Exponential increase in healthcare database volume, increasing investments on digital tech to effectively manage available information, rising adoption of electronic health records to effectively manage patients health, adoption of advanced analytics, growing need for cost curbing tools such as healthcare predictive analytics software are key factors contributing to high CAGR of Healthcare Predictive Analytics market during forecast period.
According to the current analysis of Reports and Data, the global Healthcare Predictive Analytics market was valued at USD 3.74 Billion in 2019 and is expected to reach USD 28.77 Billion by the year 2027, at a CAGR of 28.9 %. The study covers Healthcare predictive analytics – analytical technique that analyses and predicts outcomes using statistical methods and technology, operating on massive amounts of relevant data for individual patients. Healthcare Predictive Analytics is widely being used in the healthcare sector all over the globe. The recent emergence of Healthcare Predictive Analytics as a time saving and cost minimizing tool is a major disruptive finding in the healthcare sector. In line with this, numerous firms and hospitals are adopting Healthcare Predictive Analytics, for time saving and cost cutting purpose. For instance, West Tennessee Healthcare saved more than 8,000 hours annually using Cerner’s Continuous Advancement Services from an optimization project which reduced the number of discrete task assays that nurses completed on a timely basis.
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Knowledge discovery, data mining, and machine learning techniques have recently attracted considerable attention, due to the growing amount of data available, and to the growing necessity to base the reasoning on evidence taken from physical measurements. Data-driven approaches to knowledge extraction have been developed as a consequence, complementing the more traditional human-centered approaches, by enabling systems to create new knowledge, update existing knowledge, and improve their performance without intervention and reprogramming. The organization (or representation) of medical knowledge is a very active research ï¬eld, characterized by a wide range of tools, models and languages, which, together with the availability of increasing computer abilities, allows one to specify and emulate systems of growing complexity. Frame representations, semantic networks, conceptual graph representations are few popular basic representational schemes heavily used in the industry today. Exponential increase in healthcare database volume, increasing investments on digital tech to effectively manage available information, rising adoption of electronic health records to effectively manage patients health, adoption of advanced analytics, growing need for cost curbing tools such as healthcare predictive analytics, are some of the key factors propelling Healthcare Predictive Analytics market growth in the industry.
However, the high cost of analytics solutions, the dearth of skilled personnel, and operational gaps between payers and providers are the major hindrance for market growth during 2019-2027. Problems such as inaccurate diagnoses and poor drug-adherence pose challenges to individual health and safety. These challenges are now being alleviated, if not completely eradicated, with Healthcare Predictive Analytics using personalized drug regimes, follow-up alerts and real-time diagnosis monitoring. Pervasive and context-aware monitoring solutions are improving the quality of life for both patients suffering from chronic conditions and their relatives, as well as reducing long-term healthcare costs and improving the quality of care. The acquisition and representation of knowledge in clinical decision support systems is an actively evolving research ï¬eld, characterized by modeling and software engineering issues of increasing complexity. The scope of designing knowledge-based systems in medicine is continuously evolving from being a mere diagnostic task to the broader issue of patient management, leading to a better integration in hospital information systems These benefits are expected to positively affect the Healthcare Predictive Analytics market.
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