Fort Collins, Colorado, March 01, 2024 (GLOBE NEWSWIRE) -- The Healthcare Predictive Analytics Market was valued at USD 14.8 Billion in 2023 and is anticipated to grow CAGR at 23.3% to reach USD 97.8 Billion by 2032.
Healthcare predictive analytics refers to integrating machine learning, artificial intelligence, and data mining tools in healthcare data to help understand and predict the growth or spread of disease in an individual in the population and help provide personalized healthcare treatments and patients.
Predictive analytics uses data modeling techniques that help create models based on current and historical data to understand ongoing trends and build models to predict future trends. With all the healthcare data getting generated and stored online using artificial intelligence, blockchain, and machine learning, the rate of data generation has grown massively in the healthcare sector. This has led to healthcare researchers using this data to predict the causes of various diseases, their effects, and the remedies used by various patients to treat them. This has led to the adoption of predictive analytics in the healthcare sector.
A major factor contributing to the growing demand for predictive analytics in healthcare is that it helps manage disease. By studying the patient data, such as their health history and the medical history of their family members, the medical staff can predict diseases the person can suffer from, vulnerabilities carried, and other such factors. This helps the patients ensure they take the necessary steps to reduce these risks by taking precautions beforehand. In addition, doctors can study the patient’s medical history and genetics and any early signs of health conditions to prevent them from becoming a major healthcare issue.
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Segmentation Overview:
The global healthcare predictive analytics market has been segmented into application, end-use, and region. Based on the end-use, the healthcare predictive analytics market is segmented into payers, providers, and others. Payers hold a significant share of the end-use segment of the healthcare predictive analytics market. Payers include stakeholders like insurance companies, third-party payers, and healthcare services sponsors, and they depend on healthcare predictive analytics to understand the insurance terms and payments well to avoid any payment and insurance conflicts.
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Healthcare Predictive Analytics Market Report Highlights:
- The global healthcare predictive analytics market growth is anticipated at a CAGR of 23.3% by 2032.
- Predictive analytics can also be used at a larger scale to study the outbreak of any disease and factors like its causes, the group of people affected the most, and reasons for it and assess the effects of vaccines on different groups of people.
- North America holds a dominant share in the healthcare predictive analytics market, with the United States holding a substantial share in this region. It has been observed that both large and small hospitals in the United States are increasingly adopting predictive analytics and other tools like artificial intelligence, the Internet of Things, and remote patient monitoring systems.
- Some prominent players in the healthcare predictive analytics market report include IBM, McKennson Corp., Oracle Corporation, MedeAnalytics, Optum Inc., Veradigm, SAS, Verisk Analytics Inc., Cotiviti Inc., and Komodo Health.
Industry Trends and Insights:
- In 2023, Fresenius Medical Care developed a predictive model technique based on cloud computing and machine learning to proactively identify the severity of a health threat for kidney patients.
- eClinicalWorks developed a front-line solution using AI models for CareSTL Health by supporting the clinic with technology support, and effective communication with patients.
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Healthcare Predictive Analytics Market Segmentation:
By Application: Operations Management, Financial, Population Health, and Clinical
By End-use: Payers, providers, others
By Region: North America, Latin America, Europe, Asia Pacific, the Middle East and Africa.
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