Five Questions to Ask Before Using Market Data

Posted on
March 27, 2018

Understanding and properly applying market data isn’t always straightforward

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Many hospitals and health organizations choose market data to benchmark their physician contracting rates. It’s fast, reliable, and cost effective.

However, understanding and properly applying market data isn’t always straightforward. Below are five essential questions leaders should ask as they set rates or review physician contracts.

  1. Consider sample size and participant characteristics
  2. To be effective, market data should be based on an adequate sample size. OIG Stark guidelines suggest that market data should include a minimum of five providers. Some surveys interpret five providers to mean five individual physicians; however, MD Ranger takes a more conservative approach that results in a more robust data set. We only report benchmarks comprised of at least five different hospital owners/corporations, regardless of the number of facilities they own. This results in benchmarks based on larger, more diverse, and more reliable datasets for setting physician contract rates. Many of our benchmarks include dozens of hospitals that represent rates paid to hundreds of physicians. Regardless of the data source you choose, a large sample size with diverse participants is key.
  3. Is the data collected consistently and comprehensively, and is it routinely audited?
  4. Database construction and maintenance can mean the difference between accurate and inaccurate benchmarks. Does the survey firm have rigorous collection and verification standards, and do they audit reported data? How often do they survey? Do they survey a variety of physician and hospital ownership types? Is all of a facility’s contract data collected or only ad hoc data? Look for consistent reporting methods, comprehensiveness across specialties and positions, thorough explanations of statistical calculations, and readily available demographic information on hospitals reporting data. As a subscriber-based survey, MD Ranger collects all of a facility’s data, meaning we report on the percent of facilities paying for a given service, and we ensure that a variety of facility types are represented in our benchmarks.
  5. Are the most helpful, relevant statistics reported?
  6. If the most important statistics go unreported, market data can be misleading and difficult to apply. When you know what types of organizations are included within a particular data set, you can find facilities that pay physicians for comparable services. When you are looking at surveys, make sure the hospital characteristics that are reported influence payment rates. MD Ranger has found that the most significant factors influencing rates are trauma status, in-house coverage, and facility size. Urban and rural status can also make a difference. Additionally, reporting down to the most specific physician specialty is very important. Within surgical specialties, there is a huge variation in call pay, and some variation in medical director/administrative pay.
  7. What is the distribution of rates within the data?
  8. The distribution of payment rates can be revealing, depending on the attributes of the sample size and specific data set. When looking at a distribution of market rates, observe the variance in the data. If the distribution is fairly concentrated and there’s not much difference between rates, this could suggest that rates are very consistent across markets and facility types. However, even if quantile ranges are narrow, it doesn’t mean that there aren’t significant and meaningful outliers. In a robust data set the outliers don’t impact the range significantly; however, in a large dataset the facilities over the 90th percentile sometimes represent special circumstances that may be valid reasons for higher pay. Examples might include highly specialized or nationally recognized leaders or physicians with scope of services and hours that are significantly different. If there is a much larger distribution of rates, it could mean many things. If the sample size isn’t large and the rates are widely distributed, it could indicate poor quality data or disparate situations. If the sample size is satisfactory or even large, variation could indicate many things, from a less-competitive market to variations in the types of organizations included in the data.
  9. Am I comparing apples to apples?
  10. It is important to assess the comparability of market data to the job description of the benchmarks and your facility’s position. A broad dataset of specialties, directorships, and administrative positions allows better documentation of market rates. Leadership positions, such as chief of staff or EHR/IT implementation, often do not vary by specialty. Using a rate for a specialty-specific directorship might set a rate that is not fair market value. MD Ranger reports dozens of medical directorships and coverage positions as well as leadership positions and ad hoc positions such as committees, teaching, and quality initiatives--giving its subscribers the opportunity to make accurate comparisons.


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