It’s a time of rapid transformation for risk adjustment. Newly announced payment models are expanding opportunities in providers’ value-based care strategies all the time. These models could make it easier than ever for hospitals and practices to recognize the benefits of risk-sharing arrangements. However, providers must incorporate new tools and practices that work within, rather than against, existing care and revenue cycle workflows.

Applying technology solutions like Natural Language Processing (NLP) to risk enables better decision making by more thoroughly and accurately identifying the disease burden of a population. Armed with this insight, providers can better capture the expected cost of care, identify care gaps, and manage the full scope of patients’ needs, ultimately offering more proactive care delivery and improved patient outcomes. 

Understanding the health status of risk-based populations is a necessity for value-based care initiatives, especially with the push to adopt downside risk models. This isn’t just a priority for programs aimed at better care integration for dual-eligible beneficiaries, either. A comprehensive and effective risk capture capability is essential across all payment models.

Despite its mission-critical nature for risk-bearing providers, risk adjustment exists within a laundry list of burning issues for health care executives. How can you simultaneously test innovative care models, analyze the data, keep up to date with federal regulations, compete with other caregivers in your market, reimagine your supply chain and labor pipeline, and negotiate with payers?

To add to an executive’s worry, clinical documentation plays a big role in value-based reimbursements, while also contributing to physician burnout. According to a 2018 Survey of American’s Physicians, 80 percent of physicians reported full capacity or overextension—78 percent reported burnout, with clinical documentation tagged as a huge contributor. Even as innovation within and outside the EHR has endeavored to mitigate the burden of documentation, the reported strain on clinical staff has not been measurably reduced.

Given these competing priorities and uncertainty about how to proceed, it’s understandable that risk adjustment may not be at the forefront. However, risk adjustment is non-negotiable in today’s evolving value-based care environment. The push to adopt more downside risk is not going away; organizations need to know how to provide care in risk-based payment models and how to thrive financially while doing so.

The recent CMS announcements underscore this necessity. But success requires a thoughtful, minimally disruptive integration of risk-capture tools into existing clinical and revenue cycle workflows.

Effective risk-capture workflow leads to a better, documented understanding of which patients require care and the highest-priority care interventions. Clinical staff is more effectively utilized, and each patient encounter yields the greatest possible impact on health outcomes. Beyond that, revenue is no longer lost by not collecting sufficient reimbursement to cover the true disease burden of a patient population.

Throwing technology at any problem in health care is rarely a straightforward solution, given the complex web of interdependent processes, user roles, and concurrent improvement initiatives. However, when implemented efficiently and in service of a clinician’s workflow, new tools can deliver substantial, measurable improvements in the accuracy and completeness of risk capture, without negatively impacting operational efficiency. Delivering suspected conditions and evidence at the point of care means integrating risk capture directly into the EHR to minimize disruption and resistance to adoption. By delivering these risk-capture insights at the optimal time, in a thoughtfully integrated manner, we can ensure clinical and coding staff are best equipped to act with greatest effect.

There are now compelling, real-world examples of this combination of cutting-edge risk capture tools and thoughtful workflow integration driving clinical and financial improvements contemplated above. Several of the largest, most innovative health systems have begun deploying these tools across their risk-bearing patient populations. While the impact on patient outcomes will need to be measured over several years, these organizations are yielding up to a 5:1 ROI on the risk capture investment itself. That return can be rolled back into other improvement initiatives, many of which will deliver return over a much longer horizon. For this reason, there is a strong argument for sequencing an investment in risk adjustment tools and practices ahead of competing priorities.

New federal initiatives are creating a golden moment to allow clinicians to return to the joy of medicine by improving the physician-patient relationship and better serving the patients. While risk adjustment may seem like an unlikely tool to foster that opportunity, it’s a scene we’ve witnessed across our provider partners again and again. Whatever approach you take, having a technology partner committed to providing a solution that serves clinicians’ priorities rather than prescribing them, while still solidifying the financial performance of the organization, is going to bring your golden moment a lot closer to realization.

About the author
As chief commercial officer, Robin Lloyd leads Health Fidelity’s go-to-market strategy and the sales, marketing, professional services, and product teams. He brings more than 25 years of experience building and leading organizations through rapid growth and transformation. He has led teams throughout the US, Europe, and Asia, and is fanatical about developing effective, customer-driven leaders who can scale and adapt along with dynamic business needs.