Technological advances and the demand for personalized and predictive therapies to improve health outcomes have led to rapid, exponential market expansion in genetic testing. As demand and utilization increase, so do the complexity and cost of managing genetic testing.
Since 2012, the number of genetic tests has increased by 1,400%, and today more than 160,000 tests are available. Thousands of code variations exist, with an average of 6.9 codes billed per test. Many health plans have 80 or more policies for genetic testing alone, several of which consist of thousands of pages and often account for 50% of all medical necessity policies. Genetic testing also accounts for 1-2% of medical spend, with the highest levels tied to prenatal, hereditary cancers, and panel tests to measure multiple genes. Research shows that $125 per test can be saved in administrative costs alone with management strategies that standardize coding, structure policies, and clarify when a test should be covered.
- Establishing a system that makes the relationship between tests and codes clear is essential to reduce variation in coding and billing for genetic tests and reduce the uncertainty that often leads to unnecessary review costs.
- Organizing policies into a highly structured database that can be coupled with machine learning provides a structure that can withstand market changes, enable clinicians to easily find policies, and lend itself to automation.
- Utilizing machine learning to map claims to a specific test, process claims, and determine if a test or coding practices meet policy requirements enables automated, integrated claim edits.
Removing the ambiguities surrounding genetic tests, codes and medical policies opens the door to a new, innovative approach that supports payers in this complex space. To learn about Magellan Healthcare’s end-to-end Genetic Testing Solution, visit www.MagellanHealthcare.com/health-plans/genetic-testing/.