Prioritizing Interventions That Matter
Written by: Cheryl Reifsnyder, PhD and Katie Wilson
With healthcare’s increasing shift to value-based care (VBC), payers continue to focus more on improving the quality of their patients’ outcomes. One strategy has been identifying members most likely to benefit from “interventions”. With health plan risk adjustment programs, interventions refer to actions that maximize health opportunities, such as:
- Reminders, such as voice or text messages, email, or snail mail
- Encounter facilitations, such as telehealth consults, wellness visits, scheduling check-ups for high-risk members
- Retrospective medical record retrievals
- In-home health assessments
- Creative campaigns, such as phone calls to members offering incentives for them to complete wellness visits with primary care physicians
There is a wide range of intervention types with a wide range of costs, making it essential to choose the right intervention for each patient. In this article, we look at how risk adjustment analytics can enable precision targeting of interventions, the process of directing the right interventions to the right patients at the right time. We also examine how Veradigm’s Risk Adjustment Analytics solution enables you to make the best use of your health plan’s limited intervention budget, saving you time, money and helping improve your members’ health.
Roadblocks to selecting the right members for interventions
Successful programs demonstrating efficient allocation of resources are those which identify the highest-opportunity members for potential interventions; however, recognizing those who are highest-opportunity can be extremely difficult. In the past, identifying likely candidates has most commonly focused on those with the highest healthcare costs to predict those with future high healthcare costs; but this method is only sometimes effective. For instance, a group of members who previously had low healthcare costs contains a subgroup at substantial risk for high healthcare costs in the upcoming year. Their high risk might stem from a recent diagnosis with a high-cost condition (such as heart disease); or they might have a high-cost condition that has been in remission for the previous year; or they might be between treatment episodes (because healthcare costs tend to be episodic).
Choosing the right members for the right potential interventions requires precision targeting which, in turn, relies on accurate coding of members’ diagnoses. However, research shows that errors in diagnoses and coding are common. Studies show that ICD-10 coding in medical records can have error rates of approximately 20-50%, while more than 40% of chronic conditions are not reported at all. Of those HCC (Hierarchical Condition Category) codes reported to the Centers for Medicare & Medicaid Services (CMS), more than 30% do not pass the CMS validation process due to a lack of supporting documentation.
Precision coding
A sound risk adjustment process enables you to catch and correct these sorts of errors. That’s because good risk adjustment enables “precision coding,” which is complete, timely, and accurate. Precision coding delivers several advantages. It enables a health plan to:
- Regularly verify the presence of chronic illnesses/preexisting conditions in members, to ensure that the plan is appropriately funded for its members’ care.
- Collect evidence to help identify unconfirmed (i.e., suspected) or unsubmitted member diagnoses, to ensure that the plan is appropriately funded for these conditions.
- Assist in earlier detection of members’ health conditions, enabling more timely and appropriate care for those conditions.
- Target risk adjustment interventions more accurately and efficiently, where appropriate, while minimizing interventions with low chances for success.
Accurate diagnostic coding is essential for members, providers, and health plans. Members require accurate diagnoses to receive the care required for their conditions. Providers rely on accurate diagnoses to deliver the best possible care to their patients. For health plans, missing or late diagnoses can result in a lack of funding for the care required by those members.
Precision targeting of interventions
Precision coding is essential if interventions are going to be targeted where they will be most effective—that is, for precision targeting. Veradigm’s Risk Adjustment Analytic solution’s patented method of precision targeting is called Dynamic Intervention Planning. This proprietary approach enables a health plan to make effective use of a limited intervention budget by targeting the “best bet” combination of intervention, member, and healthcare provider (HCP), helping you to improve your members’ health while simultaneously saving money and improving coding.
Veradigm’s Risk Adjustment Analytics solution provides advanced risk adjustment algorithms built from large data sets to enable exceptional accuracy. It utilizes multiple predictive models in conjunction with Big Data mining and clinical inferencing to leverage a broad range of information. This enables it to create algorithms that weigh more variables than are generally available to individual health plans. “Data Mining” allows the algorithm to identify factors shared by members with select conditions. It can then use those factors to identify other members who might have those conditions as well.
Big Data mining enables access to and utilization of:
- Medical and pharmacy claims
- Medical records
- Lab results
- Health assessments
- Sociodemographic information, including some Social Determinants of Health (SDoH)
- Additional information typically excluded from data sets
We prioritize accuracy and transparency in the analytics we provide, enabling precise, efficient intervention targeting, prioritizing interventions and gap closure opportunities using confidence-adjusted risk scores. Using this data, we identify risk adjustment opportunities based on currently diagnosed conditions as well as conditions confirmed in previous periods that have not yet been confirmed for the current period.
We also use available data to identify “suspected” conditions: that is, health conditions that may be risk-adjustable and may be present, but do not yet have a formal diagnosis. Our “suspecting” algorithms are cutting edge, enabling us to identify more suspected conditions. These algorithms tend to identify about 90% of all the hierarchical condition categories (HCCs) in the associated charts.1
This patented targeting method provides health plans with the precise information needed to target the right interventions, to the right members, at the right time.
Veradigm Provider Engagement solutions
Identifying gaps in care is only the first step in the process; closing these gaps requires communication with the member’s HCP. Veradigm Provider Engagement Solutions (formerly Collabor8) is a solution designed to optimize payer-provider interactions to make gap closure efforts as efficient and effective as possible. Veradigm Provider Engagement solutions consolidates data from multiple risk adjustment and quality algorithms into single alerts to minimize provider burden. It helps you better engage providers by streamlining payer-provider communications, minimizing workflow disruptions, and reducing wasteful encounters.
Today’s health plans have limited budgets with which to fund interventions, making it critical to target interventions to those times and places where they will have a significant financial impact. The key to interventions that reduce waste and help improve health outcomes is to use the power of precision targeting.
Contact us to learn more about Veradigm’s Risk Adjustment Analytics and how its patented method of precision targeting can help you to select more financially advantageous interventions for your members.
References:
- Internal Data on File. 9/2023