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Equian: The Right Amount Paid to the Right Party at the Right Time

CIO VendorScott Mingee, CEO
Errors in claim payments and inaccuracies have historically been an area of concern for the healthcare industry. Previously, the process for identifying inaccuracies mainly focused on fraud, but now it has expanded to a wider range of improprieties in the claims processing lifecycle—broadly termed as payment integrity. However, a large set of data is sorted through while looking for errors and technologies such as data analytics make the process faster while providing actionable insights. Making it their mission to deliver actionable data is Equian—a payment integrity company for payers or fiduciaries, who through their A2 initiative—automation and analytics—deliver products and services focused on identifying payment errors. Equian’s solution ensures the recovery of inaccurate transactions, thus, reducing the cost an organization loses in a claims process.

“We analyze healthcare and insurance data to ensure payments are fair, accurate, and paid by the correct party— saving billions of dollars for our clients every year,” explains Scott Mingee, CEO of Equian.

Equian’s payment integrity value chain includes pre-and post-payment solutions that detect data inconsistencies before and after a payment failure occurs. The vast sets of data generated in the process of identifying errors are highly complex and come with customer specific attributes. Equian’s A2 methodology analyzes data to simplify the complexities and improve the productivity and efficiency of their client’s business. Further, the company’s solution also creates unique tags that derive new fields and attributes to run algorithms or content.

At its core, Equian employs a proprietary Total Claim Score (TCS) Engine, which changes the game for overpayment audit programs.

We analyze healthcare and insurance data to ensure payments are fair, accurate, and paid by the correct party


The engine rapidly assesses a full universe of claims and identifies the optimal subset for audits, which means fewer records have to be audited and financial results are improved. Using the same functionality, Equian helps health plan providers identify ongoing and complex reimbursement errors, quantify overpayment, recover revenue, and address root cause systemic and procedural errors.

Mingee gives an example where they helped a medium-sized regional health plan reduce their annual claims expense in response to changing health reforms and competitive market conditions. Using the latest in NLP, RPA and Machine Learning a determination of medical claims reimbursement accuracy was conducted which included adjudication errors, billing and coding errors, overpayment identification, and recovery and process improvement opportunities. The plan’s vision to develop a centralized mode of operations for claims processing was challenged by the decentralized nature of their overpayment identification efforts across various departments. Equian addressed several issues with the existing claims and data extracts that were utilized for reimbursement analysis and overpayment identification. Not only did Equian recover more overpayments, but it also uncovered the root cause of the errors, quantified the opportunity, and delivered the corrective action plans needed to avoid the errors in the near future. The result was a significant reduction in overpayment errors, successful identification for ways to reduce large spending, and higher overall reimbursement accuracy that further reduced administrative expenses.

Over the years, Equian has leveraged novel techniques to continuously fine-tune its algorithms to identify even minute inconsistencies and enrich the existing data to benefit their clients. Going forward, the company will be monitoring the available technologies to offer state-of-the-art insurance analytics solutions. Mingee informs, “Our market is constantly changing and we are investing in various analytics applications and new product lines that will continue to benefit payers or fiduciaries in our markets.”