In April, the U.S. Department of Health and Human Services released Report The Office of the Inspector General (OIG) announced that a Medicare Advantage (MA) organization improperly denied prior authorization and payment requests for covered medical services. The OIG report has been New York Times and other publications, are driving new legislative efforts to automate prior authorization (PA) for the MA program.
The OIG initially chose to investigate the denial investigation out of concern that the MA scheme’s capitation model, which pays private insurers a fixed amount per member, could incentivise the scheme to increase its profits by denying members access to the services they need. While the vast majority of service requests are approved by the MA program — which denied only 5 percent of all prior authorization requests in 2018 — erroneous denials can prevent or delay patients from accessing appropriate care.
To infer the incidence of inappropriate denials, OIG’s team of coding experts and physician reviewers examined a sample of 250 PA denials and 250 payment denials posted by 15 MA organizations during the week of June 2019. Investigators found that 13% of denied PA requests were for services that met Medicare coverage rules, while 18% of denied payments were for services that met both Medicare coverage rules and MA plan-specific billing rules.
Notably, the OIG found three common and easily preventable reasons for these inappropriate denials:
- First, MA organizations sometimes rely on other clinical criteria not included in Medicare coverage rules, such as requiring X-rays before more advanced imaging, which results in requests being denied.
- Second, some PA requests were denied due to lack of or insufficient documentation despite adequate documentation in the member’s medical records.
- Third, most inappropriate payment denials are due to human error or inaccurate system programming during the manual clinical review process.
1. Automated clinical intelligence
For years, efforts to fix prior authorization have focused on the digitization of existing processes. Many health plans have implemented electronic prior authorization (ePA) systems, and there has been some movement to tier providers and selectively apply authorization requirements based on past performance.
However, simply digitizing PAs doesn’t address the root of the problem, which is a fundamental mistrust in how health plans design their utilization management (UM) programs. As the MA program strives to provide members with the most appropriate healthcare services, they should utilize a system that incorporates clinical intelligence to guide high-value healthcare choices. Providers should trust health plans to evaluate these requests not to save money, but to ensure safe, necessary care for each patient.
For UM to run smoothly, the rules should be completely transparent to the provider, such as 2018 Consensus Published by six national advocacy associations. UM programs must use well-defined and referenced evidence-based clinical standards. And, most importantly, it must provide meaningful support to providers to help achieve the fastest and best outcomes for patients, which can be achieved by combining artificial intelligence with clinical intelligence. The three main reasons for inappropriate denials that the OIG team identified were easily preempted by the Smart Licensing Platform.
2. Clarify the level of clinical standards
One of the main advantages of an MA plan over traditional health insurance is its flexibility. MA plans are allowed to provide supplemental benefits, define their own high-value services, and provide different coverage for designated populations; in general, they enable a more people-centered approach to benefit design. For example, an MA plan might cover two brand-name drugs and a generic alternative, or it might provide benefits for people not normally covered by national coverage determinations or local coverage determinations (NCDs/LCDs).
However, an MA plan’s UM plan must have strict controls in place to ensure that its clinical criteria for assessing medical necessity are no more restrictive than Medicare’s criteria. This can be difficult to do without an intelligent authorization platform that provides automatic rules to preserve priority hierarchies.
For example, MA programs may choose to follow evidence-based guidelines developed by national medical associations because they provide more detailed, up-to-date guidelines than federal standards. A smart authorization platform can evaluate PA requests using the health plan’s policies, while ensuring that rules default to NCD/LCD in the event of a divergence in these criteria. Additionally, automated systems can immediately reflect and enforce policy changes as best practices evolve.
3. Fix documentation issues
Concerns about the performance of Medicare Advantage UM plans are not new. In 2015, CMS is cited 56% 140 audited MA contracts for two violations related to inappropriate denial of service requests and/or payments. Health plans were cited for making incorrect clinical decisions based on submitted information, and for failing to gather appropriate information from providers prior to making clinical decisions.
Let’s look at the documentation process. Typically, providers exchange information with five to ten health plans, each with its own authorization portal, fax process, 278 EDI process, and coverage policies, which are often opaque to providers. Physicians submit individual authorization requests for each individual care service or drug. The health plan can then take up to two weeks to review the case and ask the provider for any missing documents. Once the provider faxes the requested information to the health plan, the documentation must be manually attached to the correct authorization request before the case enters clinical review.
Given the inherent complexity of the process, it’s no wonder investigators from the Office of the Inspector General found that some authorization requests were improperly denied due to alleged lack of documentation.
In addition to providing the necessary clinical context for service requests, the AI-driven authorization platform ensures the correct completion of all PA requests—forward They are submitted. Machine learning (ML) models can parse requests as they are entered and trigger automatic prompts when expected information is omitted. For example, an ML model might detect that a doctor requesting an injection for a patient has not provided evidence of advanced imaging in the clinical record, prompting the platform to request imaging documentation before submitting the request.
4. Use AI to reduce human error
Understanding a member’s healthcare journey is more important to preventing denials and improving outcomes than most health plans realize. By taking a more holistic approach to care management, health plans can better predict, manage and approve patient needs throughout the care process. An intelligent authorization platform can extract patient-specific data from the EHR, map unstructured clinical records to the correct authorization requests, and provide health plans with a more complete patient record.
Using physician input, patient data, and historical datasets, intelligent platforms can also determine longitudinal patient journeys or care paths for various conditions, automatically suggesting additional services that may be suitable for bundled entitlements. Instead of submitting multiple disconnect requests for a single patient, physicians can obtain approval for multiple services in advance for the entire stage of care, reducing PA time and costs for providers and health plans. Such a platform could also prompt physicians to make higher-value care options when necessary, such as jumping directly to the gold-standard imaging modality, rather than requiring a series of lower-value tests.
Perhaps most importantly, applying AI to UM can improve the automatic determination rate of PA requests, as the technology can identify which requests actually require review. Smart authorization platforms can reduce rejection rates by 60% or more, while increasing provider confidence that most requests will be approved immediately. For requests that require human review, AI algorithms can quickly identify the right focus areas in the case, making the reviewer’s job faster and easier. An intelligent authorization platform can detect evidence of compliance with a health plan’s specific criteria, linking relevant text in clinical records to the plan’s policies.
As of last year, 42% of all Medicare beneficiaries were enrolled in a Medicare Advantage plan, and that number is expected to reach 51% by 2030. With the rapid increase in enrolment, Master’s programmes will face greater scrutiny of the effectiveness of their processes. Whatever happens at the legislative level, MA programs must ensure that their UM programs are built on sound principles and easily expandable to handle more requests. While MA programs will never completely eliminate human error, incorporating AI and ML into their UM practices will go a long way toward preventing inappropriate denial.
Alina M. Cheque, mph, is Vice President of Strategic Partnerships at Cohere Health, a utilization management technology company. Previously, Ms. Czekai served as a senior advisor to former CMS administrator Seema Verma and held leadership positions at Aspire Health and the U.S. Institute for Health Policy.