Health care organizations are under increasing pressure to reduce costs. An important consideration is whether revenue for risk adjusted populations, including Medicare Advantage plans, is based on complete and accurate reporting of the health of your membership. Most health plans immediately look to their risk adjustment programs, such as in-office and in-home assessments, to ensure appropriate reporting. However, many plans are now realizing the impact of data integrity and controls. In a recent survey of top health plans, Optum learned 68% feel they need to improve the quality of their encounter data. Incomplete encounter data is a leading cause of inaccurate diagnostic data reporting for Medicare Advantage plans, accounting for an average revenue loss of $63 per member per year.* In fact, encounter data quality is not only important for accurate and complete reporting, but it can also reduce costs, improve quality scores and have a positive impact on health care outcomes.
The Optum monthly webinar series, “The Path to Risk and Quality Success”, tackled this topic in our May session titled, “Encounter Data Quality and the Impact on Health Plan Profitability.” Experts from Optum Advisory Services, Mary Larson and Brian Flower, discussed the importance of encounter data quality for accurate and complete health data reporting and associated plan revenue, quality scores, medical costs and health care outcomes. Almost 200 individuals joined us, including attendees from eight of the largest Medicare Advantage plans. Here’s what these plans had to say about their encounter data:
Start with submission data
One of the market dynamics for Medicare Advantage plans driving the need for improved encounter data quality is the implementation of the Encounter Data System (EDS) submission requirements. With the move to 50% of Medicare Advantage risk adjustment score being based on encounter data, we wanted to know if attendees had done a Hierarchical Condition Category (HCC)-level comparison of their Risk Adjustment Processing System (RAPS) versus EDS submissions. More than 50% of health plans have not gone to HCC reconciliation between the two data types.
Remember, many plans built their EDS process from scratch because of the difference between RAPS and EDS data requirements. There may be different data sources for the two submissions, making it important to understand the differences between the submissions for EDS and RAPS and why each difference exists. This is an opportunity for many plans to identify and correct data dropped inadvertently that is directly impacting complete reporting.
Health plan and provider collaboration
As provider organizations are taking on more risk and engaging in new and unique contracts with health plans, the provider organizations are becoming increasingly interested in end-to-end reconciliation with health plans. Attendees were asked if they had engaged with provider groups for end-to-end data reconciliation and, if so, how many. Results were fairly well split:
Results show an opportunity for health plans to discuss encounter data quality with their provider partners and engage further in reconciliation. Optum also asked plans whether they had performed diagnosis truncation analytics on claims and encounter data. Results were split equally almost three ways from running QA analytics regularly and on an ad hoc basis to not at all. Over 30% of attendees have already implemented regular quality assurance analytics.
Data trends, such as the number of diagnosis codes submitted per claim, are a good leading indicator of a data integrity issue. Monitoring these trends on an ongoing basis is important for identifying data quality changes that can be caused by system implementations or upgrades and can be causing inaccurate revenue for your health plan.
Challenges and opportunities for health plans
Not surprisingly, based on the results to the previous questions, 68% of health plan attendees feel they need to improve their encounter data. Almost 90% agreed that data quality evaluation is important at both the provider and health plan levels. A little over a quarter of health plan respondents felt they had appropriate visibility into the data quality checks and controls impacting risk adjustment and quality performed in their organization today, signaling a clear opportunity for plans to address encounter data quality.
Four takeaways on encounter data quality
As health plans look to improve their visibility into potential encounter data quality issues, here are the four key takeaways Optum offered during the webinar:
- The quality of encounter data that a Medicare Advantage plan receives from providers through claims and encounters directly impacts its data reporting and associated revenue, as well as cost and quality. An average Medicare Advantage plan has its revenue reduced by $63 per member per year due to encounter data quality issues.
- Health plans and providers need to work together to capture and report complete and accurate diagnosis data to reflect the true health status of their population. In turn, both health plans and providers benefit from improved insights into their populations, allowing them to provide better care and drive better health outcomes.
- When thinking about capturing and reconciling encounter data, it is best to think about it in two sections: from point of care to encounter and claim data coming in the door at the health plan and from the health plan through submission to the Centers for Medicare & Medicaid Services (CMS).
- Now is a great time to evaluate the quality of your encounter data as well as clean up your data to improve third and fourth quarter risk adjustment and quality program effectiveness as well as submit a complete set of diagnosis data for the January Medicare Advantage submissions sweep.
Optum can help
Optum Advisory Services Risk Adjustment can help address concerns about the quality of your encounter data and how to improve the accuracy of your revenue and quality scores, or reduce costs. We can offer a second opinion on processes you have developed to support encounter data quality, assist in developing end-to-end reconciliation processes and reports within your health plan or with provider organizations, and evaluate data trends to determine your current risk for data leakage.
On-demand and upcoming webinars
Please visit our The Path to Risk and Quality Success webinar series page to explore upcoming topics, register for the next monthly webinar or watch on-demand one of our other webinars in this series.
If you were unable to attend the webinar on encounter data quality or one of our other webinars in this series, you may watch on-demand.
*Based on the average recovery of MA health plans engaged in the Optum Data Leakage programs to capture diagnosis data that was documented at the point of care and inadvertently dropped prior to submission to CMS.
Meet the Authors
VP and Practice Lead, Risk Adjustment Advisory Services
Brian Flower, MBA
Senior Director, Risk Adjustment Advisory Services