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Leveraging clinical perspectives to power the middle revenue cycle—insights that drive impact.

In today’s fast-moving digital healthcare landscape, staying ahead of clinical updates, coding changes, and revenue cycle trends is more critical—and more accessible—than ever. Chart Check Up, Accuity’s new podcast, brings you fresh perspectives and expert insights that make a difference where it counts: the middle revenue cycle.

Join us as we explore the latest developments with physicians, CDI professionals, and industry leaders—including Accuity’s own clinical and revenue integrity experts. Each episode dives into timely topics designed to inform and empower healthcare professionals.

Topics include:

Whether you’re a CDI specialist, coder, physician advisor, clinician or healthcare executive, Chart Check Up will keep you informed, inspired, and ahead of the curve.

Episode 1 is live now – listen on your favorite podcast platform or at https://accuitychartcheckup.buzzsprout.com/

Encephalopathy is not a single disease but a disorder of cellular metabolism. Whether it is a lack of oxygen, a chemical imbalance, a metabolic dysfunction, dysregulation, or a toxic environment, the brain cells cannot function, leading to neurological symptoms.

Although most cases are temporary, the capture of encephalopathy is critical for documentation accuracy and to capture the complexity of the patient’s encounter. To accurately translate cases involving this diagnosis into coding and avoid cumbersome denials, coders and CDI specialists must thoroughly understand what to look for in clinical documentation. Physicians can help by using precise and codable terminology in their documentation.

Unraveling a diagnosis such as encephalopathy can be a daunting task due to the numerous types and the many twists and turns it can take clinically. I’ve outlined five core concepts to help anyone navigate the complexity of an encephalopathy case.

5 types of encephalopathy

  1. Metabolic Encephalopathy is an acute condition arising from a metabolic disturbance within the body that alters mental status.
  2. Toxic Encephalopathy can appear as a result of a reaction from a prescribed medication, illicit drugs, over-the-counter drugs, or a toxin such as vapors or toxic solutions and is also considered an acute condition.
  3. Hepatic Encephalopathy arises from a form of liver dysfunction such as cirrhosis or hepatitis. It is usually accompanied by an elevated ammonia level, which is often responsible for the acute alteration of mental status.The other scenario that can occur is when a patient has a progression of their underlying liver disease, resulting in an acute alteration of mental status that is remedied by increasing specific medication regimens.
  4. Hypertensive Encephalopathy occurs as a result of an acute hypertensive episode and can serve as an end-organ dysfunction in a hypertensive emergency or crisis.
  5. Static Encephalopathy is a chronic permanent state of a patient suffering from chronic epilepsy. This is not to be confused with transient (acute) alteration in mental status (AMS) during the post-ictal state that follows seizure activity, as this is considered integral to the seizure.

Acute forms of encephalopathy occur more frequently than chronic. There are numerous terms used in medical documentation for an encephalopathic process. Still, one should also consider coding rules, clinical symptoms, and regulatory enforcement of clinical validation, which comes from the False Claims Act, meaning that there must be sufficient clinical indicators to support billing for any encephalopathy.

5 key concepts for navigating encephalopathy documentation

Encephalopathy is diffuse by nature.

Per the National Institute of Neurological Disorders and Stroke, Encephalopathy is considered a ‘diffuse’ condition, indicating that the problem occurs as a widespread pathology within the brain that can’t be pinpointed.

Imaging results are expected to be negative.

Because encephalopathy is defined as a diffuse condition, an abnormality should not be identified on imaging via CT scan or MRI.

One exception we must consider is the AHA Coding Clinic fourth quarter, 2018, page 16, which states that encephalopathy can be due to a cerebrovascular accident (CVA). CVAs are identifiable on imaging except for embolic showers, which require more time to build up the density needed to be identified on a head CT scan or MRI. Although this coding clinic’s direction appears to be the opposite of the medical definition, we cannot ignore the AHA Coding Clinic.

Many interpret it as: If the symptoms are due to direct damage (i.e. dysarthria due to fronto/temporal stroke) encephalopathy is not appropriate. However, global diffuse altered mental status due to the general dysfunction of the steady state of the brain, which dissipates after time and treatment, may be captured as encephalopathy.

Identifying the cause is necessary.

Encephalopathy is always due to an underlying etiology, so the next step after imaging is to follow working differentials to identify the underlying cause.

The underlying etiology must improve with treatment.

Once the underlying etiology is identified, the next step is to determine if the treatment for the underlying etiology improves the encephalopathic process that resulted in an altered mental state.

If the patient’s alteration in mental status (AMS) does not improve once treatment for the underlying condition is implemented, there are two possibilities. Either the underlying etiology is incorrect, and the treating providers must return to the drawing board and work up the clinical differentials again, or the patient doesn’t have encephalopathy, and something else is happening.

The patient must return to mental status baseline.

The last core concept is that if the patient’s mental status has improved once treatment for the underlying cause was treated, the patient should return to their normal mental status baseline.

When a patient with dementia is admitted for AMS, a dementia baseline should be documented to allow for a CDI specialist to measure the patient’s return to baseline. This core concept is the clinical validating piece that supports the diagnosis of whichever type of acute encephalopathy is being addressed.

Conundrum cases

I can’t speak about encephalopathy without addressing a few twists and turns that make this diagnosis challenging to capture accurately.

One particularly challenging scenario is when a patient with dementia is admitted with an alteration in mental status. Often, the patient resides in a nursing home and wakes up altered, making it necessary to transport the patient to the emergency room, where a UTI is identified. For this class of patients, the only way to measure the return to baseline is to have a documented mental status baseline for dementia.

Another problematic scenario is when two different forms of encephalopathy are superimposed on each other. This gets tricky as one would need to identify an underlying etiology for each one to validate the diagnoses clinically.

Conclusion and additional resources

Regardless of the scenario, if the five core concepts outlined above are considered, along with referring to applicable AHA coding clinics and coding conventions, processing these cases will be more straightforward. Accuity’s clinical capture experts have created this tip sheet as an additional support tool.

The healthcare industry faces an invisible yet significant challenge: the “silent payer discount.”

The silent payer discount is a hidden revenue loss, where hospitals and health systems miss out on millions. The average health system’s silent payer discount can equal $2-$5 million for every 10,000 inpatient discharges.

Revenue “leaks” contributing to the silent payer discount are hard to identify, quantify and resolve. Even the best-performing revenue cycle teams are losing out on millions in potential revenue.

What is the Silent Payer Discount?

To provide an official definition, the silent payer discount is earned revenue, typically between 3% and  5% of the hospital’s annual net revenue, that is lost due to the complexity of accurately documenting and coding complex inpatient cases.

At a mid-size health system, this can mean a staggering $22 million to $38 million in lost revenue annually. Even hospitals with strong Clinical Documentation Improvement (CDI) programs aren’t immune to these losses, leaving health systems struggling to be fully reimbursed for the critical care they provide.

Why does this happen?

Unfortunately, the silent payer discount is a natural consequence of the status quo. It’s caused by unavoidable challenges in today’s healthcare system that are largely out of providers’ control. The three main causes of the silent payer discount are clinical documentation issues, payer challenges, and a massive increase in patient data.

Clinical documentation

Today’s insurance system is designed to reimburse providers based on documented care rather than actual care provided. One of the primary culprits of the silent payer discount is the disconnect between physician documentation and the coding process.

Clinical documentation and coding are two different “languages.” Physicians use free-text documentation to describe the complexity of cases, but when this information is translated into codes for billing, critical details can get lost.

Physicians are focused on describing a patient’s condition, not necessarily on how their documentation impacts coding and reimbursement. In contrast, coders work within a strict framework that doesn’t always align with the nuances of clinical care.

Take, for example, a physician’s note about a “frozen mediastinum,” a situation where scar tissue makes surgery more difficult. This complexity doesn’t translate neatly into a code, and coders don’t always have the luxury of talking to the physician directly for clarity. Instead, it might be ultimately coded as simple pneumonia, missing the intricacies of the case. The result? The hospital misses out on the full reimbursement it’s entitled to.

Physicians often believe their clinical judgment should be enough to justify a diagnosis, but that’s not how the system works. Coding and documentation need to match perfectly to secure reimbursement. Queries from CDI teams can help bridge the gap, but they are often seen by physicians as challenges to their expertise rather than a tool to ensure proper coding.

Payer created challenges

The complexity of coding patient care is largely driven by payers, who benefit from the system’s intricacies. Payers control the rules for how patient care is coded and reimbursed, leading to an uneven playing field. The payers and auditors make the rules and can change them anytime, as well as audit providers for compliance. These rules also do not always take the physician’s clinical judgment into account, even though physicians are the ones experiencing face-to-face encounters with patients.

A 2021 survey showed a 20% increase in claim denial rates over the prior five years. Many of these are clinical validation denials—where a payer rejects a diagnosis based on its own clinical criteria. When a payer’s definition of a diagnosis, like sepsis or respiratory failure, doesn’t align with a physician’s clinical judgment, hospitals lose potential reimbursement.

To gain back this revenue, hospitals must dedicate resources to managing denials and navigating payer guidelines that often differ by payer and state. Documentation requirements for audits, appeals, and claims are also constantly increasing. Hospitals must invest in internal training for CDI teams and physicians to enhance documentation for complex patient cases.

This reimbursement structure causes excess stress for the healthcare systems balancing their work between patient care and avoiding the silent payer discount. It puts a lot of responsibility on the provider’s shoulders.

Increase in patient data

High-complexity cases with longer stays and more expensive treatments are on the rise. These cases generate massive amounts of both structured and unstructured data in a patient’s medical file.

Structured data is quantifiable, like a patient’s vital signs, lab results, and basic personal information like an address or zip code. This data can be easily automated and formatted into a standardized database.

Unstructured data, however, is the way the care teams communicate within a hospital. It involves free-written notes from multiple people based on their assessments of the patient’s situation. Think of how a radiologist might describe an image or how a physician will describe the intensity of a patient’s illness.

While structured data is easily quantified and coded, the majority of medical records—about 80%—are unstructured, making them harder to translate into billable codes. This increase in data requires more collaboration between CDI teams, coders, and physicians.

However, not all teams have access to a physician’s input in the coding process to bridge the gap. Without effective communication, critical information can slip through the cracks, leading to further revenue loss.

Solving the silent payer discount

These factors work together to create a silent payer discount, which benefits payers and costs providers, leaving a major impact on a hospital’s bottom line. The margins for hospitals have already been continuously decreasing due to the high cost of healthcare. One of the only ways to combat this is to avoid revenue leakage at all costs. If hospitals and health systems stay idle, there’s no chance of ending the silent payer discount.

Long-term success requires systematic efforts to bridge the gap between physicians and CDI teams. Until providers can plug the leaks mid-revenue cycle, they risk losing millions each year in lost reimbursement.

To learn more about how the silent payer discount may be affecting your health system and how you can stop revenue from slipping through the cracks, contact the Accuity team. Let’s talk.

In clinical documentation, cases often arise that are commonly difficult to accurately diagnosis and document. Coagulation happens to be a condition that is a documentation challenge for physicians and CDI teams alike. 

Accuity’s education team, Dr. Lynn Miller and Kelly Burns, CCS, were featured on the ACDIS Podcast to examine how hospitals can better identify coagulation pathways, which can manifest in multiple forms, from traumatic DIC to thrombophilia in weight loss surgery to new board coagulopathy. 

“Coagulopathy is incorrectly assumed to be a problem with clotting and increased risk of bleeding usually due to impaired clot formation,” said Dr. Miller. “But really it’s any derangement of hemostasis, which is the true definition of coagulopathy.” 

Listen to the ACDIS Podcast now.

Listen to the ACDIS Podcast to hear Dr. Miller and Kelly offer tips to help your CDI teams comb through charts for coagulopathy clinical indicators. They also dive into the importance of examining the big picture of a patient’s history and social determinants of health so that CDI teams have strong clinical background knowledge to capture this difficult diagnosis. They also offer tips to writing effective queries surrounding a coagulation diagnosis. 

Dr. Lynn Miller, a Board-Certified Adult and Pediatric Neurosurgeon, left a full-time surgical practice to join Accuity and is now leads Accuity’s education team as Director of Education. Dr. Miller earned her undergraduate and graduate degrees from Michigan State University and has Fellowship status in the American College of Osteopathic Surgeons. She also holds Board Certification in Integrative Medicine and continues to work on her Fellow status within Wilderness Medicine. This creates a nice blend of professional growth with exciting travel opportunities and family adventure, both additional favorite pastimes.

Pertinent to her work at Accuity, Dr. Miller has developed and implemented educational events and programs within academic arenas, medical facilities, and medical device corporations prior to joining Accuity’s education team. She also has extensive knowledge regarding the revenue cycle particularly from a surgical and implant perspective. 

Kelly Burns, CCS is Accuity’s education analyst. She serves as a subject matter expert in medical coding and revenue cycle management, in addition to spearheading education offerings for client coders. Her background in health information and physician directed content development enables her to be a key member of Accuity’s education team. Kelly obtained her coding education at SUNY Downstate Brooklyn and is pursing a Master of Public Health from George Washington University.

Learn more about Accuity’s customized, data-driven physician education program.