveness, and even the best way to diagnose the cause of back pain. This lack of agreement stems in part from a lack of studies, called clinical trials, which provide the scientific evidence that clinicians need in order to know how best to treat their patients. With no consensus about how to diagnose and treat back pain, the rate of back surgery varies a great deal from place to place.

On the other hand, when clinicians agree on how to treat a condition, there is often relatively little geographic variation in the care patients receive. Take the example of hip fracture. Diagnosing a broken hip is not difficult, and all physicians agree that patients with a broken hip must be hospitalized and undergo a procedure to repair it.”

The goal, then, seems to be to establish consensus on treatment.  For many conditions, however, a consensus may develop but this consensus may decide that treatment should vary depending on the severity of the disease.  In this case, even if a consensus is established, physician preferences will still play a large role since they are the ones who determine the severity of each condition.

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Is there really large differences in Medicare Spending across states?

March 30, 2011 in Health Reform, Medicare, Supply of Medical Services | 2 comments

Research by the Dartmouth Atlas team has indicated that Medicare spending is concentrated regionally.  States such as Florida spend much more per beneficiary than do doctors who treat similar patients in low cost states like Minnesota.

A recent paper by Reschovsky and co-authors, however, has determined that variation in supply-induced demand is not a major driver in regional variation in health care costs once one controls for health status at the beneficiary level.  Read more to find out how the authors came to this conclusion.

Read the rest of this entry »

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Regional Variation in Diagnosis Frequency

May 18, 2010 in Medicaid/Medicare, Supply of Medical Services | 1 comment

For many years, the Dartmouth Atlas has chronicled how variation in medical resource use across the country.  Despite glaring differences in the cost and volume of care across the nation, regions with higher health care costs do not necessarily have better health outcomes.

However, medical treatment is a two step process.  First, the physician must diagnose a disease, and next the physician must decide the course of treatment given the disease the patient is assigned.  Thus, the reason regions have more intensive use of medical services could be 1) they are more likely to diagnose patients as having a more severe disease, or 2) they are more likely to use more expensive medical services in the treatment of that disease.

A recent paper in the New England Journal of Medicine does find that there is significant regional variation in how patients are diagnosed.  Simply examining regional variation in diagnoses may simply indicate that one region has more sick people than another.  To get around this problem, the authors examine what happens when Medicare beneficiaries move.  As people age, they are more likely to become sicker and thus accumulate more diagnoses.  However, individuals who moved to high cost regions were more likely to acquire more and more serious diagnoses than those who moved to lower cost regions.

To determine diagnose severity, the authors used Hierarchical Condition Categories (HCCs)–which Medicare uses as a risk adjustment mechanism to reimburse Medicare Advantage managed care plans–to create a risk score. Ranking individuals by risk score quintile,  this chart clearly shows a trend that when individuals move to higher cost regions, they are more likely to accumulate more diagnoses and increase their HCC risk score.

The authors conclude by pointing out the following:

“A major concern about both payment reforms and performance-measurementinitiatives is their potential for adversely affecting behavior. For example, if providers are more highly compensated for treating patients with more diagnoses, they could conceivably be inclined to perform more intensive screening and diagnostic testing, with clear effects on costs and uncertain effects on health outcomes.”

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Medicare Regional Variation in Service Use may be Exaggerated

February 3, 2010 in Medicaid/Medicare, Supply of Medical Services | 1 comment

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.”

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.

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High spending regions do not have better quality health care

January 14, 2009 in Supply of Medical Services | 1 comment

From the researchers at the Dartmouth Atlas of Health Care:

“Regional differences in Medicare spending are largely explained by the more inpatient-based and specialist-oriented pattern of practice observed in high-spending regions. Neither quality of care nor access to care appear to be better for Medicare enrollees in higher-spending regions.”

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Can HilaryCare end regional variation in healthcare spending?

February 18, 2008 in Current Events | Permalink

Michael Cannon of Cato-at-Liberty cites a study from the Congressional Budget Office (CBO) that it is difficult for centrally planned medical care to eliminate local norms.

“…the centrally budgeted VA system does not display much less geographic variation in spending than is exhibited in the unbudgeted Medicare program . . . . In addition to exhibiting geographic variation in spending, the VA system shows substantial variation in patterns of clinical practice despite the fact that VA’s management tracks providers’ compliance with national guidelines for the treatment of many medical conditions . . . . The implication is that local norms can influence practice patterns, even in a relatively centralized system that places a strong institutional emphasis on adherence to clinical guidelines for care”

Cannon also concludes that pay-for-performance mechanisms may have a similar difficulties eliminating regional variations.

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