A $88 Billion Global Opportunity for Healthcare Analytics by 2026 - New Research from StrategyR

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May 31, 2022, 09:45 ET

SAN FRANCISCO , May 31, 2022 /PRNewswire/ -- A new market study published by Global Industry Analysts Inc., (GIA) the premier market research company, today released its report titled "Healthcare Analytics - Global Market Trajectory & Analytics". The report presents fresh perspectives on opportunities and challenges in a significantly transformed post COVID-19 marketplace.

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A $88 Billion Global Opportunity for Healthcare Analytics by 2026 - New Research from StrategyR

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Edition: 12; Released: April 2022
Executive Pool: 20568
Companies: 123 - Players covered include Allscripts Healthcare, LLC; Cerner Corporation; CitiusTech Inc.; Cognizant; COTIVITI, INC.; ExlService Holdings, Inc.; General Electric; HMS; IBM Corporation; Inovalon; McKesson Corporation; Optum, Inc.; Oracle; SAS Institute Inc.; Wipro Limited and Others.
Coverage: All major geographies and key segments
Segments: Type (Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, Cognitive Analytics); Application (Financial Analytics, Clinical Analytics, Operational & Administrative Analytics, Population Health Analytics)
Geographies: World; USA; Canada; Japan; China; Europe; France; Germany; Italy; UK; Rest of Europe; Asia-Pacific; Rest of World.

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ABSTRACT-

Amid the COVID-19 crisis, the global market for Healthcare Analytics estimated at US$36.3 Billion in the year 2022, is projected to reach a revised size of US$88 Billion by 2026, growing at a CAGR of 23.6% over the analysis period. Descriptive Analytics, one of the segments analyzed in the report, is projected to grow at a 20.2% CAGR, while growth in the Predictive Analytics segment is readjusted to a revised 26.4% CAGR. The prominence of healthcare analytics has been growing owing to several factors such as thirst for information by stakeholders; need to manage huge, diverse data; growing competition; increasing regulatory complexity; and technological advancements in the medical field. Meaningful and robust analytics has the power to change a healthcare organization and place it ahead of its competitors. The pandemic has significantly expedited adoption and expanded the scope of data analytics in the healthcare domain. The healthcare crisis has pointed towards the critical need for the healthcare industry to embrace healthcare analytics for robust decision support along with other compelling benefits. The integral role played by healthcare analytics and data in improving the response amid COVID-19 highlighted the relevance of data-driven insights to save lives. The crisis has prompted a large number of hospitals to continue shifting towards healthcare analytics over the long-term for tapping meaningful insights and taking informed decisions. The pandemic paved way for numerous technological trends that rely heavily on data and advanced analytics for offering relevant insights. The crisis has led participants to explore and embrace new approaches to curtail spread of the virus and ensure better services to patients. The scenario created an ideal landscape for data analytics within the healthcare industry, a trend that is anticipated to remain unabated in the post-pandemic phase.

Medical professionals are expected to continue relying on data analytics for gaining new insights to keep people safe. In addition, existing models of healthcare data analytics are anticipated to undergo changes in line with the emerging dynamic landscape. In the wake of COVID-19, the healthcare industry has been turning to technology to realign its business amid the economic and public health challenges. Epidemiologists have been coming together with the data scientists during the time of crisis. A discipline called pandemic analytics has been emerging due to the need for open-source visualizations and data sets to fulfill the public's demand for information during the virus spread. The healthcare industry is being increasingly betting on sophisticated IoT options, like wearable sensors or monitors for tracking people infected with COVID-19 and health monitoring tasks. These devices are intended to capture and transmit significant data volumes that can be exploited using data analytics. The approach provides healthcare professionals with meaningful insights into factors that can improve healthcare services. Medical professionals are using sophisticated algorithms and AI technology for determining patients that are required to be treated first and identifying the right approach for treatment.

The ongoing Covid-19 pandemic has exposed the many limitations of the existing global healthcare systems, wherein governments across the globe are struggling to control the outbreak, challenged by the lack of a unified interconnected and trusted network to share data and track cases. The pandemic has highlighted the urgent need for a better system of healthcare data sharing. A highly interoperable healthcare system has the potential to improve national response to Covid-19. Data sharing helps provide the best care to patients and helps stretched healthcare services to work in the most effective way possible. Shared health and medical information could reduce doctor visits, emergency room visits, and hospital admissions. In addition, providers can share healthcare data to avoid medication errors and reduce possibility of duplicate testing. Secure sharing of patient data across healthcare systems and organizations is widely recognized as part of the solution to improve patient outcomes. Patients can influence and benefit when their health data is collected and put to work. Patient-reported data may help researchers and clinicians uncover patterns that would otherwise remain hidden, leading to new ways of predicting, diagnosing, managing and treating illness. These breakthroughs can lead directly to improvements in a patient's own care. For example, federal health IT policy in the US prioritizes wider interoperability and encouraging consumer-mediated exchange through mobile devices and APIs to achieve data sharing.

Covid-19 has prompted more healthcare organizations to adopt data sharing solutions. Regulations that held back information-sharing are being revised and related technology tools encouraged to address the problem of interoperability between healthcare payers and providers. For instance, Google launched its Cloud Healthcare API to help health systems and providers connect data across various sources. Furthermore, consumer interest in sharing of patient data post Covid-19 with various healthcare stakeholders, including payers and health systems is expected to boost the importance of data sharing solutions. Emergency rooms, urgent care centers, and skilled nursing facilities are all grappling with the challenge of timely access to data. By enabling data sharing between clinical and nonclinical partners, frontline workers can make informed decisions faster. For instance, HCA Healthcare, a leading healthcare provider in the US, partnered Google Cloud to launch a national Covid-19 data portal that pools hospital metrics on ICU beds, testing results and patient visits. The National Response Portal provides vital information all health data related to Covid-19 to healthcare providers, researchers, policymakers and the general public. The open data platform, built by and operated by SADA Systems, was launched with the aim to promote data sharing about the pandemic and in turn help hospitals and communities prepare and respond.

AI plays a crucial role in developing healthcare analytic solutions. The technology has already been implemented in diagnosing the coronavirus using imaging analysis, where the diagnose time from CT scan results has been decreased from 5 minutes to just 20 seconds. In addition to coping with the increased diagnostic workloads, AI can also help in freeing up useful resources that can focus on treating patients. ML and AI help in speeding up the development of pharmaceutical processes. There has been considerable success in the development of AI-based drugs so far, proving that technology is capable of expediting the drug development process that usually takes years. It is quite possible that medical researchers, using AI, can further reduce the drug development timelines to months or even weeks. Sharing, analyzing, and deriving insights from the shared knowledge are expected to be the greatest strength in fighting the disease. Applying right technology in the right direction would potentially minimize and contain the impact of the ongoing pandemic in the future. Mor e

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www.StrategyR.com
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