57.5 Percent of Commercially Insured Patients Had at Least One Chronic Condition in 2024, According to FAIR Health Report
The Cost for a Patient with One Chronic Condition Was Nearly Double That for a Patient with No Chronic Conditions
NEW YORK, NY—February 2, 2026—The majority (57.5 percent) of commercially insured patients had at least one chronic condition in 2024. The average allowed amount [1] for a patient with no chronic conditions was $1,590, while the average allowed amount for a patient with one chronic condition was nearly double ($3,039). Of 44 common chronic conditions studied, hyperlipidemia, or high cholesterol, was the most common, with a crude prevalence [2] of 21.2 percent. These and other findings are reported in a FAIR Health white paper released today: Chronic Conditions in the United States: A Study of Commercial Claims .
Chronic diseases or conditions are the leading cause of illness, disability and death in the United States. FAIR Health Atlas, an epidemiological reporting platform to be launched in 2026, uses FAIR Health's repository of commercial healthcare claim records—the largest in the nation—to measure prevalence and costs associated with chronic conditions. This study of common chronic conditions in the commercially insured population in the United States in 2024 draws on that platform. The study focuses on prevalence, co-occurring conditions, costs, geography and correlation of prevalence rates to the poverty rate. The key findings, all from 2024, include the following:
- Many patients had more than one chronic condition. For example, 11.5 percent of patients had two conditions, and 9.1 percent had three.
- Some chronic conditions frequently co-occur. In the commercially insured population, 33.4 percent of patients had hyperlipidemia, hypertension, obesity or some combination of these, and 4.3 percent had all three. [3] Half the patients with any one of these conditions had more than one.
- The number of chronic conditions per commercially insured patient per year drives healthcare spending. The average allowed amount rose per number of chronic conditions, reaching $21,730 for 10 or more chronic conditions—13.7 times higher than for a patient with no chronic conditions.
- Chronic conditions vary in their median and average number of co-occurring chronic conditions and average allowed amount per year. Of the 44 chronic conditions studied in the commercially insured population, lung cancer had the highest average allowed amount per year ($22,740) and ADHD the lowest ($4,175). [4] Acute myocardial infarction, non-Alzheimer's dementia and Alzheimer's disease had the highest median number of comorbidities (six) and pneumonia and autism the lowest (one). Acute myocardial infarction had the highest average number of co-occurring chronic conditions (6.19) and autism the lowest (1.63).
- When analyzed in pairs, the crude prevalence rates of hypertension, hyperlipidemia, obesity and diabetes [5] had a moderate to strong positive correlation. [6] The prevalence rates of hypertension and diabetes had the strongest positive correlation (86.0 percent); those of obesity and hyperlipidemia had the weakest (45.0 percent).
- Some clusters of chronic conditions—such as the cluster of hypertension, diabetes, obesity, chronic kidney disease and hyperlipidemia—are more strongly correlated to the poverty rate than others. The prevalence rates of all of the conditions in the cluster just mentioned had a positive correlation to the county-level poverty rate. By contrast, the cancers studied all had negative correlations to the poverty rate, with breast cancer showing a -24.3 percent correlation.
The findings in this report have implications for stakeholders across the healthcare spectrum, including patients, providers, payors, policy makers and researchers. The report also demonstrates some of the capabilities of the forthcoming FAIR Health Atlas on which it is based. Among those capabilities are measuring chronic condition prevalence, comorbidities and costs in the commercially insured population; mapping the prevalence of chronic conditions; using correlations to measure how closely chronic condition prevalence rates are related; and using correlations to measure how closely chronic conditions are related to risk factors such as poverty.
For the complete white paper, click here .
