Title: Medicare Risk Adjustment & Hierarchical Condition Category (HCC): Coding Guide (2018-2019)
Publisher: Independently published
Publication Date: 2018
Language: English
ISBN 10: 1719832455
ISBN 13: 9781719832458
Binding: Paperback
Condition: Brand New

About this title

Synopsis

Risk Adjustment and Hierarchical Condition Category (HCC) coding is a payment model mandated by the Centers for Medicare and Medicaid Services (CMS) in 1997. Implemented in 2003, this model identifies individuals with serious or chronic illness and assigns a risk factor score to the person based upon a combination of the individual’s health conditions and demographic details. The individual’s health conditions are identified via International Classification of Diseases – 10 (ICD –10) diagnoses that are submitted by providers on incoming claims. There are more than 9000 ICD-10 codes that map to 79 HCC codes in the Risk Adjustment model. CMS requires documentation in the person’s medical record by a qualified health care provider to support the submitted diagnosis. Documentation must support the presence of the condition and indicate the provider’s assessment and/or plan for management of the condition. This must occur at least once each calendar year in order for CMS to recognize the individual continues to have the condition. The Centers for Medicare and Medicaid Services (CMS) Risk Adjustment Model includes nearly 80 HCC categories of chronic illnesses with thousands of diagnosis codes. Beginning HCC coders need solid instruction on HCC coding to properly map codes and ensure the organization receives the reimbursement payments. This webinar educates the audience on HCC coding and discusses popular risk adjustment coding guidelines. It identifies what makes a document valid for submission, including which sources of documentation should or should not be used. Attendees will have the opportunity to review common mistakes, like a lack of specificity in provider documentation. Often overlooked conditions, which are frequently undocumented by the provider, are also explained. The presenter will give a brief demonstration on how to determine if a condition is reimbursed or not, as well as a case study showing how to apply the theories learned. Through clarification of codes and specific examples, the speaker underscores the importance of provider documentation and its impact on reimbursement. This session is a great overall introduction for beginners and the perfect refresher course for those who have already begun and want to enhance their knowledge in the field. Objectives Learn about HCC coding and risk adjustment coding guidelines. Demonstrate how mapping tools help to properly identify HCCs. Understand the importance of provider documentation and its impact on reimbursement. Risk adjustment in the CMS- HCC model characteristics is based on multiple factors, which are analyzed and reduced to offer the right risk management plan for a patient. The factors that influence risk adjustment includes: Hierarchy of diseases: Ensuring that diagnoses are included in the appropriate disease groups and are in accordance with the necessary hierarchy. Disease Interactions: The additional factors that recognize and assess the severity of multiple conditions. Demographic Variables: These focus on the demographic of the patient’s living conditions and demographics. Diagnostic Sources: CMS recognizes diagnoses from a hospital’s inpatient, outpatient and physician settings only. Prospective model: The diagnoses based on last year are used to extrapolate the possible payments for the next year. Multiple conditions A patient can have multiple HCC categories assigned to them based on their medical conditions. In some cases, specific conditions can override others, when documenting. This is based on the strict hierarchy of the coding procedures. HCCs are captured once a year, every year in order for the CMS to reimburse payments to the Medicare Advantage. However, diagnoses from previous years are used to establish capitation payments to the Medicare Advantage plan.

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