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Clinical Risk Grouping Solution Market size was valued at USD 673.4 million in 2023 growing at a CAGR of 11.5% between 2024 and 2032. Clinical risk grouping solutions help in identifying high-risk patients and managing the care more efficiently. Therefore, one of the primary drivers is the increasing healthcare cost, as healthcare costs continue to rise, there is a greater need for solutions that can effectively manage and mitigate the expenses of treatment.
Additionally, the rise in prevalence of chronic diseases such as diabetes, cardiovascular diseases, and cancer increases the need for effective population health management solutions. For instance, as per the report published by World Health Organization it has been reported that noncommunicable diseases (NCDs) kill 41 million people each year, equivalent to 74% of all deaths globally. Cardiovascular diseases account for most NCD deaths, or 17.9 million people annually, followed by cancers (9.3 million), chronic respiratory diseases (4.1 million), and diabetes (2.0 million including kidney disease deaths caused by diabetes).
Report Attribute | Details |
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Base Year: | 2023 |
Clinical Risk Grouping Solution Market Size in 2023: | USD 673.4 million |
Forecast Period: | 2024 – 2032 |
Forecast Period 2024 – 2032 CAGR: | 11.5% |
2024 – 2032 Value Projection: | USD 1.8 billion |
Historical Data for: | 2021 – 2023 |
No. of Pages: | 128 |
Tables, Charts & Figures: | 213 |
Segments covered: | Component, Application, End-use, and Region |
Growth Drivers: |
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Pitfalls & Challenges: |
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Thus, the rapid increase in the prevalence of chronic disease globally is the major factor that is expanding the demand for clinical risk grouping solution for better risk stratification and to manage patient populations and improve healthcare outcomes, thereby driving the market growth. A clinical risk grouping solution (CRGS) is a sophisticated tool or system used in healthcare to categorize patients based on their clinical risk. The main purpose of CRGS is to predict and manage healthcare outcomes, optimize resource utilization, and improve patient care by identifying individuals at varying levels of health risk.