Healthcare Analytics Global Market Opportunities And Strategies To 2022

Starting Price : $ 4000.00 | Pages : 70 | Published : July 2018 | SKU CODE : o&s014 | Format :

Analytics is the systematic use of data and related business insights developed through various analytical models such as statistical, cognitive, contextual, predictive, quantitative and other emerging models to initiate fact based decision making for planning, measurement, management and learning. These analytics may be predictive, descriptive, and prescriptive. Analytics can improve effectiveness and efficiency. From managing small issues to larger processes, these analytics can aid assessment and discovery of innovative insights, which ultimately help design and plan policy, improve service delivery operations, enhance sustainability, mitigate risk and evaluating critical organizational data.

Some of the key players operating in the healthcare data analytics market include Cerner Corporation, Oracle Corporation, McKesson Corporation, IBM Corporation, Truven Health Analytics, Optum, and MedeAnalytics. The report covers more details about the data analytics healthcare industry, data science applications in healthcare, and health data marketplace.

Global Healthcare Analytics Global Market Size

The global market for healthcare analytics market share was valued at $11.3 billion in 2017. North America had the largest healthcare data analytics market size in the medical analytics market in 2016, accounting for nearly 61% of the total market.

Global Healthcare Analytics Global Market Segmentation

The Global Healthcare Analytics Market is segmented into Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, Clinical Data Analytics, Administrative & Operational Analytics, and Financial Analytics.
Healthcare Descriptive Analysis Market descriptive analysis is defined as the systematic quantitative gathering and transformation of data that includes hospitalization summaries, frequency of various disease cases and length of patient stay in the hospital. Currently, various healthcare organizations are extensively using this analytical tool, which provide them with the clear understanding of what has happened and its visualization by means of key performance metrics or data in the report or dashboard showing present state and past performance.
Healthcare Predictive Analytics Market predictive analysis tools assist in understanding the past unstructured data to predict the future actions in customer perspective. These analytics includes performance management, workforce planning management, financial management, patient record management, risk and compliance management, marketing optimization, marketing planning, payment management, readmission analysis, billing management and operations management.
Healthcare Prescriptive Analytics Market prescriptive analytics is the form of business analytics that includes examination of past and current data of patients to recommend the course of action to be taken for positive outcomes, a decision modelling system for the industry. The core objective of the prescriptive analytics is not only to predict the future outcomes but also to recommend the therapies based on outcomes. These analytics guide healthcare professional actions by making treatment recommendations based on the past patients’ data. Prescriptive analytics minimized the risk in strategic decision making to improve the organization’s profitability, improved customer satisfaction along with the consumer experience. In view of all these above-mentioned supportive factors, prescriptive analytics technology is considered as the fastest emerging healthcare analytics technology.
Clinical Data Analytics are intensively used to reduce medical errors incidence, to improve the quality of healthcare, and also to make healthcare procedures more efficient to treat.
Administrative & Operational Analytics Most healthcare organizations, professionals and hospitals use administrative and operational analytics to improve the treatment outcomes, identify the patients for the clinical trials, optimize utilization of resources, reduce costs and also to analyse the treatment versus outcomes. These analytics are further segmented into resource analytics, supply chain management analytics and strategic analytics.
Financial Analytics are further subdivided into risk analytics, revenue cycle analytics and claims analytics.

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