Healthcare Predictive Analytics Market
Number of pages: 100 | Report Format: PDF | Published date: March 03, 2023
Historical Years – 2021 | Base Year – 2022 | Forecasted Years – 2023-2031
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Report Attribute |
Details |
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Market Size Value in 2022 |
US$ 27.03 billion |
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Revenue Forecast in 2031 |
US$ 152.89 billion |
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CAGR |
21.23% |
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Base Year for Estimation |
2022 |
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Forecast Period |
2023-2031 |
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Historical Year |
2021 |
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Segments Covered |
Product, Mode of Delivery, Application, End User, and Region |
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Regional Scope |
North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa |
According to the deep-dive market assessment study by Growth Plus Reports, the global healthcare predictive analytics market was valued at US$ 27.03 billion in 2022 and is expected to register a revenue CAGR of 21.23% to reach US$ 152.89 billion by 2031.
Healthcare Predictive Analytics Market Fundamentals
Healthcare predictive analytics refers to software systems used by healthcare organizations, hospitals, and clinicians to analyze and process patient data to provide data-driven, high-quality care, precise diagnoses, and tailored therapies. Predictive analytics is a sophisticated tool for improving patient outcomes in healthcare. Healthcare data is any information on an individual’s or a group of people’s health gathered via administrative and medical records, health surveys, disease and patient registries, claims-based datasets, and EHRs. Healthcare analytics is a tool that everyone in the healthcare business - healthcare organizations, hospitals, doctors, physicians, psychologists, pharmacists, pharmaceutical companies, and even healthcare stakeholders - may use and benefit from to provide better-quality treatment.
Services, software, and hardware are the primary components of healthcare predictive analytics. Healthcare predictive analytics solutions provide services such as recognizing early indicators of a patient’s condition deterioration, risk score for chronic illnesses, preventing patient suicide and self-harm, and lowering hospital readmission rates. Healthcare predictive analytics delivery models include stand-alone and integrated, and they are utilized for operations management, financial, population health management, and clinical purposes. Healthcare payers and providers are among the end users of predictive analytic services.
The importance of predictive modeling in healthcare may be seen in emergency care, surgery, and intensive care, where a patient’s outcome is directly associated with the healthcare provider’s quick reaction and critical decision-making when or if the situation takes an unanticipated turn for the worse. Yet not all predictive analytics in healthcare necessitates the deployment of an experienced team. Predictive modeling in healthcare and prospective payment systems can assist companies in identifying individuals who are at a higher risk of developing chronic diseases early in the disease’s development, allowing them to avoid costly and difficult-to-treat health issues. Creating risk scores based on health conditions, as well as demographic factors, such as Medicaid and disability status, gender, age, and whether a beneficiary lives in the community or a facility, can provide healthcare data companies with insight into which individuals may benefit from personalized healthcare or wellness programs to prevent problems from occurring. Predictive health analytics systems that identify patients with traits that indicate a high possibility of readmission can help healthcare practitioners determine whether to focus resources on follow-up and how to build individualized healthcare regimens to reduce hospital readmissions. Due to unplanned gaps in the daily schedule, a clinician’s daily workflow might easily be thrown off, resulting in unfavorable financial ramifications for the organization. In healthcare, it is possible to identify patients who may miss their appointments without prior notice with the help of predictive analytics.
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Healthcare Predictive Analytics Market Dynamics
Healthcare spending as a proportion of GDP is increasing in developed and developing countries. Healthcare expenditure has already hit double digits in most European countries and is expected to rise further. Moreover, it is also rapidly increasing in developing countries. Predictive analytics can help cut expenses, including decreasing hospital readmissions, removing needless diagnostic tests, and reducing emergency room visits. Analytics can also eliminate needless tests, a key component of healthcare costs. As predictive analytics can forecast future events well in advance, it reduces potential such visits. Its use at various levels to reduce wasteful expenditures has greatly enhanced the technology’s acceptance rate, and the trend is projected to continue during the forecast period.
The limitations associated with the healthcare predictive analytics industry may impede the expansion of the healthcare predictive analytics market. For instance, a lack of adequate infrastructure is projected to restrict the expansion of the healthcare predictive analytics market. A solid infrastructure is essential for any project’s efficient operation and scalability. The demand for more precise and trustworthy prediction models is growing with the lack of a dependable infrastructure and the growing need for renewal investments. The ability of any project to scale effectively is dependent on its infrastructure.
Healthcare Predictive Analytics Market Ecosystem
The global healthcare predictive analytics market has been analyzed from five perspectives: product, mode of delivery, application, end user, and region.
Healthcare Predictive Analytics by Product
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Based on the product, the global healthcare predictive analytics market has been segmented into hardware, software, and services.
The software and services segments accounted for a significant revenue share of the healthcare analytics market in 2022. Healthcare and life science companies are driven to outsource their analytics services to other leading analytical solutions providers due to a lack of competence and resources. In addition, the services segment is projected to experience the strongest revenue growth rate in the coming years.
Healthcare Predictive Analytics by Mode of Delivery
Based on the mode of delivery, the global healthcare predictive analytics market has been segmented into on-premise and cloud-based.
The on-premise model is the most common option since it provides easier access from remote areas, requiring less maintenance and incurring lower costs. The process of delivering systems and solutions on machines already used by the organization is called on-premise deployment. Despite being installed on-premise, these software solutions may be accessed from anywhere at any time with minimal effort and money, requiring less maintenance.
The demand for large physical facilities for server rooms raises the cost of implementing on-premises software solutions, which is expected to hinder segment expansion. Server rooms house the equipment that requires constant maintenance and is expected to contribute to the segment’s growth. According to industry projections, the cloud-based market is expected to grow at the fastest revenue CAGR during the forecast period.
Healthcare Predictive Analytics by Application
Based on the application, the global healthcare predictive analytics market has been segmented into clinical data analytics, financial data analytics, research data analytics, operations management, and others.
The financial data analytics segment is likely to dominate the market during the forecast period owing to the rising availability of financial data analytics and services in developed regions, such as North America. For instance, in November 2022, International Business Machines Corporation, Technology Corporation, developed software to assist organizations in breaking down data and analytics and identifying the healthcare solution and funding for surgical and operational activities in healthcare.
Healthcare Predictive Analytics by End User
Based on end user, the global healthcare predictive analytics market has been segmented into healthcare provider, pharmaceutical industry, and others.
The healthcare provider segment is likely to dominate the market during the forecast period due to the rising releases of healthcare services by healthcare providers. Healthcare Triangle Inc. announced the debut of Healthcare Triangle services in Asia Pacific, where the usage of virtual healthcare is rapidly increasing. The increase in investments in the digitalization of healthcare institutions is accelerating the adoption of digital health platforms.
Healthcare Predictive Analytics by Region
Based on the region, the global healthcare predictive analytics market has been segmented into North America, Europe, Asia Pacific, Latin America, Middle East & Africa.
The market in North America is expected to maintain its dominance during the forecast period as more platforms for healthcare predictive analytics services are launched in North America. For instance, Databricks, a software startup, developed a lake house platform for Healthcare and Life Sciences in March 2022. The Databricks lake house platform for healthcare and life science is a platform for data management, analytics, and advanced AI use cases such as disease prediction, medical image classification, and biomarker identification.
In the domain of predictive analytics, the healthcare infrastructure in the United States is experiencing positive trends. According to studies, more than 40% of healthcare executives have reported a 50% increase in data volume in the last few years. As data sets grow in size and complexity, health institutions and payers are increasingly turning to predictive analytics. Healthcare organizations also recognize that social determinants of health contribute more to a patient’s well-being than medical difficulties. One of the emerging trends is the collaboration of non-competing healthcare groups to manage a population’s health. Government payers such as Medicare and Medicaid are quickly adopting capitated payment and value-based purchasing models in which results are assessed and rewarded. As a result of improved healthcare infrastructure, the industry is predicted to rise rapidly.
Asia Pacific is the fastest-growing region in the global healthcare analytics market due to the increasing awareness about healthcare analytics, the rising population, and industry improvements in this region.
Healthcare Predictive Analytics Market Competitive Landscape
The increased usage of inorganic techniques, such as acquisition, by key players to extend the capabilities of healthcare predictive analytics is likely to generate attractive growth prospects for participants in the global market.
The prominent market players in the global healthcare predictive analytics market include:
Healthcare Predictive Analytics Market Strategic Developments
Healthcare predictive analytics refers to software systems that healthcare organizations, hospitals, and clinicians use to analyze and process patient data and provide data-driven, high-quality care, precise diagnoses, and tailored therapies.
Asia Pacific is the key revenue growth region in the global healthcare predictive analytics market.
The emergence of personalized and evidence-based medicine and the growing need for rising efficiency in the healthcare industry are fueling revenue growth in the market.
Allscripts Healthcare Solutions, Cerner Corporation, and Information Builders Inc. are among the top market players.
The financial data analytics application leads the global healthcare predictive analytics market.
*Insights on financial performance are subject to the availability of information in the public domain