In light of various challenges that payers and providers are facing due to the COVID-19 pandemic, the Centers for Medicare & Medicaid Services (CMS) issued 2022 Medicare Advantage and Part D rates three months early on January 15th, 2021 in order to give plans more time to calculate bids for the next coverage year. In addition to providing information about the new rates and per capita payments, there are three noteworthy aspects that are important for payers and providers to factor into their risk adjustment processes. These are going to be critically important for payers and providers to ensure they are accurately documenting and coding the risk acuity of their patients.
Encounter Data Processing System (EDPS) readiness
CMS plans to complete its transition from Risk Adjustment Process System (RAPS) to Encounter Data Processing System (EDPS). EDPS requires much more detailed information about the risk eligible diagnosis code as part of encounter level data submissions. To avoid rejections and ensure compliance it is important for payers and providers to not only ensure that all data elements are sufficient, including accurate diagnosis codes and CPT information, but also to ensure they have the appropriate processes in place to validate that diagnosis codes for each encounter are being accurately assessed, documented, and coded.
Pitfalls to avoid during the EDPS process review
According to CMS, payers and providers must ensure that their EDPS submissions are appropriate for the right place of service. Examples of these types of pitfalls include but are not limited to: acute codes such as stroke, sepsis, and hemorrhages in place of service (POS) 11. These types of conditions require inpatient treatment.
Required documentation for telehealth visits
It is encouraged to use some form of interactive audio and video telecommunications system with the patient for these types of encounters. These visits still have certain documentation requirements of an evaluation and management service. Payers and providers must ensure they are reviewing these types of encounters and diagnoses to meet the encounter documentation compliance requirements. A good exercise would be to audit a sample size of these telehealth visits to ensure they meet the documentation criteria.
Physician/Coder training to account for new conditions that are being added into the risk model
There are several changes to the risk model with the introduction of new conditions. On the provider side, it is important to make sure physicians are looking out for these conditions and paying close attention to actively managing and reviewing these conditions with their patients as well as making sure they are appropriately documented and coded. Some of these conditions, such as mental health and substance abuse, are often overlooked and it is important for providers to make certain that their physician and CDI teams are trained on identifying and documenting them. We foresee the risk model continuing to change and evolve as CMS continues to include Social Determinants of Health (SDoH) and other often overlooked aspects that have a significant impact to patient care and outcomes. A great way for providers to confirm that these aren’t overlooked is to use sophisticated Natural Language Processing (NLP) technologies that can scan through their current and historical patient records to identify patients that indeed have these conditions. An effective NLP system can identify both clinical and non-clinical information.
For payers, it is equally important to look out for and review these conditions to verify that they are coded correctly. If there isn’t sufficient documentation to support these conditions, they need to be deleted from the encounter data submissions. It is necessary to work closely with these providers as they are improving their documentation and coding practices for these new conditions. NLP technologies are extremely helpful for payers to look out for these conditions and to find opportunities where they could potentially be undercoded or even overcoded.
Elevate your business operations with NLP-enabled risk adjustment coding
Talix provides solutions to help providers, payers, and accountable care organizations navigate the dynamic healthcare landscape with respect to risk, quality, and value-based care. The Talix Platform uses award-winning, patented natural language processing (NLP) and machine learning (ML) techniques to power workflow applications, making processing patient data more accurate and efficient. For more information or to schedule a demo, please visit www.talix.com or email email@example.com.