2026 Article Archive

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May 2026

Onshore to Offshore: Why Blended Medical Coding Models Have Become the New Standard

By Sabrina Yousfi, MBA, RHIA, CCS, CDIP

Nearly 80% of health system finance leaders state they will use some form of outsourcing within the health care revenue cycle in 2026. Outsourcing is increasingly being used to cope with staff shortages, mitigate rising payer denial rates, and build stability amid uncertain reimbursement forecasts. Revenue cycle outsourcing has also emerged as a strategic lever for operational resilience.

One of the areas within revenue cycle that is ripe for outsourcing is medical coding. Whether outsourced “as needed” or fully contracted out, coding services companies have been serving health care provider organizations for several decades. Outsourced segments account for 64.8% of the US medical coding market revenue, as providers increasingly move away from purely in-house models to reduce administrative overhead and help combat the 12% talent gap in the domestic medical coding workforce. What’s evolved is the location of the outsourced staff. Read more »

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April 2026

AI, Medical Records Review, and HIPAA Implications

By Elizabeth S. Goar

In February 2026, CMS awarded a $4.28 million contract to ePathUSA to conduct a two-year pilot program to test the viability of leveraging AI for medical record review (MRR). The program, part of CMS’s push to modernize its medical records management infrastructure, is meant to evaluate the role of optical character recognition, machine learning, natural language processing, and other AI tools in enhancing medical documentation management and processing.

The CMS AI MRR pilot offers several anticipated benefits, says Alexandra Moylan, an attorney, shareholder, and member of Baker Donelson’s Health Law Group and Data Protection, Privacy, and Cybersecurity Team. While AI-enabled MRR has the potential to make Medicare oversight faster, more consistent, and more sustainable for payers, providers, and patients, “HIPAA compliance considerations arise when sensitive medical records are processed through third-party AI systems,” she says. Read more »

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March 2026

Unraveling the Web of Sjogren’s Disease

By Barbara A. Rubin MEd, RHIA, CHIP

One of the marketing points to replace ICD-9-CM, with ICD-10-CM, was that ICD-9 was running out of space to add diseases and conditions or even expand related additional digits to a current code. Sjogren’s disease and dry eye are one of those examples. They are two separate conditions and should not be classified as one condition. However, old habits are truly hard to break.

It became common knowledge, even to patients, that “dry eye,” which is not a standalone condition or disease but is a symptom of Sjogren’s, was placed in the same category. The result was all conditions, whether they were dry eye or more complex like Sjogren’s, became known simply as dry eye syndrome and hence fell under the dry eye symptom, not the more crucial disease of Sjogren’s. Read more »

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February 2026

AI and Health Care Cybersecurity Risk

By Elizabeth S. Goar

The downside of the transformative impact of AI on the health care landscape is its impact on provider organizations’ cybersecurity risk profiles. Cybercriminals are following in health care’s footsteps and using AI to improve their workflows, eg, automating reconnaissance, crafting more effective phishing messages, and altering attack vectors.

And both sides are honing their weapons: The bad guys can now use AI to alter code in real time to avoid detection, while the good guys are working on entropy-based anomaly detection to flag early stages of ransomware encryption. As a result, cybersecurity is now about pitting adaptive algorithms against adaptive defenses. Read more »

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January 2026

Generative AI in Value-Based Care and Risk-Bearing Organizations

By Anil Patil

Value-based and risk-bearing primary care practices are under rising expectations to deliver outcome-based care at lower cost while managing increasingly complex populations and patients with multiple chronic conditions. Unlike fee-for-service environments, success for these organizations hinges on proactive, coordinated, and data-driven care delivery. Yet clinicians and care teams remain overwhelmed by administrative work, fragmented data, and reactive operational and technology workflows. Generative AI (GenAI) is emerging as a powerful enabler in the care models—not by replacing clinicians or admin staff, but by optimizing their ability to identify risk, close care gaps, engage patients, and act at the right moment. When applied thoughtfully, GenAI can help value-based and risk bearing practices align clinical outcomes with economic performance. Read more »