Data analytics facilitates the acquisition of explicit, actionable knowledge. In this case, internal, health plan data and statistical algorithms reveal past patterns and trends in claims to help plan sponsors understand workforce health and what’s driving benefits costs.

Clinical informatics involves the acquisition of tacit knowledge. This is a deeper exploration of healthcare data, through a combination of computer science, patient care, healthcare management and information science. If data analytics reveals financially problematic medical trends, clinical informatics uncovers why conditions are manifesting and what risks they present.

How they work

Data analytics might show growth in the plan’s diabetic population, and one member’s claims hitting $350,000. Also uncovered are an increase in concurrent and prospective risk scores and heavy utilization in a particular drug category. Analytics also provides insights into the plan’s year over year changes. This results in partial storytelling of the plan’s standing, without fully addressing the “so what” of what the data suggests. That invites doubt and inaccurate recommendations and no change in outcomes.

The broader perspective of informatics tells a complete, unbiased story, because of its holistic view of facts, patterns and prognoses. It identifies shortages of available endocrinologists in relevant plan communities and predicts another $300,000 in spending by the high-cost claimant. It also uncovers critical “whys.” Provider-based gaps in care, for example, are leading to risk score increases. Heavy medication utilization is due to off-label, non-evidence-based use. Informatics further makes the case for intervention: better results with no impact on utilization.

In fact, everyone’s better served when data analytics and clinical informatics work together to uncover risk trends in the health plan and get at their root causes. The result is smarter clinical and administrative decision-making and sharper strategies to manage risks and costs.

How clinical informatics can shape a medical plan cost containment strategy

To understand the impact, take a hypothetical example: a movie production company with three to four annual releases. It has seen an increase in mental health leaves, raising concern about loss of productivity, employee burnout and stress churn.

Data analytics involves reviewing diagnosis and prescription usage, providers and use of onsite and virtual care use and estimating productivity loss. It focuses primarily on access to care and its impact, looking at types of mental health claims, if particular people are affected and network access is adequate.

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The process for informatics involves observing the severity and frequency of claims, assessing clinical risk variables and stability of care. The influence of social determinants of health is reviewed, while job class patterns are uncovered. Informatics seeks to quantify the propensity of risk, and patterns of risk within the employee population. It also focuses on the root causes – work and social – of mental health, supporting targeted strategies based on specific risks.

Ultimately, clinical informatics significantly bolster network optimization strategies, as clinicians help ensure cases and claims are properly managed. In providing a more holistic view of mental health, it encourages a more targeted and effective treatment.

Why informatics is more relevant than ever

What many small and middle market employers don’t realize is that they are entitled to their benefits data under the Consolidated Appropriations Act (CAA). That includes pharmaceutical use and cost data (which were initially excluded). The aim was to provide more transparency over plan performance and cost drivers. In exchange, plan sponsors are financially obligated to ensure their plans are properly managed – and solvent.

With full access to their data, mid-market employers are empowered to change the carrier’s narrative about their risk posture and its role in rate increases and shape their own vision. But it takes getting complete data, for starters, and then, utilizing data analytics and clinical informatics to gather insights that improve their benefits strategies.

The goal with clinical informatics is to get pre-emptive in managing risks before they become so bad on the back end that they can’t be controlled. Because in exchange for transparency under the CAA, employers are obliged to ensure the plan is performing as expected in supporting optimal medical care – lest they become as legally liable for lapses as insurers.

Dr. Kryijztoff (Kryz) Novotnaj, DNP, MPH, CPHIMS, is the Chief Clinical Informatics Officer (CCIO) for global insurance brokerage Hub International.