Healthcare Predictive Analytics

Healthcare Predictive Analytics

Healthcare predictive analytics refers to the practice of leveraging advanced analytical techniques and algorithms to extract meaningful insights from large and complex healthcare datasets. It involves the systematic analysis of historical and real-time data, including patient records, clinical data, claims data, and other relevant sources, to identify patterns, trends, and associations. The primary goal of healthcare predictive analytics is to generate accurate predictions, forecasts, and risk assessments that enable healthcare organizations to make informed decisions and take proactive measures for improving patient outcomes, optimizing resource allocation, and enhancing operational efficiency.

The healthcare predictive analytics market is expected to grow at a steady rate of around 24.6% owing to the increasing adoption of electronic health records, the emphasis on population health management, and the need for personalized medicine. By implementing predictive analytics, healthcare providers can identify high-risk patients, predict disease trends, optimize care pathways, and design targeted interventions. This not only leads to improved patient outcomes but also offers opportunities to enhance operational efficiencies, reduce healthcare costs, and improve overall healthcare delivery.

• Based on application, the healthcare predictive analytics market has been classified into clinical data analytics, financial data analytics, research data analytics, operations management, and others. The financial data analytics category is to witness higher adoption of healthcare predictive analytics during the forecast period. This is mainly due to the surging focus of the payers on the early detection of fraud and reducing preventable costs. Moreover, the need to reduce costs without effective quality of care is leading to the growing use of data analytics in the healthcare sector. Furthermore, the benefits of financial analytics in purposes such as claim settlement, risk adjustment & assessment, and fraud analysis is the demand generator for the healthcare analytics market.
• Based on the mode of delivery, the market is segmented into on-premises and cloud-based. The on-premises category is to witness a higher CAGR during the forecast period owing to the low deployment cost associated with the on-premises solutions is one of the key contributing factors for the growth in the market. However, on-cloud deployment is expected to witness a robust CAGR in the forthcoming years due to the widespread adoption of EHR, surging emphasis on digitization, and an increase in funding for innovative delivery solutions. As per IDC, “Global spending on cloud services would surpass USD 1 trillion in 2024.
• Based on end-user, the healthcare predictive analytics market has been classified into healthcare providers, pharmaceutical industry, and others. The healthcare providers category is to witness higher adoption of healthcare predictive analytics during the forecast period. This is mainly due to healthcare organizations aim to deliver high-quality and cost-effective care, they increasingly recognize the value of predictive analytics in improving patient outcomes, optimizing resource allocation, and enhancing operational efficiency. Also, healthcare providers are investing in advanced analytics platforms and hiring data scientists to leverage their vast amount of patient data, electronic health records, and clinical data to generate actionable insights. For instance, more than 19,000 hospitals were present in Europe in 2020, according to the European Hospital Register. It is anticipated that the demand for advanced healthcare solutions, including healthcare analytics, will rise as the region's hospital population continues to grow.
• For a better understanding of the market adoption of the healthcare predictive analytics industry, the market is analyzed based on its worldwide presence in the countries such as North America (U.S., Canada, Rest of North America), Europe (Germany, U.K., France, Spain, Italy, Rest of Europe), Asia-Pacific (China, Japan, India, Rest of Asia-Pacific), Rest of World. North America holds the major market share of this market and is anticipated to grow at a substantial CAGR during the forecast period. This is mainly due to the region having a mature healthcare system with a strong emphasis on advanced technology adoption. The increasing digitization of healthcare data, including electronic health records (EHR) and patient-generated data, provides a rich source of information for predictive analytics. For instance, according to the Office of the National Coordinator for Health Information Technology (ONC), data from 2019 & 2021, 86% of non-federal general acute care hospitals had adopted a 2015 addition certified electronic health record (EHR). Additionally, the growing focus on population health management and value-based care models in the region drives the demand for predictive analytics to identify high-risk patients, improve care coordination, and optimize healthcare resource utilization.
• Some of the major players operating in the market include Cloud Software Group, Inc.; Oracle; Health Catalyst; Verisk Analytics, Inc.; MCKESSON CORPORATION; SAS Institute Inc.; Allscripts Healthcare, LLC; Optum, Inc.; MedeAnalytics, Inc.; and IBM.