Navigating the complexities of risk adjustment

Analyzing plans performance

Data from CMS settlements between benefit years 2020-2023 reveal that some plans have significant opportunities to reduce their owed settlement amounts. Recent national settlement numbers owed by plans indicate an upward trend in the individual market, while the settlement for group plans remains steady.

Figure 1 - PY2023 financial settlement

Using PY 2023 as an example, 190 Plans (HIOS IDs) paid an average of $45.5M back to their individual regional pools to offset expenditures by their competitors in the same market.  

Of the plans represented in the above chart, 156 Group and 79 Individual plans have owed money at the time of settlement for each plan year (2020 – 2023).

The risks of sub-optimal risk adjustment

The implications of a poorly managed RA program can be significant. Plans may need to increase premiums to offset losses, potentially reducing their competitiveness within their regions. Additionally, unanticipated large payouts can hinder a plan’s ability to expand and/or innovate, necessitating frequent reviews of long-term strategic planning. In extreme cases, continued mismanagement of risk adjustment may lead to insolvency and exit from the marketplace. 

Opportunities for improvement

On a positive note, subpar RA performance often stems from multiple contributing factors, providing numerous opportunities for analysis and targeted enhancements. Payers should focus on common issues such as missing or inaccurate diagnosis codes, enhancing patient clinical documentation, and ensuring the accuracy of data submissions. 

Historically, these efforts required substantial resources; however, advancements in technologies—such as artificial intelligence (AI) and machine learning (ML) tools—can significantly enhance a plan’s RA program. For example, ML algorithms can identify potential coding gaps and predict future health risks. At the same time, natural language processing can extract relevant information from unstructured clinical notes to support coding accuracy.

Moreover, plans can now broaden their data sources beyond traditional medical charts and electronic health records (EHRs). By integrating data from mobile health technologies and wearable devices, Payers can engage enrollees and gather real-time health information, enhancing the accuracy of risk profiles. This multi-faceted approach, combining cutting-edge technology with diverse data sources, enables health plans to optimize their RA strategies more effectively and efficiently than ever before.