Another important aspect of HCCs is that risk adjustment payment models are additive. That means values of each HCC are added together to establish the overall risk score of a member (unless a diagnosis is trumped by a more severe diagnosis in the hierarchy family, as explained above).
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Also, risk adjustment prevents insurers from discouraging sick patients from enrolling since they are compensated more for risk adjustment for sicker patients. How Does Risk Adjustment in Healthcare Work?
The “risk” to a health plan insuring members with expected high healthcare use is “adjusted” by also insuring members with anticipated lower healthcare costs.
For instance, an insurer may use premiums and risk adjustment payments to offer its members enrollment in exercise programs, case or disease management, transportation to medical appointments, and other services.
The variables that most impact one’s risk adjustment are: disability status, low-income status, Medicaid, the reason for entitlement, age, and sex. They utilize prospective modeling, meaning they use previous year data to predict cost in the current year vs. concurrent modeling, which uses current year data.
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Overview of Risk Adjustment Program • Section 1343 of the Affordable Care Act provides for a permanent risk adjustment program – Applies to non-grandfathered individual and small group plans
Agenda • Introduction. • Calibration data. • Risk adjustment model. • Variable selection. • Potential adjustments to the model. 3
Risk Adjustment Search Tool. Use the Risk Adjustment Search Tool to quickly find a hierarchical condition category (HCC) assignment. Enter the ICD-10-CM code or the diagnosis for results in three risk adjustment models — the CMS-HCC PACE/ESRD Category V21, the CMS-HCC Category V24, and the RxHCC Model V05.
The programs use a person’s Social Security number, permanent address, and medical and financial questionnaires to establish enrollment.
While most medical coders are familiar with the fee-for-service (FFS) payment methodology in which insurers pay providers based on the procedures or services performed for a patient, risk adjustment is instead how insurance companies participating in specific programs get payment for managing the healthcare needs of members based on their diagnoses.
Another important aspect of HCCs is that risk adjustment payment models are additive. That means values of each HCC are added together to establish the overall risk score of a member (unless a diagnosis is trumped by a more severe diagnosis in the hierarchy family, as explained above). Also keep in mind that no matter how many different ICD-10-CM codes map to the same HCC, the value for that category is added only once to a member’s risk score.
A risk score is the numeric value an enrollee in a risk adjustment program is assigned each calendar year based on demographics and diagnoses (HCCs). The risk score of an enrollee resets every January 1 and is officially calculated by the state or government entity overseeing the risk adjustment program the member is enrolled in. Another term for risk score is risk adjustment factor (RAF), sometimes referred to as RAF score.
Because risk adjustment programs are developed and managed by government agencies created to serve all eligible members of the public, a health insurance company cannot discriminate or purposely insure only a certain demographic of members with a limited range of expected healthcare costs.
Commercial risk adjustment was created by the Patient Protection and Affordable Care Act (ACA) of 2010 and implemented in 2014. This type of payment model serves individuals and small groups who purchase insurance through the online insurance exchange called the Health Insurance Marketplace.
Understanding Hierarchical Condition Categories is a good place to start when learning about risk adjustment, particularly from a coding perspective.
The Centers for Medicare & Medicaid Services’ (CMS) textbook definition is that risk adjustment is “a statistical process that takes into account the underlying health status and health spending of the enrollees in an insurance plan when looking at their health care outcomes or health care costs.”. In contrast, a certified medical coder would tell ...
Through this connection, not only do members receive the care they need, but their doctors can proactively manage their overall health, which increases members’ confidence in their providers. Studies have shown that engaged members are less costly and experience better outcomes than non-engaged members, and ensuring care is delivered appropriately enables the documentation that is critical for risk adjustment programs.
Payers should leverage the power of advanced analytics to not only identify how and when to reach members, but also know which providers are administering care appropriately, adhering to best medicine and coding practices, and cost-effectively addressing their members’ health care needs.
Accurate and thorough documentation is increasingly important as payers shift risk onto accountable care organizations, provider groups, and ultimately providers. This trend incentivizes providers to chart and document more thoroughly and completely while complying to best coding practices. More health plans also enable their network providers with point-of-care analytics to improve the delivery of care to their members. Ultimately, the goal of these tools for payers is to help providers “get it right the first time” and reduce the need for retrospective coding.
The goal of any provider encouragement program is to reward providers that actively reach out to the health plan’s members, ensure they routinely see members, document the members’ health records, and, if needed, close care gaps (or refer members to appropriate specialists).
To ensure member conditions are accurately documented within medical records, health plans should make use of the following five tools.
High-quality member/provider connections: enables members and providers to connect in meaningful ways to document and promote the health and care of beneficiaries
The programs use a person’s Social Security number, permanent address, and medical and financial questionnaires to establish enrollment.
While most medical coders are familiar with the fee-for-service (FFS) payment methodology in which insurers pay providers based on the procedures or services performed for a patient, risk adjustment is instead how insurance companies participating in specific programs get payment for managing the healthcare needs of members based on their diagnoses.
Another important aspect of HCCs is that risk adjustment payment models are additive. That means values of each HCC are added together to establish the overall risk score of a member (unless a diagnosis is trumped by a more severe diagnosis in the hierarchy family, as explained above). Also keep in mind that no matter how many different ICD-10-CM codes map to the same HCC, the value for that category is added only once to a member’s risk score.
A risk score is the numeric value an enrollee in a risk adjustment program is assigned each calendar year based on demographics and diagnoses (HCCs). The risk score of an enrollee resets every January 1 and is officially calculated by the state or government entity overseeing the risk adjustment program the member is enrolled in. Another term for risk score is risk adjustment factor (RAF), sometimes referred to as RAF score.
Because risk adjustment programs are developed and managed by government agencies created to serve all eligible members of the public, a health insurance company cannot discriminate or purposely insure only a certain demographic of members with a limited range of expected healthcare costs.
Commercial risk adjustment was created by the Patient Protection and Affordable Care Act (ACA) of 2010 and implemented in 2014. This type of payment model serves individuals and small groups who purchase insurance through the online insurance exchange called the Health Insurance Marketplace.
Understanding Hierarchical Condition Categories is a good place to start when learning about risk adjustment, particularly from a coding perspective.