How is comparative effectiveness research being used for decision-making in orthopaedics, and what does the future hold?
Comparative effectiveness research (CER) refers to assessing the body of evidence that compares the benefits and harms of different treatment methods. What differentiates CER from traditional medical research is that CER is demand driven. In other words, only when the demand for a procedure or technology grows to the point of significant budget impact will CER be performed. A confluence of factors at both the Federal and state level are raising the profile of CER and taking it from the academic to the health policy realm. These factors include:
- The growing role of government as the primary payer of medical services
- The pressure to reduce a ballooning Federal deficit
- State fiscal shortfalls/crises from recession-depleted coffers
- A sharp increase in Medicaid enrollees due to both the recession and healthcare legislation
- Comparative data starting to emerge from Federally funded CER projects
These price pressures, combined with emerging results that in many cases underscore a dearth of evidence supporting expensive technologies, are drawing increased attention to the power of CER to provide cover for difficult resource allocation decisions.
CER in Theory: The Push for CER in Orthopaedics
While comparative analyses between different pharmaceutical treatments have been common for some time, critical appraisals of surgical techniques and devices have rarely been performed. A major reason for the lack of rigorous comparisons in the surgical literature is, in large part, due to the difference in clearance pathways for devices. Over 90 percent of the devices on the market were clearance through the 510(k) process that requires limited evidence for clearance. This evidence is usually in the form of case series, most of which are retrospective and do not have the rigorous independent assessment of outcomes that would allow meaningful comparisons among products.
The U.S. market for spinal implants and devices used in spinal surgery grew about 11 percent between 2008 and 2009 to over $6.8 billion.1 The U.S. spine market for 2009 is about 30 times larger than the $225 million dollars reported for 1994.2 The U.S. hip and knee implant market grew 7.6 percent between 2007 and 2008 to about $6.1 billion.3 Given this continued expansion of orthopaedic volumes, calls for a more rigorous assessment of outcomes in orthopaedics are growing.
In 2007, the Congressional Budget Office (CBO) published a report on opportunities to use CER for healthcare decision-making. The CBO report includes data from The Dartmouth Atlas group showing the degree of geographic variation in treatment patterns for four orthopaedic procedures: hip fracture, knee and hip replacement and back surgery. (See Exhibit 1.) There was little regional variation from the mean in hospitalization rates for patients with hip fractures, a diagnosis that would be made with little disagreement among providers. Variation was greater for rates of hip and knee replacements, in which the decision to have surgery can be based on numerous factors. The fourth procedure, back surgery, showed the largest regional variation by far. Data such as these raise questions about the role of physician judgment and whether better evidence on the appropriateness of procedures for different patients could reduce inappropriate care and costs.
Exhibit 1: Rates of Four Orthopaedic Procedures among Medicare Enrollees, 2002 and 2003(Standardized discharge ratio, log scale)
Source: Dartmouth Atlas Project, The Dartmouth Atlas of Health Care
Notes: In the figure, each point represents a hospital referral region; the country was divided into about 300 such regions on the basis of where Medicare enrollees typically receive hospital care. The points indicate how the rate at which the procedure is performed (per 1,000 Medicare enrollees) in each referral region compares with the national average rate (which has been normalized to 1.0). Differences in procedure rates were adjusted to account for differences among regions in the age, sex, and race of enrollees and for measures of illness rates.