How to reduce risk with better claims and provider insights
Healthcare organizations are no strangers to risk, but the way they assess and manage it is changing fast. Rising costs, growing chronic disease burdens, and widening variation in provider performance are putting traditional risk models under pressure.
Today, most forward-thinking teams are turning to medical and prescription claims data and healthcare provider intelligence to get ahead of risk and not just react to it. After all, claims reveal the real-world story of how patients engage with care: Where they go, what they receive, how much it costs, and whether it works. On top of that, healthcare provider insights offer visibility into performance patterns and inefficiencies that often go unnoticed in traditional models.
When combined, these datasets deliver clear, actionable intelligence for understanding and managing risk more effectively. They allow actuaries to fine-tune forecasts, underwriters to price premiums with greater precision, and care teams to intervene earlier. In this how-to guide, we’ll walk through three use cases where using claims data and provider insights can meaningfully reduce risk, so you can better understand how to leverage and incorporate these insights into your risk management strategies.
1. Predict where risky populations will emerge
High-cost patients often start as moderate-risk individuals whose needs gradually intensify. But because many organizations lack visibility into early indicators of rising risk at the population level, they’re forced to react after costs have already escalated. This creates a persistent gap between where risk starts and when it’s actually addressed.
Medical and pharmacy claims data can help close that gap. By analyzing claims across large populations, organizations can surface patterns that signal emerging risk, such as increased utilization, growing comorbidity burdens, or more complex treatment regimens. For example, an uptick in ED visits among patients with diabetes, or a rise in patients initiating dual therapies for cardiovascular disease, can point to underlying deterioration that hasn’t yet triggered high-cost events.
Provider insights add another layer of predictive value. By assessing the performance of physician groups or facilities, such as readmission rates, care coordination scores, and utilization patterns, organizations can understand where gaps in care are likely to contribute to rising risk. If a provider group has a pattern of low preventive screening rates and high downstream acute care use, that’s a flag worth watching.
Taken together, these datasets give healthcare organizations the ability to model future risk, prioritize rising-risk segments, and adjust strategy accordingly. Instead of reacting to high-cost events after the fact, teams can take a proactive stance and act before the cost hits.
2. Price groups more accurately in underwriting
Inaccurate pricing at the group level is a persistent risk for insurers and self-funded employers. Groups that appear low risk on paper can generate unexpected claims costs due to hidden factors like poor provider performance, chronic disease, or inefficient utilization patterns. Traditional underwriting inputs like age, gender, or location are useful—but only tell part of the story.
With access to medical and prescription claims data, underwriters can assess trends in cost and utilization across populations to make educated, data-driven decisions about the group they’re evaluating. For example, claims data may reveal that similar employee populations in the same region are seeing increased spend tied to musculoskeletal procedures or specialty drugs for autoimmune conditions. This insight enables underwriters to anticipate potential cost drivers before they show up in the group’s own claims.
Detailed intelligence into provider performance sharpens the lens even further. If a group relies heavily on a provider network with high rates of inpatient admissions, readmissions, or low-value procedures, that introduces additional risk, even if the members themselves seem healthy. Understanding the referral patterns, utilization intensity, and cost-per-episode associated with the providers in a group’s network allows for more precise pricing, benefit design, and risk adjustment.
3. Manage and optimize pharmacy spend
Pharmacy costs are one of the fastest-growing components of total healthcare spend, especially with the continued rise of specialty drugs, GLP-1s, and biosimilars. What makes this category particularly challenging is that spend can escalate quickly and quietly, without clear visibility into which populations or prescribing patterns are driving it. By the time costs spike in the claims, it's often too late to adjust course.
This is where prescription claims data can help. At scale, prescription claims reveal what’s being prescribed, how often, to whom, and for how much.
Organizations can use pharmacy claims data to:
- Identify high-cost drug classes trending upward across specific populations or geographies.
- Spot therapy escalation (e.g., a move from oral medications to injectables in chronic disease management).
- Flag non-adherence or inconsistent refills, which often lead to poor outcomes and higher downstream costs.
But prescription patterns don't exist in isolation—they’re driven by providers. By layering in prescriber-level data, organizations can:
- Track which providers or groups are driving high-cost prescribing trends.
- Compare provider behavior against evidence-based guidelines or peer benchmarks.
- Spot outliers, such as clinicians prescribing specialty therapies at disproportionate rates.
This dual perspective offers healthcare leaders unparalleled clarity into the latest trends and shifts in the market, enabling them to coordinate, strategize, and execute faster and with greater efficiency and precision than before. This might take the form of healthcare leaders realigning formularies and prior authorization policies with emerging patterns of use, adjusting pharmacy benefit design to manage costs more effectively, or engaging providers when practices diverge from clinical norms.
The best risk management strategy is a proactive one
Risk doesn’t have to be a black box. With the right insights, it becomes something you can measure, model, and manage.
Definitive Healthcare gives you the tools to do just that, with claims and provider intelligence built for strategic decisions.
Whether you're building a new risk model, evaluating provider partners, or developing a more data-driven pricing strategy, Definitive Healthcare gives you the foundation to act confidently and with clarity. We offer comprehensive medical and prescription claims data at both the provider and organizational level as well as detailed provider performance metrics and in-depth profiles.
When combined, you get powerful, actionable insights that can help you predict emerging cost and utilization trends, anticipate where risk will rise and understand what’s driving it, and take action before risk escalates.
Book a demo with Definitive Healthcare today to see how we can help.