Tag: senior vice president

Unlocking Optimized HCC Documentation and Coding

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Eric McGuire

By Eric McGuire, senior vice president, Medical Coding and CDI Service Lines and Corporate Strategy, AGS Health.

Traditional fee-for-service reimbursements are falling by the wayside as healthcare continues its transition toward value-based reimbursement models. This is evidenced by data from the Health Care Payment & Learning Action Network (LAN), which shows more than half of healthcare payments in 2022 were made under value-based care models. Additionally, nearly 75% of health plan leaders surveyed by LAN believe value-based care model activity will continue to rise.

Integral to this transition – which requires providers to better manage patient costs based on a clear, concise, and comprehensive picture of patients’ health and medical conditions – are Hierarchical Condition Category (HCC) codes. Used by the Centers for Medicare and Medicaid Services (CMS) and commercial payers 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.

In fact, HCCs are the preferred method of risk adjustment for the Medicare population, which includes nearly 60 million people on both Part A and Part B, CMS reports. As such, accurate HCC management is critical for appropriate reimbursement of the care provided to Medicare patients and beneficiaries.

Accuracy is Key

The highly complex HCC model includes approximately 10,000 diagnosis codes that map to HCC codes and 189 different HCC categories with 87 CMS-HCCs, each of which represents diagnoses with similar clinical complexity and expected annual costs of care. Any error can significantly impact reimbursements, which under HCC is determined by mapping a patient’s diagnoses to these codes to create a Risk Adjustment Factor (RAF) score.

The RAF score represents the estimated cost of caring for that patient based on their disease burden and demographic information. It is then multiplied by a base rate to set the provider’s per-member-per-month (PMPM) reimbursement amount. The sicker the patient, the higher the RAF score and, subsequently, the provider’s reimbursement.

Each year, CMS publishes a list of diagnosis codes and corresponding HCC category. Hierarchies (or ‘Families’ of categories) are listed among related condition categories, which set values based on the severity of illnesses. Improperly documenting HCC codes, or failing to document the highest appropriate specificity, results in lower reimbursement rates. For example, HCC 19 (diabetes with no complications) might pay an $894.40 premium bonus compared to a bonus of $1,273.60 for diabetes with ESRD, which requires two HCC codes mapping to 18 and 136.

Conversely, properly documenting HCCs at the highest appropriate specificity can boost reimbursements. For example, if CMS has set a $1,000 PMPM for a patient with an RAF of 2.234 who has diabetes with complications reimbursement would be just $673 per month if the condition is not coded. However, if the case was properly coded as E11.9 Type 2 diabetes mellitus without complications under HCC19 Diabetes without complications, the RAF increases to 2.366, resulting in reimbursement of $1,062 per month. If properly coded as E11.41 Type 2 diabetes mellitus w/diabetic mononeuropathy under HCC18 Diabetes w/ chronic complications, the RAF increases to 2.513 for a reimbursement of $1,312.5.

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9 Ways Artificial Intelligence Can Boost Your Revenue Stream

By Dan Schulte, MBA, CHFP, senior vice president, provider operations, HGS.

Dan Schulte

As outbreaks of COVID-19 continue to crop up around the country, the ongoing public health crisis is just one facet of the situation; economic disruption is another grim reality, including for the healthcare industry itself. The American Hospital Association estimates COVID-19 will result in losses of $202.6 billion for the country’s hospitals and health systems due to factors such as the cancellation of nonemergency procedures; the high cost of treating a patient with COVID-19; and the millions of Americans who could become suddenly uninsured due to the economic implications of the virus.

Providers must improve cash flow to remain stable, which will require new revenue cycle management strategies supported by technology. Artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) together can provide an effective automation strategy that will help healthcare systems recover and retain more of their revenue —  while boosting patient satisfaction — as they navigate this costly crisis.

Nine revenue cycle functions ripe for automation include:

  1. Prior authorizations: With manual prior authorizations requiring an average of 21 minutes and as much as 45 minutes per transaction, the opportunity to drive cost savings through automation is significant. Because of well-defined business rules in this area and structured data that systems exchange in conducting prior authorizations, RPA can significantly improve this process: Implementing a “bot” that can perform the same tasks repetitively and without variation can help reduce error rates, so patients can get the authorization they need quickly, and lower the likelihood of claim denials.
  1. Eligibility and benefit verification: While fully electronic transactions account for more than 84% of all eligibility and benefit verification transactions — a positive development — more can be done to reduce wasteful spending in this part of the revenue cycle. As the starting point for care delivery, this function represents a significant potential for improvement via intelligent automation. The focused manager will ensure that the EDI tools bring the right data across to the patient accounting system (timely, accurate and complete data), and will have the necessary add-ons to find the last 15% of data from screen scraping and outsourcing to a reliable service provider.

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