FEST Builds a Critical Piece of CareConnectors’ Medicare Advantage System
Medicare is the federal health insurance program primarily for people who are 65 and older. Individuals who enroll in Medicare are known as beneficiaries.
CareConnectors’ platform allows parties in the healthcare ecosystem to exchange health care data. CareConnectors enlisted FEST to implement a solution that performs Medicare risk scoring for beneficiaries who are enrolled in Medicare Advantage.
An individual, if eligible, may choose to enroll in Medicare Advantage, an alternative to the traditional Fee-For-Service (FFS) Medicare program. Under Medicare Advantage, health providers are incentivized to reduce medical costs by providing preventative care, early treatment of diseases, and better coordination of care.
For the Medicare Advantage program to work effectively, the projected cost of providing healthcare to a beneficiary must be calculated. The beneficiary’s risk score is a component of this cost calculation. The risk score is based on the beneficiary’s demographics, Medicaid eligibility, and health status. For example, a beneficiary who is 65 years old and has rheumatoid arthritis, but no other medical conditions, has a lower risk score than a beneficiary who is 88 years old, has lung cancer, diabetes, and other medical conditions.
Calculating a beneficiary’s risk score is a complex process; a linear regression algorithm is used to add hundreds of independent variables together.
Which programming language is best suited to implement the risk scoring algorithm? A statistical language could be selected. However, while statistical languages offer a lot of power, they have some drawbacks. They can be complex, making coding difficult to learn and an existing code base difficult to maintain. They may also have a high licensing cost.
CareConnectors challenged FEST to implement the risk scoring algorithm using a general programming language that would address the drawbacks of statistical programming languages.
FEST implemented the risk scoring algorithm using Microsoft Azure, Microsoft .NET, and Microsoft SQL Server. By using this technology stack, FEST built their solution on a programming platform that many developers are already familiar with. Also, usage of this stack was licensed at an attractive cost.
FEST’s implementation of the algorithm quickly calculates risk scores for beneficiaries in bulk. Their implementation supports ICD 9 and ICD 10 codes which are used in calculating risk scores. These codes classify diseases and related health problems.
Risk scoring is adjusted on a yearly basis so that beneficiary health costs can be more accurately predicted for the following year. FEST’s implementation can easily accommodate these adjustments.
FEST chose a technology stack that was appropriate for CareConnectors’ needs and implemented the risk scoring algorithm to meet their requirements. By doing this, FEST successfully tackled the challenge that CareConnectors presented to them.