Having robust and accurate policies to base payment decisions on is critical to payer business outcomes. Payers must continually translate the latest shifts in the regulatory environment, treatment options, and changing health care costs into updated policies for providers—to increase the accuracy of claims—and for clinical and coding reviewers—to make accurate, consistent, and timely coverage decisions. However, this relies on the following assumptions:

1. All reviewers are informed of, understand, and remember the latest policies
2. Policy changes are reflected in decisioning documents or tools
3. Policies are accurately and consistently interpreted in decision-making

Most payers struggle to incorporate legislative, coding, and clinical changes into policy as well as to validate that policies are consistently applied to make timely, accurate payments of claims. Furthermore, existing mainframes cannot support the granularity of payment rules needed to support complex payment decisions, inevitably leading to costly mistakes and rework. This is even more acute for those payers encouraging the transition to payment by quality, under value-based care, as incentives are tied to the validation of claims against the medical record, policies, contracts, and payment rules. Payers face pressure to widen the validation sample, yet lack the capacity to scale what is currently a highly-manual review process.

A combination of legacy infrastructure and highly-manual processes currently impact the ability of payers to make timely, accurate, and consistent payment decisions. This post will explore these challenges and how to transition to a platform that codifies clinical, coding, and payment policies into software to support more autonomous, policy-driven decision making.

How Legacy Infrastructure Impacts Policy Enforcement

Current technology supporting the claims process is highly fragmented, a combination of siloed contract and policy databases, legacy payment integrity systems, and a patchwork of add-on solutions all trying to enforce policies and rules—and none of them doing so reliably. Due to these technological deficiencies, human review remains integral to finding and resolving errors, adding to the problem. Further, manually-maintained documents and tools used to support decisioning are at risk of going out of sync with evolving policy standards.

As a result of inefficiencies in claims processing and validation, there is a significant amount of abrasion across the payer-provider relationship and impacts network ability to care for patients. Healthcare providers struggle with a 30% shortage in medical coders, reducing the capability to prepare clean claims or respond to post-pay claims corrections. These provider challenges lead to an increase in payer time and effort to support pre-pay and post-pay decisioning. Adding in more outsourced programs to support throughput can be an unsustainable solution if payers don’t first fix the root causes associated with how policies are managed and used to support decisioning.

‍

Codifying policies into software can help payers administer claims more efficiently, consistently, and accurately. McKinsey Research suggests there is a $150 billion opportunity for operational improvement within the payer industry, with 43% of tasks automatable, including in claims processing. In fact, 72% of the 25 largest US payers agree automation within claims processing offers the greatest potential cost-reduction impact.

Supporting Policy-Driven Decision Making

Payers can realize significant business opportunities by creating a single, centralized source of truth for policies backed by software that standardizes and codifies rules to minimize process variance throughout the claims lifecycle and support near real-time decisioning across:

• Prior-authorizations
  Automate the decisioning of authorization requests across care categories, providing more auto-approval rates and speed up time to care.
• Automated repricing
  Compute the right claim payment amount based on the relevant policies, payment rules and contract terms.
• Flagging claims
  Identify claims with potential discrepancies likely to contain clinical, coding, or billing errors and flag them for audit pre- and post- payment.
• Review assistant
  Provide findings and suggestions to human experts to validate and revise claims with greater speed and accuracy.

At Machinify, we build systems that address the root cause of problems, rather than applying temporary, unsustainable band-aids that don’t converge into fundamentally better solutions. Our goal is to create a source of truth that ensures payer decisions consistently reflect the latest policies, contracts, and payment rules. We work with payers to ensure that payment rules are defined objectively, with a granular level of detail, to support fast, accurate, consistent software-based decisioning with fewer disputes.

Our cutting-edge generative AI (GenAI) solution is constantly gathering feedback from decisions and audit results to better support payers and providers alike. Such a tight feedback loop, measured in seconds rather than days or months, is essential to effective care delivery and to the necessary ongoing refinement of payer policies.

To learn more about how Machinify can help automate your claims administration, please fill out this form or reach out directly to info@machinify.com.

‍