A zombie statistic is a false or misleading statistic,
often reanimated from studies conducted many years ago and now printed as truth
Well-constructed prevalence studies on health conditions require large populations to produce statistically relevant results. The rarer the disease, the bigger the required population. The expense and effort to accurately assess the prevalence of a rare disease is beyond the reach of most study budgets. As a result, zombie-like rare disease prevalence estimates may not have a basis in reality. In addition, publications rarely segment prevalence rates by U.S. health insurance market (commercial, Medicaid, Medicare, individual) even though sometimes significant differences in prevalence may exist among different covered populations. The United States incentivizes the development of drugs to treat rare diseases through the Orphan Drug Act of 1983, which defines a rare disease as having fewer than 200,000 individuals affected.
In this article, Milliman’s Donna Wix and David Williams used real-world data to calculate the age-adjusted prevalence rate for three diseases: rheumatoid arthritis, which is uncommon but not a rare disease by the Orphan Drug Act definition; ulcerative colitis, which could be considered a rare disease depending on which source is cited; and hemophilia, for which an antihemophilic factor was approved in 2010 by the U.S. Food and Drug Administration (FDA) under the 1983 Orphan Drug Act. They then compared these results to zombie statistics commonly cited.
Healthcare providers can improve their financial performance under value-based contracts by implementing an effective contracting strategy. Milliman consultants David Williams, David Liner, and Colleen Norris discuss how providers can accomplish that by prioritizing and measuring operational and contractual elements against three core pillars: transparency, stability, and control. Here is an excerpt from their article “Building a successful value-based payer contracting strategy.”
Providers prioritize each pillar and attribute to create weights for each cell. Contractual elements are then evaluated against those pillars to produce a score for each cell. This can be either a subjective evaluation or a more rigorous analytic evaluation depending on the nature of the element. The weighted scores can be used to prioritize areas of administrative concentration and to compare payer contracts on a similar basis. This prioritization is a critical step to a successful contracting evaluation process….
…The exercise of scoring the grid identifies high-risk elements and compares contract structures from different payers that require revisions. When performed rigorously, this process brings focus that allows management to spend more time on contracts with the greatest risk and potential for improvement. Applying each pillar to specific payer contract elements identifies specific risks and creates areas of focus for providers during negotiation. However, this analysis alone does not enable providers to easily compare value-based contracts in their entirety.
The complex evaluation process is illustrated below in a simplified form. The intent of this illustration is to highlight important aspects of the decision-making process required to effectively manage complex payer relationships.
First, the contract is scored for each pillar and element cell in the scoring grid. Each contract is evaluated separately and may contain different elements. The provider may require independent help.
Second, the provider weights each cell in the grid based on priorities. These weights would likely be consistent across contracts. The provider may counsel with outside help to prioritize, but ultimately will be responsible for the focus of their efforts.
Finally, the total score is calculated by applying weights in each cell based on prioritization of the contracting elements. Figure 2 illustrates this contract-scoring approach.