Transforming healthcare revenue cycle performance takes more than a focus on days in accounts receivable, a metric that reflects the speed with which reimbursement is collected from health plans. To truly overhaul revenue cycle management, hospitals must start with a primary predictor of performance: their clean claim rate.
A hospital’s clean claim rate reflects the percentage of claims that are free of mistakes upon submission, include all required information and are submitted within the time period established by the payer. HFMA’s MAP Keys, the industry standard for healthcare revenue cycle benchmarks, calculates the clean claim rate by dividing the number of claims that pass all edits without manual intervention by the total number of claims accepted into the claims processing tool for billing.
Typically, a hospital’s clean claim rate falls between 75 percent and 85 percent. It is largely viewed as the quality of claims-related data collected and reported. But elevating an organization’s clean claim rate takes more than a careful review of the user errors that impact this percentage. Here are four strategies to consider.
Dig deep into bypassed claim edits
Increasingly, hospitals use claim scrubbers to prompt billing staff for edits prior to claims submission based on payer rules, identification of missing information, eligibility checks, and more. But a close look at the data behind an organization’s clean claim rate may indicate that some billers are bypassing the claim edits. In these instances, claims are submitted before corrections are made. The result is a lower-than-expected clean claim rate.
One way to tackle this challenge is to develop scorecards for individual employees that detail their performance against key metrics, including their rate of bypassed edits. Then, reiterate expectations for revenue cycle processes. Doing so will decrease the rate of bypassed edits and strengthen financial performance. Be sure to check in with staff monthly to review performance, keep expectations top of mind, and celebrate successes.
Implement tools to stay ahead of payer rule changes
Billing rules for health plans are complex and inconsistent from one payer to the next—and they change rapidly. In the next five years, we’ll see the use of machine learning to identify changes in payer rules before they are widely known. In the meantime, with more than 100,000 payer rules to keep track of, hospitals must update these rules weekly to protect their clean claim rate. Look for automated solutions that actively monitor changes in payer rules and prompt billing staff to incorporate these rules in claims prior to submission, minimizing rejections and denials.
Shore up registration and eligibility processes
Registration and eligibility errors account for nearly 25 percent of denials—and most of these denials are preventable. Consider equipping front-end staff with “intelligent guidance” to capture the data needed to support clean claims, such as tools that can verify patient demographic data in real time. These tools alert staff to errors in patient information at the point of registration and check-in, while patients are still available to prompt for corrections.
Automating eligibility checks during registration also improves clean claim rates. One tip is to run a second eligibility check right before claims submission. Sometimes, a patient’s coverage may change between the point of registration and care delivery. If these instances aren’t caught before claims submission, the claim will automatically be rejected. Running a second eligibility check on the back end increases the chances of a clean claim while keeping days in A/R low.
Manage problem payers
There are significant differences among national health plans when it comes to key performance indicators (KPIs) such as initial denials rates, days in A/R, requests for medical necessity documentation, and more, researchers for Crowe Horwath found. Implementation of a claims analytics solution enables revenue cycle leaders to compare payer performance by KPIs and more effectively manage payer contracts. It’s an approach that enables team members to spot changes in payer behavior, such as increased requests for documentation by DRG, and respond proactively (for example, by including the documentation in the initial claim submission). Using advanced analytics to manage payer relationships not only enhances clean claim rates, but also supports reimbursement recovery.
The ability to understand variances in revenue cycle processes and payer behavior better positions leaders to improve their organization’s financial health. Using data analysis to boost clean claim rates is a solid first step toward revenue cycle transformation and sustainable improvement.