Risk adjustment coding is a vital part of any managed care organization. It helps to ensure that patients are appropriately diagnosed and documented accurately according to risk level, which in turn allows the organization to receive appropriate capitated payments to provide all the care needed to reduce avoidable hospitalizations and achieve maximum health. And regardless of how challenging and time-consuming it can be to implement, getting it right is vital on many levels. Diagnosing and coding for risk can be tricky.
It is not always obvious how complex and risky a condition is, especially because some patients are at higher risk than others for diseases like depression or schizophrenia, but many conditions can be difficult to diagnose. Those who appear low-risk might actually be high-risk, once you dig deeper into the specific diagnosis details. There are thousands of potential codes and conditions to diagnose that can be used to determine risks. There is no perfect formula for every managed care organization; you have to find protocols for training and improvement that work best for your clinicians and operators. Let’s take a look at some of the challenges involved in risk adjustment coding and how to get it right.
Determining risk is difficult
When implementing a risk adjustment program, make sure you have a team on hand with strong coding and data management skills. These team members should be able to look at each patient record and determine both the conditions that have been diagnosed as well as the documentation criteria to be applied to that patient in the chart. This team will be responsible for determining and documenting diagnoses that correlate to the risk level of each patient. This task can be difficult since mastering HCC coding for risk adjustment requires a lot of learning and is often different than standard ICD-10 coding. But there are modern tools for mastering this, so do not lose hope.
Risk adjustment requires a lot of data
Risk adjustment also requires a lot of data. The more information you have about each patient, the better you are able to diagnose based on their true conditions and related risk. If you do not have enough data about a patient, or lack consistent data throughout the lifetime of a patient relationship, you will have a hard time determining their true risk level.
For example: Patient A has been a patient for 10 years, and Patient B has been a patient for 2 years. If you’re trying to diagnose the patients, you’ll have to take into account their lifelong risk factors and current health status. This includes things like socioeconomic status, age, family history of certain diseases, how much they smoke, and more. If you have a few years of data points on Patient A, and only a few months of data points on Patient B, you’ll be able to diagnose Patient A more accurately.
Coding errors are common
Coding errors are common in risk adjustment, but they can be avoided with consistent training, accountability, strict internal audit procedures, and improved clinician buy-in. Coding errors can lead to overcharging or undercharging the CMS, resulting in either missed earnings or painful charge-backs. Coding errors can be caused by a number of different factors. For example, mistakes could be made when determining which diagnoses apply to patients, which codes to use for the diagnoses, or what to document to justify the diagnosis in the chart. Diagnoses require clear communication as well as consistent documentation on all patient records.
It is only going to get harder.
The bad news is that risk adjustment is only going to get harder. New technologies like AI, voice recognition, and machine learning are changing the way health care providers analyze and manage data. While these technologies will make many aspects of coding and managing data easier, they will also make it more complex by introducing even more variables and data points to consider. So while risk adjustment could be more challenging, there are tools available that simplify the process both in training and inside the EMR.
Risk adjustment is vital, because it ultimately determines what type of care an individual patient needs and how much risk the organization is taking on, managing that care. It is important to ensure that your organization is accurately diagnosing and documenting so that patients stay healthy and your organization has the needed revenue to manage their care.