Client News Coverage

Used by the Centers for Medicare and Medicaid Services (CMS) and commercial payors to forecast medical costs for patients with more complex healthcare needs, the HCC risk adjustment model measures relative risk due to health status to determine reimbursement levels. The more complex the patient's medical needs, the higher the provider's payment.

HCCs are now the preferred method of risk adjustment for the Medicare population which, according to figures from CMS, includes nearly 60 million people on both Part A and Part B, approximately 30.2 million of whom are enrolled in a Medicare Advantage (MA) plan. Thus, doing it correctly is crucial to Medicare providers and payors who wish to be appropriately reimbursed for the care provided to patients and beneficiaries.

BC Advantage»

What would happen if you had a medical emergency? Would the emergency room doctors know what medications you are taking? Would they know about your allergies? Would they know about your pre-existing conditions that might skew your blood work? Would they know who your emergency contact is? And would that emergency contact know all your important medical information to give to the emergency department staff?

Those questions kept Austinite Jennifer Devening looking for easy answers.

Austin American-Statesman»

Safeguarding revenues in the coming year requires healthcare systems to proactively navigate an evolving landscape with cross-functional collaboration, technological innovation, and increased AI investments. Additionally, going into 2024 operational excellence is the table stakes for healthcare organizations to improve bottom lines, and where AI and automation can provide a boost in productivity and costs.

Those are the high-level findings of MDaudit’s 2023 Benchmark Report on the trends, challenges, and opportunities encountered by U.S. healthcare organizations, which analyzes auditing, charge analysis, and denial assessment data from MDaudit’s network of more than 650,000 providers and 2,200 facilities. Insights are also from auditing professional and hospital claims totaling more than $5 billion and denials from commercial and government payors exceeding $150 billion.

Autonomous coding is an AI-driven leap forward from traditional Computer-Assisted Coding (CAC) systems, promising transformation for labor-intensive and error-prone coding processes in healthcare, with substantial benefits in terms of cost savings, efficiency, and reduced denials. However, to optimize its value and protect investments in coding solutions, healthcare organizations must understand the realities and limitations of this evolving technology.

Last week, the Medical Group Management Association (MGMA) suggested that federal regulators use corrective action plans and education to remedy information-blocking allegations instead of significant financial penalties. Now other stakeholders, including the EHR Association and Civitas Networks for Health, have weighed in with their concerns and suggestions for improving the final rule. 

Information blocking is when a provider knowingly and unreasonably interferes with the access, exchange, or use of electronic health information except as required by law or covered by a regulatory exception.

More organizations are releasing their comments to the Office of the National Coordinator for Health Information Technology, Centers for Medicare & Medicaid Services and Office of the Inspector General on the proposed federal rule to establish disincentives for information blocking by providers under the 21st Century Cures Act.

Most of the disincentives are aimed at providers participating in CMS programs, which some organizations like the American College of Radiology say is the appropriate mechanism for provider disincentives.

Finance leaders are battling the rising denial headwinds that threaten to derail the progress healthcare organizations have made toward stabilizing revenues after years of operating in the red. For many, the solution is an optimization of financial clearance and other patient access processes. Doing so, however, is often hampered by staffing and outdated technology limitations that impede efficiencies and increase front-end authorization errors – errors responsible for more than half of all claim denials.

However, as artificial intelligence (AI) and automation embed more deeply into healthcare revenue cycle management (RCM), a new subset of tools has emerged that can accelerate and streamline prior authorization, eligibility and benefits determination, and other back-end financial clearance workflows. Early adopters are reporting numerous benefits, most notably:

AI has become a fixture in healthcare revenue cycle management (RCM) as finance leaders seek to provide a measure of relief for overburdened, understaffed departments facing unprecedented volumes of third-party audit demands and rising denial rates.

According to the newly released 2023 Benchmark Report, growing investments in data, AI, and technology platforms have enabled compliance and revenue integrity departments to reduce their team size by 33% while performing 10% more in audit activities compared to 2022. At a time when RCM staffing shortages are high, AI provides a critical productivity boost.

Unite.AI»

Identity queue management is an important aspect of an effective value-based care strategy. It lays the foundation for establishing an effective person index, minimizing overlays, and facilitating streamlined care coordination. Left unresolved, backlogged work queues can have costly implications for patient care and safety, as well as revenue integrity.

However, many provider organizations are struggling to stay ahead of burgeoning identity error queues, with health system clients reporting that weekly error tasks have more than doubled. At one health system, the volume of potential overlays queue swelled from 2,000 per week to more than 5,000 per week over the course of just a few months, while another organization found itself dealing with a backlog of 100,000 identity interface errors. The health information management (HIM) director at a third health system shared that his team evaluated up to 400,000 potential overlay tasks in the last year to identify just 60 true overlays.

Optimizing financial clearance and other patient access operations is an important aspect of any strategy to offset revenue cycle issues that are behind more than half of all claim denials. Healthcare organizations struggle to do so, however, thanks to staffing and technology limitations that impede efficient operational processes and increase front-end authorization errors.

Those barriers are starting to crumble as artificial intelligence (AI) and automation become more deeply embedded in healthcare revenue cycle management (RCM). Of particular note is the emerging subset of tools designed to streamline and expedite aspects of financial clearance operations, including eligibility and benefits determination and prior authorization processes. Early adopters of these intelligent authorization tools are reporting rapid return on investment (ROI), including 70% to 85% faster eligibility and benefit determination and 85%-90% improvement in authorization determination time.

The Office of the National Coordinator for Healthcare Technology has completed its final health IT certification rules and the U.S. Health and Human Services Agency has sent the document to the Office of the Federal Register for publication.

The Health Information Management Systems Society and Electronic Health Record Association weighed in with initial thoughts on the industry's concerns voiced during the comment period.

With approximately half of all denials resulting from front-end revenue cycle issues, optimizing patient access operations – in particular financial clearance processes – is crucial to the financial health of today’s hospitals and health systems. For many, achieving that goal has been hindered by staffing and technology limitations that impede efficient operational processes and increase front-end authorization errors.

However, as artificial intelligence (AI) and automation make their way deeper into healthcare revenue cycle management (RCM), we are seeing an emerging subset of tools capable of streamlining and expediting many aspects of financial clearance operations including eligibility and benefits determination and prior authorization processes.

The finding from the latest “MDaudit Annual Benchmark Report” found that external payer audits rose significantly compared to last year as Recovery Audit Contracts (RACs) and Medicare Administrative Contractors (MACs) sought to reign in overpayments made over the last two to three years. Additional Documentation Request (ADR) letters also became longer, with some providers reporting ADR letters over 100 pages long.

The report said long ADR letters can make it challenging for providers to parse and file appeals in a timely manner, putting healthcare revenue at risk.

MDaudit recently released its 2023 Benchmark Report on the trends, challenges, and opportunities being encountered by healthcare organizations in the United States.

Crucial needs emphasize that healthcare systems must proactively navigate an evolving landscape with cross-functional collaboration, technological innovation, and increased artificial intelligence (AI) investments to safeguard revenues. Going into 2024, operational excellence is the table stakes for healthcare organizations to improve bottom lines – and where AI and automation can provide a boost in productivity and costs.

MDaudit announced today the release of Service Provider Workflow. This latest enhancement to its industry-leading billing compliance and revenue integrity platform supports billing when rendering providers differ from service providers, reducing audit risks related to the billing of split/shared services.

Under changes to its Evaluation and Management (E/M) guidelines, the Centers for Medicare and Medicaid Services (CMS) require split/shared services — which are performed jointly between a physician and a non-physician practitioner (NPP) in the same group and in a facility setting — to be reported by the clinician who performs the substantive portion of the patient visit.