Health Care Predictive Analytics Market: Overview
Turing historical data into useful insights and predictions to enable clinical decision making is a key facet of the expanding role of predictive analytics into healthcare. The healthcare predictive analytics market has made continuous strides from the growing real-life applications of predictive analytics in hospital settings. For instance, various tools are used to proactively identify health issues and prevent hospital readmissions. Over the years, algorithmically derived probabilities from these tools have enabled clinicians to make better informed decisions while evaluating the risks. Gaining access to these probabilities send timely alerts to clinicians and caregivers in the management of chronic diseases. The expanding array of tools in the healthcare predictive analytics is being enriched by the growing incorporation of advanced artificial intelligence (AI) and internet of things (IoT) in the platforms.
In the times of management of Covid-19 around the world, healthcare predictive analytics played a useful role, as these helped clinicians reduce the unnecessary burden on the ICUs. The focus toward early identification of disease conditions is a key health proposition for the deployment of technologies pertaining to healthcare predictive analytics. Thus, healthcare predictive analytics has helped in the identification of at-risk patients. This is crucial in case of infectious diseases or of disease of high worldwide mortality.
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Healthcare Predictive Analytics Market
Healthcare Predictive analytics can be described as a branch of advanced analytics that is utilized in the making of predictions about unknown future events or activities that lead to decisions. Unlike prescriptive analytics, which uses data sets to help streamline existing processes and improve operational performance, healthcare predictive analysis frameworks use machine learning and artificial intelligence models to discover correlations across disparate data sources and provide actionable recommendations. The power of healthcare prediction with data analytics is especially critical in medicine. In practice, predictive analytics offers benefits across multiple use cases, such as
- Improved patient outcomes. By integrating patient records with other health data, healthcare organizations can detect warning signs of serious medical events and proactively prevent their occurrence.
- Holistic health support. Evolving patient-centric models focus on the person as a whole rather than on outcomes in isolation. Predictive tools make it possible to collect and integrate lifestyle, symptom and treatment data to produce holistic treatment plans.
- Enhanced operations. Predictive tools can also be applied to internal healthcare processes such as equipment provision or staffing requirements to help lower overall costs.
- Personalized service provision. Care personalization has taken center stage as pandemic pressures evolve. Predictive tools make it possible to create truly personalized treatment plans tailored to unique patient needs.
Predictive analytics is a technology used in the field of business intelligence that produces predictive information for customers or organizations. Predictive analytics uses machine information, data mining, and business intelligence tools in order to make predictions. Also, it involves statistics and different modeling techniques to derive some information. Presence of a large volume of structured and unstructured data and wide technology distribution are major factors driving the predictive analytics market.
Developing countries worldwide are confronting issues caused by sudden increase in drug prices. Governments of these countries are taking steps to provide good-quality affordable health care services. These factors are projected to drive the health care predictive analytics market during the forecast period. Additionally, rising attention toward personalized patient care, growing awareness in the market, and advancements in health care technologies led by increased health care spending are fueling the market. However, factors such as data insecurity, privacy issues, and lack of experienced professionals in the field of predictive analytics are hindering the health care predictive analytics market. Rising adoption of electronic health records among patients and health care providers to better manage the details has reduced the overall expenses associated with manual work. This has boosted the demand for predictive analytics in the health care industry.
The global health care predictive analytics market can be segmented based on application and end-user. Based on application, the health care predictive analytics market can be segmented into financial, operations management, population health, and clinical. Based on end-user, the market can be segmented into payers, providers, and others. Among applications, the financial segment holds the leading market share. The predictive analysis in healthcare helped in fraud detection and prevention and also in the revenue cycle management. Based on end-user, the payers segment is projected to hold the leading market share during the forecast period.
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Geographically, the global health care predictive analytics market can be segregated into North America, Europe, Asia Pacific, Latin America, and Middle East & Africa. Although industrially developed countries in Europe and North America account for a leading share of the global health care predictive analytics market owing to more systematic health care systems and policies, high growth is witnessed in emerging health care predictive analytics markets in Asia Pacific. High demand for health care predictive analytics in Asia Pacific is attributable to rising population, increasing awareness, and surging investments in health care infrastructure, and rising need for managing large volumes of data in the region. Large market players are focusing on Asia Pacific to accelerate their business in upcoming economic markets. Competitiveness in the health care predictive analytics market is increasing, with more number of players seeking to leverage benefits of boom in the IT industry and its outsourcing in developing regions.
Key players operating in the global health care predictive analytics market are Verisk Analytics, Inc., IBM, Optum, Inc., Allscripts, Cerner Corporation, SAS, MedeAnalytics, Inc., McKesson Corporation, and Oracle. The key strategy to the growth of the health care predictive analytics market includes rising number of strategic collaborations between health care and IT companies and also increasing focus on product development by the health care industry.
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