Mastering CDPS Risk Adjustment Categories: A Comprehensive Technical Guide

Revolutionizing Healthcare Data Management: Traditional Rules Engines vs. Advanced Generative AI Techniques
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I. Introduction

The Chronic Illness and Disability Payment System (CDPS) is a diagnostic-based risk adjustment model extensively used in Medicaid programs to adjust capitated payments for health plans enrolling Medicaid beneficiaries. Here’s a comprehensive overview of the CDPS model, including its development, methodology, and application, which could be particularly informative for health insurance executives: 

II. Overview and Purpose of Risk Adjustment

Risk adjustment is a statistical process considering the underlying health status and health spending of enrollees in an insurance plan. It’s essential to ensure fair payments to plans serving higher-risk populations and to discourage plans from selecting only healthy individuals​​. 


Developed initially in 2000 with data from seven Fee-for-Service (FFS) Medicaid programs, the CDPS model has undergone significant updates over the years. It uses International Classification of Disease (ICD) codes to categorize illnesses related to major body systems or chronic diseases, assigning weights within these categories that reflect clinical severity and anticipated costs. Additionally, the Medicaid Rx (MRX) system, part of the CDPS+Rx model, employs National Drug Classification (NDC) codes for assigning weights based on types of pharmacotherapy​​​​. 

IV. Application and Scoring

CDPS risk scores are calculated for individuals but applied at the group level. These scores include baseline (intercept), demographic factors (age and gender), and weights for all indicated CDPS categories. Notably, the CDPS weights are hierarchical within major categories but additive across them. This means that while an individual can receive higher scores for multiple chronic conditions across different categories (e.g., Cardiovascular and Diabetes), they would only receive the highest score for conditions within the same category (e.g., for heart failure but not also for hypertension)​​. 

V. Updates and Revisions

The CDPS model has been regularly updated to incorporate the most recent ICD and NDC codes. A major revision, CDPS 7.0, used data from 2017 to 2019 from national Medicaid managed care plans. This update aimed to reflect changes in patient treatment due to new technologies and to better represent the cost patterns in managed care, differing from the Fee-for-Service model​​. 

VI. CDPS+Rx Payment Model:

The CDPS+Rx model combines the CDPS model with prescription drug utilization data to create a more comprehensive risk score. This model integrates both diagnosis codes and National Drug Codes (NDCs), offering a nuanced assessment of an individual’s health risk.


  • Medical Claim Example: Suppose a member has been diagnosed with two conditions, heart failure (a cardiovascular condition) and type 2 diabetes. Based on the CDPS model, each of these conditions falls into different major categories (Cardiovascular and Diabetes). The model assigns a weight to each condition based on its severity and expected cost impact. The individual risk score for this member would be the sum of the weights assigned to the heart failure condition and the type 2 diabetes condition.


  • Pharmacy Claim Example: Assume this member is also taking medication for both conditions. Under the CDPS+Rx model, the pharmacy claim would be analyzed using National Drug Codes (NDCs). Each medication would be categorized based on the type of pharmacotherapy, and an MRX weight would be assigned accordingly. If the medications are for treating heart failure and diabetes, they would fall into relevant MRX Categories.


  • Hierarchy and Rank: Within each category, conditions and medications are ranked based on severity. A higher rank (more severe condition) takes precedence over a lower one.


  • Calculations
    • Prospective (PRO-Rx) Model: Utilizes diagnoses and medications from the prior period to predict costs for the next period. 
    • Concurrent (CON-Rx) Model: Uses current diagnoses and medications to estimate current period costs.


  • Combining Medical and Pharmacy Claims for CDPS+Rx Score: The final risk score for this member under the CDPS+Rx model would be the sum of:
    • The baseline demographic weight (considering age and gender). 
    • The weights for the heart failure and type 2 diabetes conditions (from the medical claim). 
    • The weights for the medications used to treat these conditions (from the pharmacy claim).

VI. Mastering Revenue Projection

Medicaid analytics entities stand to gain significantly by utilizing sophisticated risk adjustment models such as CDPS+Rx.


These models facilitate precise risk management and revenue forecasting. By offering accurate projections of capitation payments and discerning emerging trends, these entities provide healthcare providers and payers with critical insights, thereby enhancing their financial outcomes.


Moreover, such analytics can uncover areas for cost reduction and care improvement, promoting initiatives for value-based healthcare. Those who navigate the evolution of Medicaid with adaptive, predictive analytics will emerge as leaders in an increasingly competitive market, integral to strategic healthcare financial planning. 

References and Resources: 


Kronick, R., Bella, M., Gilmer, T., Somers, S. (2000). The Faces of Medicaid III: Refining the Portrait of People with Multiple Chronic Conditions. Center for Health Care Strategies. 


Richard Kronick, Ph.D., Todd Gilmer, Ph.D., Tony Dreyfus, M.C.P., and Lora Lee, M.S. (2000). Improving Health-Based Payment for Medicaid Beneficiaries: CDPS  


Pope, G., Kautter, J., Ellis, R., Ash, A., Ayanian, J., Lezzoni, L., et al. (2004). Risk Adjustment of Medicare Capitation Payments Using the CMS-HCC Model. Health Care Financing Review, 25(4), 119–141. 


3M Health Information Systems. (n.d.). Chronic Illness and Disability Payment System (CDPS). Retrieved from 

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