Clinical analytics: bridging gap between health plans and health care

Clinical analytics is not the next big thing in health care. There’s no next about it. Data analysis plays an increasingly central role in optimizing care and managing costs.

Data can help better connect payers and providers

In a nutshell, clinical analytics makes use of real-time medical data to support fact-based diagnosis and treatment decisions. This, in turn, improves outcomes and lower costs. Data analytics can inform almost every aspect of care, including care management, network & value-based care, and cost & utilization.

At NHP, we like to think of clinical analytics as transforming relevant data into thoughtful insights. The data can provide an unprecedented 360-degree picture of patients and facilitate and unprecedented level of payer/provider collaboration.

As a clinical analyst, I compare claims data with enrollment data to uncover patterns that predict which members may be at increased risk for conditions like diabetes and heart disease, so we can partner with the provider to intervene. The algorithms both identify and stratify members, so we can make sure the most at-risk members are our highest priority. Based on the results of my work, a care manager may also reach out directly to a member. In this way, analytics facilitate more human interaction, thereby improving healthcare outcomes.

Looking to the future of clinical analytics

While the trend in analytics is industry-wide, NHP has invested heavily in our analytical capabilities. We’re also exploring ways to overcome some of the current limitations and unlock the full potential of the data.

For example, I mentioned cross-referencing claims and enrollment data. This only allows us to categorize what types of members are at high-risk, it does not identify specific members who would benefit from clinical intervention. This is because claims data only tells us what has already happened to a member, not what is likely to happen in the future.

The trend toward more collaboration among healthcare providers and insurers creates a golden opportunity for fully integrated analysis. Access to patient data directly from providers can help insurers extrapolate high-risk members before the claims process and there’s time to suggest more effective and efficient care plans. In collaboration with providers, we can find ways to predict which individuals are likely to develop certain conditions or need certain treatments, so we can step in while they are still healthy. In other words, we can harness clinical data to power preventive medicine – not just treatment and interventions.