Leveraging Patient Access APIs to Optimize Risk Adjustment Efforts

Understanding the risk profile of their member population is essential for payers participating in Medicare programs. Risk adjustment allows the Centers for Medicare & Medicaid Services (CMS) to pay plans for the expected risk of the Medicare beneficiaries they enroll, instead of a simple, average amount. Still, the task remains a pain point for many health plans due to a lack of access to data that gives visibility into a member’s medical and claims history.

But thanks to new interoperability requirements enacted by CMS, entities acting on behalf of members/patients (e.g., app developers) can tap into detailed information about each member, facilitating insight into potential opportunities for risk adjustment leading to proper payment and improved care management.

The inability to document and capture actual disease burden annually could lead to inadequate patient care resources and funding to treat a payer’s patient population. Historically, payers have been hampered by their inability to acquire accurate data about new enrollees: Members report incorrect information on health risk assessment (HRA) surveys, and their clinical histories remain siloed in provider records.

Risk adjustment is a highly complex process. However, additional member-level data can support two key areas associated with risk optimization:

• Recognizing trends in care patterns to uncover potential under- or undiagnosed conditions
• Reviewing clinical documentation to ensure risk is adequately captured

This data aggregation and supplementation process ensures that per-member-per-month (PMPM) payments reflect the true costs of the plan’s population.

Fortunately, changing federal regulations put into effect earlier this year are set to usher in a sea of change related to data exchange, allowing payers to create a more accurate picture of their members’ health risks, receive appropriate payment from public payers and design care management programs that lead to improved member experience and population health.

The key to unlocking member data comes from the implementation of patient access application programming interfaces (APIs) that permit “patients to easily access their claims and encounter information, including cost, as well as a defined subset of their clinical information through third-party applications of their choice.” This requirement should open the door to longitudinal data on members (with consent).

What’s more, a future requirement for providers starting in 2023 will bring clinical data into the picture and further support payer risk adjustment activities.

Data access and risk adjustment

Access to pertinent member health information is vital to payer’s risk adjustment efforts. Considering how CMS calculates risk scores, a holistic view of a member’s data drives an opportunity to optimize risk adjustment factor (RAF) scores by ensuring that critical clinical information is documented.

A member’s RAF score is calculated using the member’s demographic traits (e.g., age, sex, diseased-disabled status, Medicaid eligibility) and documented hierarchical condition categories (HCCs; medical codes linked to specific clinical diagnoses). These attributes are weighted and added together to determine a RAF score that estimates the expected annual expenditure reflected in PMPM payments. Having historical information on hand allows yearly wellness visits to capture the relevant information about members to give CMS the information required to recalculate risk scores.

However, missing information — such as a failure to document the presence of chronic obstructive pulmonary disease (COPD) or the progression of uncomplicated diabetes to diabetic neuropathy over a single year during wellness visits — could easily lead to a decrease in a member’s risk score and associated payment because the requisite HCCs used to calculate a RAF score simply are not present.

“The plan of care must support the diagnosis for each condition listed, and the condition must be reestablished, along with the appropriate care plan, each year. In other words, the previous coding resets to zero if not reestablished,” John P. Yeatts, MD, MPH, and Devdutta G. Sangvai, MD, MBA, noted in a 2016 article on HCC coding, risk adjustment, and physician income.

With RAF scores depending on the availability and accuracy of demographic information and HCCs, payers will significantly benefit from greater insight into a member’s medical history and past interactions with the healthcare ecosystem via claims data.

“Every time a new person enrolls with a new health plan, the new payer does not have access to the historical data,” says Jonathan Shannon, Senior Director of Healthcare Strategy at LexisNexis Risk Solutions.

“They have to rely on things such as HRAs, which are directionally accurate at best,” he continues. “However, if you start to think about the relevant healthcare data that is held at various entities, health plans actually have the most longitudinal data set. They are the nexus of claims submitted by and paid to physicians, hospitals, pharmacies and so on. Now members and their representatives can access this trove of data via the patient access API.”

By leveraging the patient access API with the member’s consent, health plans can supplement self-reported information with hard data from paid claims and clinical screenings to support effective risk adjustment efforts for the populations they serve. Additionally, members can benefit from no longer having to complete assessments and other forms.

“The benefit to patients is they don’t have to fill out pages of forms while the health plan is able to have a much more holistic view of this patient coming into their plan,” adds Shannon.

For members with underreported and unreported health conditions, especially chronic conditions likely to worsen in severity over time, they stand to benefit from their health plan being able to access this data at the point of enrollment and make appropriate care services and resources available to reduce risk and adverse health outcomes.

The challenge is now on health plans to leverage new technical capabilities to access existing member information and create an accurate picture of health risk among their member populations. With longitudinal information in hand, payers will be able to support their members in achieving positive health outcomes, run their businesses more efficiently by allocating resources most effectively and engage in data-driven risk adjustment.

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The Health Care business of LexisNexis Risk Solutions combines proprietary analytics, data science and technology with the industry’s leading sources of provider, member, claims and public records information to deliver insights that improve cost savings, health outcomes, data quality and compliance.