We’ve been talking a lot about preventive healthcare and how it is the most cost-effective and impactful strategy for addressing today’s global health challenges. At the end of the day, the benefits are clear: instead of reacting to illness once it appears, preventive health measures focus on reducing risks, identifying problems earlier, and allowing patients to maintain long-term well-being. But to make prevention effective, healthcare organizations must first understand who to target.
This is where target group segmentation comes in. By dividing populations into specific risk groups and functional health patterns, organizations can design interventions that are timely, relevant, and cost-efficient. Whether it is preventive health screening by age, controlling risk factors for chronic diseases, or tailoring wellness programs to vulnerable groups, segmentation transforms preventive healthcare into a precise science.
At Thryve, we have our own risk scores program, where we segment populations into risk groups based on their health metrics. And today, we explore the general idea and the role of segmentation in preventive health, the benefits it creates for organizations and patients, the key methods for defining target groups, and how data-driven insights, especially from wearables, are changing the game.
Segmentation is not a new concept in healthcare. For decades, public health campaigns have been built around demographic groups such as children, adults, or seniors. What is different today is the ability to define groups with far greater precision, using real-time data and digital health platforms.
Effective segmentation matters because:
In short, segmentation aligns preventive healthcare with both clinical effectiveness and economic sustainability.
Segmentation strengthens prevention by turning broad strategies into precise, actionable interventions that create value for patients, providers, and payors alike.
Segmentation enables earlier identification of individuals who are most at risk for chronic diseases, such as cardiovascular disease, diabetes, and obesity. By stratifying populations, clinicians can direct preventive screenings, lifestyle interventions, and monitoring programs where they will have the highest impact. Tailored interventions address specific risk factors, for example, targeting sedentary lifestyles or poor sleep quality, and improve both disease management and patient outcomes over time. This ensures that prevention is proactive rather than reactive.
From an organizational perspective, segmentation reduces inefficiencies in care delivery. By concentrating resources on the right groups, hospitals can lower avoidable admissions, emergency visits, and complications that result in costly treatments. Insurers benefit from fewer high-cost claims, while employers see reduced absenteeism and greater workforce productivity. The ripple effect is significant: more efficient use of resources translates into long-term savings and sustainable healthcare cost reduction across entire systems. Check our blog post on how early prevention pays off, even if it takes some time!
Segmentation also drives stronger engagement by making preventive health more relevant to individuals. When people feel that care plans reflect their unique circumstances, they are more likely to participate in wellness programs and adhere to lifestyle recommendations. This personalized approach builds trust, strengthens patient-provider relationships, and creates a sense of shared responsibility for health. Over time, engagement turns into measurable behavior change, such as increased physical activity or improved sleep hygiene.
For healthcare providers and insurers, these benefits translate directly into measurable health ROI. For patients, segmentation provides more than numbers; it leads to longer, healthier lives supported by interventions that feel tailored, timely, and effective.
There are several ways to divide populations into risk groups in preventive health. Each approach has its own strengths and use cases:
Age is one of the strongest predictors of disease risk. Preventive health screening programs often follow age-based guidelines, such as:
Factors like activity level, diet, smoking, and alcohol consumption are strong indicators of long-term health outcomes. Segmenting by these patterns allows for targeted interventions in lifestyle coaching, digital wellness apps, and insurance incentive programs.
Beyond demographics and behaviors, wearables and sensors capture daily data on sleep, activity, stress, and recovery. These functional health patterns can reveal subtle risk groups that are invisible in traditional surveys or check-ups.
Segmentation can also focus on individuals with known comorbidities or a family history of chronic diseases. For instance, people with obesity and hypertension may be flagged as a higher-risk group for cardiovascular disease. Find out more about chronic disease management in our blog post here!
Living conditions, income level, and access to healthcare services shape health outcomes. Segmenting by environmental and social factors ensures preventive programs are equitable and inclusive.
One of the most valuable advances in segmentation comes from analyzing control risk groups. These populations show patterns of modifiable risk. Wearables play a key role here, as they can continuously monitor indicators such as heart rate variability, step counts, and sleep cycles. This enables organizations to identify groups with higher risk but also higher potential for measurable improvement.
Targeting these groups benefits multiple stakeholders:
For more information on how to use wearable data for establishing long-term health incentives, check our page here!
Preventive healthcare only works if it is targeted in the right direction. At the end of the day, you have to know the main risks and problems of the segmented population to actually implement a predictive and proactive approach. Think of it as a long friendship, where you have to get to know your friend first, just the basics at first, then details, so that at the end, you can naturally assume what would work best for them.
Through target group segmentation, providers and insurers can identify the right populations, deliver personalized interventions, and allocate resources more effectively. Whether through age-based screenings, behavioral segmentation, or functional health patterns derived from wearables, segmentation makes prevention more precise, equitable, and impactful.
At Thryve, we have created a special health risk assessment program that segments users into specific risk groups based on the analysis of their wearable data. Moreover, we support healthcare organizations, insurers, and digital health providers with the infrastructure needed to make segmentation actionable. Our API allows for:
By empowering organizations to identify and act on target group insights, we help make preventive healthcare both scalable and sustainable.
Book a demo with Thryve to see how we support preventive healthcare through secure, data-driven segmentation.
Tigran Kuloian is a working student in content marketing at Thryve. As a digital marketing student, he is sharpening his skills in SEO, social media strategy, and content management by working at Thryve. His background in the creative industries adds a fresh perspective to our marketing strategy. At Thryve, Tigran focuses on shaping engaging, data-driven content that connects innovation in wearable data with audiences across healthcare and technology.
