Incomplete or inaccurate data from provider claims impacts risk scores
Health plans are held accountable for the accuracy of data submitted to CMS. Often, plans act as data aggregators and submit data generated by providers and third-parties to CMS. Incomplete or inaccurate diagnosis data may lead to overpayments or underpayments depending on the nature of the data discrepancy. Both scenarios pose undesirable impacts to appropriate revenue or compliance. For many health plans, conducting chart reviews for every encounter is not feasible. Therefore, a targeted and systematic approach to identify and remediate root causes of provider data issues is required to drive data submission completeness.
Here are three areas to consider as your organization strives to improve risk score accuracy:
Applying a measured and targeted approach to verifying provider data is critical to identify and rectify root causes of data inaccuracies. ATTAC Consulting Group has the expertise to make sure accuracy of risk scores is always in the forefront of your organization’s risk adjustment program. With a pulse on the latest CMS and OIG trends and the knowledge of where to look, ATTAC is uniquely positioned to support your organization’s end-to-end risk adjustment program.
- Determine provider groups to analyze and review. As with many risk adjustment initiatives, targeting the appropriate subset of the population is paramount to achieve optimal results, and this holds true in selecting the right provider groups for a data deep dive. Most health plans do not have the resources to evaluate every provider group, so plans may want to apply an 80/20 rule and focus on a small number of larger groups that drive a disproportionately larger percent of claims data. Advanced analytics may also be employed to further refine the in-scope target list for outlier providers within a particular group.
- Evaluate professional setting diagnosis data processes. The next step is to evaluate the processes, efficacy and accuracy of face-to-face office visits. These professional-setting encounters are billed on CMS 1500 Health Insurance Claim Forms that have spots for 12 diagnosis codes. Review and evaluation of how data is placed on the bill, and if any elements are lost via edits, truncation, or data removal, is key for effective root cause analysis and timely remediation.
- Evaluate impact of claim submission timing. For health plans participating in the Affordable Care Act Marketplace, External Data Gathering Environment (EDGE) Server submission timelines occur within a relatively short eight-month window compared to Medicare Advantage data submissions that span multiple years. Due to this condensed runway, and the EDGE Server rules, timely receipt and processing of medical claims is critical to achieve optimal risk score accuracy by the April 30 submission deadline. Quantifying the impact stemming from claim submission lags and denials by provider groups is essential to mitigate any opportunity ‘left on the table.’