New York, USA, Aug. 08, 2023 (GLOBE NEWSWIRE) -- Predictive Disease Analytics Market Overview
According to a Comprehensive Research Report by Market Research Future (MRFR), “Predictive Disease Analytics Market Information By Component, Deployment, End User, And Region - Forecast till 2032", the market is projected to grow from USD 2.6 Billion in 2023 to USD 13.7 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 23.20% during the forecast period (2023 - 2032).
Market Scope
Predictive analytics is a subset of advanced analytics that uses modeling, data mining, statistics, and artificial intelligence (AI) to create predictions and improve decision-making. Big data and predictive analytics aid in enhancing cohort therapy, personal medicine diagnostic and treatment precision, and the operational oversight of healthcare organizations. The healthcare sector has faced difficulties, including rising treatment costs, a lack of better patient care, and low patient satisfaction and retention. Therefore, predictive data analysis methods are being used in the healthcare industry to improve operations and provide better patient care. These are a few of the major forces driving the healthcare analytics market. These initiatives are undertaken in response to the growing demand for predictive disease analytics in the life sciences and healthcare sectors. Furthermore, these players frequently use mergers, acquisitions, and geographic expansion as crucial strategies.
The healthcare expenditure percentage has surpassed double-digit digits in most European nations and is still rising. Spending on healthcare is rapidly increasing, even in developing nations. The use of predictive analytics can help cut expenses in a variety of ways, including by lowering emergency room visits, unneeded diagnostic testing, and readmissions to the hospital. Analytics can also be used to cut down on unneeded tests, which make up most healthcare costs. Healthcare businesses that are confident they have a comprehensive and reliable descriptive analytics program advance to the next step of analytics, which is predictive analytics. Based on the descriptive data that is now accessible, predictive analytics utilizes data mining, machine learning, statistical approaches, predictive modeling, and other sophisticated computer techniques to anticipate the likely future.
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Report Scope:
| Report Attribute | Details |
| Market Size in 2032 | USD 13.7 Billion |
| CAGR | 23.20% |
| Base Year | 2022 |
| Forecast Period | 2023-2032 |
| Historical Data | 2021 |
| Forecast Units | Value (USD Billion) |
| Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
| Segments Covered | By Component, Deployment, End User |
| Geographies Covered | North America, Europe, Asia-Pacific, and Rest of the World (RoW) |
| Key Market Drivers | Increase in efficiency in the healthcare sector |
| Emergence of personalized and evidence-based medicine |
Predictive Disease Analytics Market Competitive Landscape:
- Oracle
- IBM
- MedeAnalytics, Inc.
- Health Catalyst
- Apixio Inc.
- SAS
- Allscripts Healthcare Solutions Inc.
Predictive Disease Analytics Market Trends:
Market Drivers:
The healthcare sector has faced difficulties due to problems like rising treatment costs, inadequate patient care, and lower patient engagement and retention. The entire sector has adopted predictive disease analytics to improve operations and give patients better treatment. The development of the healthcare analytics sector is primarily due to these causes. There is an increase in the prevalence of chronic diseases like cancer, Type 2 diabetes, respiratory illnesses, and cardiovascular illnesses. Healthcare providers evaluate the risk proportion to a person's health using predictive modeling, a component of clinical data analytics. Clinical data analytics aid patients and caregivers in addressing post-operative concerns such as surgical site infections, impaired physical function, and drug and allergy reactions since healthcare personnel are supplied with the patients' historical medical data, which has been provided through electronic health records.
An industry for predictive disease analytics solutions has been created to manage such diseases effectively. Healthcare practitioners can now collect and analyze vast amounts of patient data thanks to technological advancements like machine learning, artificial intelligence, and data analytics. Health practitioners are better able to develop precise predictive disease analytics solutions with the aid of these technologies. Thanks to predictive disease analytics tools, healthcare practitioners can customize treatments for specific patients, considering their medical histories and distinctive traits.
Browse In-depth Market Research Report (128 Pages) on Predictive Disease Analytics: https://www.marketresearchfuture.com/reports/predictive-disease-analytics-market-11853
COVID 19 Analysis
Due to the growing demand for digital solutions and sophisticated analytical tools for managing the patient population, COVID-19 helped the industry's market flourish. Large data are produced due to factors including the growing patient load on the healthcare system, increased disease prevalence, and others. The healthcare sector is under increasing pressure to deliver better patient care at reduced prices, which creates more market opportunities. During the pandemic, enormous amounts of clinical data were produced, which needed to be managed properly using analytics tools. This would enable researchers and healthcare providers to produce better results, identify trends, and comprehend disease transmission dynamics.
Predictive Disease Analytics Market Segmentation
The market's various components include hardware and software. Healthcare payers, providers, and other end users are all included in the market under end users. The market is segmented into on-premises and cloud-based deployments.
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Predictive Disease Analytics Market Regional Insights
The proliferation of helpful government programs is responsible for market expansion. The rising healthcare spending also encourages market growth and opens new business opportunities. Additionally, the Indian Predictive Disease Analytics market had the quickest growth rate in the Asia-Pacific region, and China's Predictive Disease Analytics market had the greatest market share. As predictive analytics may make accurate predictions and results well in advance, it can reduce such visits. Promising trends in predictive analytics are being observed in the US healthcare system. Healthcare providers are also becoming aware that social aspects of health have a greater positive impact on a patient's wellness than medical problems.
One of the trends that have been noticed is the collaboration of non-competing healthcare companies to manage the well-being of a population. Government suppliers, including Medicare and Medicaid, quickly embrace value-based purchasing and capitated payment models where performance will be tracked and rewarded. The trend is anticipated to continue during the projected period due to the technology's widespread use at various levels to cut back on wasteful spending.
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