As healthcare organizations shift toward value-based contracting, accurately representing the health status of their patient population is key to receiving revenue that would compensate them fairly for the care of their patients. Most value-based contracts use a risk adjustment methodology to either determine capitated payments or adjust attributed healthcare expenditures in shared savings contracts. The most widely discussed has been the CMS HCC (Hierarchical Condition Category) methodology that is used in most Medicare Advantage and Medicare ACO and shared savings programs. HCC coding has now become a top priority for healthcare organizations. Today, numerous healthcare IT companies promote their “solution” for navigating the complexities of HCC coding. Wouldn’t it be great if there was a technology that would solve all our risk adjustment challenges for us?
”Engaging clinicians and understanding how they work is essential for ensuring that new technologies won’t interfere with their efforts to provide care.”
The answer to that question isn’t so simple. Properly documenting all patients’ underlying health conditions requires a complex interplay of processes involving clinical decision-making, operational workflows, and back-end revenue cycle. Providers and healthcare organizations need to understand where gaps lie in these processes in order to select the technology that is right for them.
At Atrius Health, 75 percent of our revenue derives from total cost of care or global budget contracts. As a CMS Next Generation ACO, identifying gaps and working proactively and collaboratively across clinical teams is crucial for lowering cost and improving the quality of care. In order to optimize our HCC coding performance, an interconnected series of processes in which clinicians, operations staff, and coders work together is crucial (see Figure 1).
Figure 1: Process Map for Risk Adjustment
Only clinicians can identify chronic conditions, but to optimize HCC coding, they must assess these conditions each year. Operations staff engage patients who have care gaps to schedule appointments. Back end coders review records to capture missing diagnoses. To ensure that clinicians did not miss any care opportunities, we installed a tool that provides those prompts right in the EHR during a patient visit. The tool reminds the clinician of a patient’s outstanding conditions upon first opening the chart during a visit. After the clinician conducts their assessment, the reminder tool can also be used for documentation. This tool also allows our analytics team to obtain data to identify patients with care gaps which the operations staff uses to outreach to patients.
Clinicians are constantly bombarded with mountains of data, so in developing this tool, we worked hard to make sure the system provides them with the right information at the right time. We’ve further tailored the tool so that specialists would see information about HCC coding opportunities that is pertinent to them. Including specialists was key to this team approach to offset the burden that most quality and performance based programs are heavily weighted towards primary care.
While we chose a technology that supported clinicians at the point of care, we also created a Risk Adjustment team to manage the entire process illustrated in Figure 1. Continuously evaluating the process and improving the process has been a more important factor in our success managing HCC coding than the technology we installed.
Throughout this process, we learned a number of lessons that organizations should consider when choosing and implementing an HCC technology solution:
• HCC is not just about risk adjustment: In order to transform your practice and engage clinicians in capturing codes for risk adjustment, leaders cannot frame this as a coding problem or a coding initiative. Long term, healthcare technology leaders need to reframe this conversation in terms of closing care gaps. Every missed coding opportunity represents a potential care gap.
• Establish metrics: The technology you implement will likely produce lots of data—it’s important to define the right driver metrics to help work toward your organization’s goals.
• Sustainable processes: Coding processes must be built so that they are sustainable. One big push around improving HCC capture does not last over time—it needs to lead to building sustainable processes and team work across the organization.
Technology is sexy, but drawing workflows and understanding what is exactly being done to care for patients is not. HCC coding won’t improve with technology alone. To maximize its impact, healthcare organizations have to understand their current processes and how to adapt them to potential technological solutions. Engaging clinicians and understanding how they work is essential for ensuring that new technologies won’t interfere with their efforts to provide care. Improving HCC coding will only occur by leveraging other members of care teams and working collaboratively across the organization to close gaps in care.