There’s a lot that goes into patient-centered healthcare. And as we’re currently experiencing, there’s even more that goes into creating the infrastructure to support it. Improved data access, interoperability and an overall realignment of systems are just a few of the many parts that must come together to create a whole-person framework, but it’s a rudimentary commitment to innovation that’s going to drive the level of value we’re looking to achieve.
Innovators of healthcare technology are continuously searching for new ways to do more with less — to eliminate waste in the system without exacerbating the already heavy administrative burden placed on providers and payers. This commitment has given way to a cutting-edge approach to healthcare payment accuracy in which episode-of-care claims data is being used to better understand the patient journey throughout the healthcare system and reveal medical coding discrepancies with unprecedented accuracy and efficiency.
Episode-Based Payment & Claims Review
As providers work to care for an aging population with a growing number of comorbid conditions, ensuring healthcare services are accurately coded, billed and paid for is an increasingly complex and multi-layered endeavor. For payers, identifying billing inaccuracies pre- and post-payment requires a robust financial review process, often involving a clinical assessment of claims data against medical records, which must be requested from the provider.
The concept of episode-based models — in which resource use is measured by grouping all of the services rendered around a specified condition or procedure — is a promising development in the effort to deliver less fragmented, more efficient care. By bundling payments into episodes, providers are incentivized to increase the quality of care through better integration of healthcare services and improved management of resources.
From a cost containment perspective, employing an episode-based approach to the claims review process provides a new way to follow the patient journey — from trigger event to post-acute care — and quickly identify whether the services billed make sense within the context of the episode of care. If, for example, the hospital or facility billed for acute kidney failure while the physician billed for a urinary tract infection, a review of all relevant claims from the entire episode of care (before, concurrent with and after the claim in question) by a clinical reviewer can inform which DRG code is in fact accurate. Should the discrepancy have resulted in an overpayment, payers can pursue recovery without having to obtain a medical record from the provider.
A Semi-Automated Approach
Episode of care reviews have the potential to transform healthcare payment accuracy by facilitating evidence-based, clinical decision-making through a streamlined process, without added burden to the provider. Because decisions are made without a medical record, payers should look to solutions that combine advanced analytics with the additional oversight of a clinical expert well versed in medical coding and health information management.
HMS' Episode of Care Review solution is a first-of-its kind payment accuracy solution accelerating recoveries for payers with reduced provider workloads and abrasion. Leveraging machine learning algorithms trained over several years in the industry’s most robust claims data set, Episode of Care targets select claims for review by a clinical recovery specialist — generally a nurse or medical coder. Claims in question are then examined using an advanced clinical review platform within the context of the patient’s history to identify mismatches that resulted in an overpayment. Once a discrepancy is identified, HMS promptly pursues recovery on behalf of the payer. No medical record is necessary, except in the rare case of a provider appeal.
As we work to break down healthcare silos to deliver higher-value care, broadening the scope of the claims review process to encompass the full patient journey represents a significant step in the shift toward patient-centered care.