Hierarchical Condition Categories (HCCs) are a component of risk adjustment coding used by Medicare Advantage Plans, Accountable Care Organizations, and commercial payors to forecast healthcare costs.
A risk adjustment code diagnosis HCC is essential to generating RAF scores for reimbursement purposes. With this, the resulting patient score could be accurate, resulting in underpayments to a healthcare provider.
HCCs (hierarchical condition categories) are part of CMS’s risk adjustment process, which is used to modify Medicare Advantage payments and Medicare prescription drug reimbursements. Healthcare providers must identify and document patient diagnoses that map to an HCC to ensure their patients are properly identified for risk adjustment.
Identifying and identifying HCCs in your patient data can be done in several ways, but most commonly involves reviewing an HCC crosswalk. The crosswalk lists all ICD-10-CM codes that are relevant to a particular HCC. These codes are grouped by category and can be accessed via the crosswalk or an HCC spreadsheet in your EHR.
However, accurate coding and documentation can also positively affect a patient’s overall HCC score. Physicians must be very careful when capturing these codes since the RAF score is often the key basis for reimbursement.
A health provider’s coding and documentation must be specific to each face-to-face encounter and patient’s medical history. This means ensuring that every diagnosis is documented in the medical record and includes an accurate progress note, HPI, physical exam, and medical decision-making.
This is especially important if your practice involves a risk adjustment program, as your HCCs will be the primary payment source. You need to properly document these HCCs to ensure you get significant money for your patients.
Developing an HCC coding cadence and using all your resources to improve coding accuracy and specificity is essential. Refrain from relying on simple recapture tools, which will always miss RAF scoring opportunities.
Identifying Co-Existing Conditions
The risk adjustment coding process involves analyzing medical records to determine the underlying health status of a patient. This information is used to assign a Risk Adjustment Factor (RAF) score that helps predict healthcare costs and manage capitated payments for the following year.
Hierarchical condition category coding is a key part of this process. It provides a means of communicating complexity to help the entire healthcare team better understand patients and their conditions, which can improve quality and cost performance metrics.
It also helps the health plan more accurately assess risk and allocate capitated payments for medical services based on a member’s clinical risk factors. Using this data, the health plan can more effectively reduce avoidable hospitalizations, improve members’ health, and achieve greater financial rewards.
Providers and their staff must document all the relevant information in the patient’s medical record to identify co-existing conditions for risk adjustment coding. This includes information about the current and past treatment of the disease or condition. It also includes the diagnosis, the severity, and the length of time the disease or condition has been present.
Physicians can use this information to create patient charts with all the necessary details for accurate coding. This documentation ensures that health plans receive the correct diagnosis codes and a clear picture of a member’s overall health and medical history for risk score calculation.
To successfully implement a risk adjustment coding program, physicians and their staff need to be trained in best practices for coding and re-coding diagnoses. It is also essential to conduct routine medical record audits for proper documentation and re-coding.
Achieving this level of medical documentation accuracy is a challenge. To make it easier to meet this goal, many health plans offer incentives for their members to connect with their physicians and follow up on their health status through wellness visits or annual physical exams.
Risk adjustment coding is an important part of Medicare Advantage, and Medicaid plans to forecast expected costs for healthcare accurately. By identifying high-risk patients, providers can ensure they provide the right care and maximize revenue for their organizations.
The key to success with coding is accurate and thorough documentation that conforms to best practice guidelines for the HCC program. This ensures the health plan’s medical burden is represented in members’ encounters and reflects their true clinical needs and outcomes.
In addition to coding the actual diagnosis, physicians and eligible non-physician providers must document treatments for these conditions. This includes monitoring signs and symptoms, assessing or addressing test results and meds, counseling and patient education, and reviewing records.
As a result, a physician’s documentation is more detailed and specific than previously required with the adoption of ICD-10-CM codes. For example, coding for cytomegaloviral disease requires more detail and specificity than previous iterations of codes.
Likewise, the coding for chronic kidney disease (CKD) is more detailed than previous iterations of codes. For example, a physician’s documentation might state that CKD is present in stages 1-2 or 2-3, if the coder does not have a query from the provider, they may choose the lower stage.
This makes it vital for providers and payers to understand the importance of ensuring the correct coding and documentation to predict the future cost of care accurately. This is especially important as payers shift more risk to the accountable care organization, provider group, or provider themselves, requiring that they chart and document more thoroughly and completely while complying with best coding practices.
To properly assign the risk adjustment factor (RAF) score for each Medicare Advantage member, physicians, and eligible non-physician healthcare professionals must thoroughly report on each patient’s diagnoses. This means they must be based on clinical medical record documentation from a face-to-face encounter.
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