Healthcare Predictive Analytics Market Size, COVID-19 Impact Analysis, Regional Outlook, Application Growth Potential, Competitive Market Growth & Forecast, 2021 – 2027
Report ID: GMI1089
Healthcare Predictive Analytics Market size is projected to witness substantial expansion from 2021 to 2027 driven by the rise in healthcare costs and the growing demand for personalized and evidence-based medicines. The influx of healthcare and wearable technology has instigated a higher awareness regarding health metrics monitoring platforms and parameters among consumers.
The increasing healthcare expenditures have pushed government authorities, medical organizations, as well as private players, to increasingly make use of healthcare predictive analytics to bend the cost curve by optimizing the existing clinical operations, workflow, and payment strategies. They are also effective in limiting the number of unnecessary tests, which are major contributors to healthcare costs.
The incorporation of predictive analytics in assisting healthcare providers in identifying patients that have a high likelihood of readmission, while offering an indication on centering assets on follow-up as well as designing personalized healthcare protocols to put an end to frequent returns to the hospital. Its varying levels of use significantly help to curb unnecessary expenditures, in turn bolstering the higher adoption of the technology.
Financial applications are anticipated to bring significant revenues for the healthcare predictive analytics market led by higher acceptance across fraud detection and revenue cycle management. While growing awareness about population health management will further sway the market growth.
The payers end-use segment is expected to emerge as a profit-enhancing source owing to the presence of several insurance companies, health plan sponsors, as well as third-party payers.
Consistent developments in healthcare IT technologies and the robust access to advanced infrastructure with ample resources have considerably boosted the deployment of healthcare predictive analytics in North America. The rising demand in the U.S. can be attributed to the presence of major service providers in this region, including IBM, SAS, and Oracle.
Verisk Analytics, Oracle, SAS, Optum, MedeAnalytics (JLL Partners), McKesson Corporation, and Cerner Corporation are a few of the prominent companies bolstering the healthcare predictive analytics market share to a significant extent.
Strategic partnerships, such as mergers and acquisitions, along with the incorporation of latest technologies to back innovations, are among the key measures undertaken by these solution providers of healthcare predictive analytics to reinforce their competitive position in the business landscape.
For instance, in August 2020, Allscripts entered a partnership with Sheba Medical Center of Israel to expedite the AI technologies as well as to enhance patient care through the hospital’s ARC (accelerate, redesign, and collaborate) Innovation Center, with an aim to drive healthcare transformation by 2030.
In another instance, in March 2021, Health Catalyst, Inc. launched the Healthcare.AI™, a suite of augmented intelligence (AI) services, and products in order to effectively expand the use cases of AI in healthcare, whilst addressing the healthcare business challenges in terms of revenue, cost, and quality.
Impact of COVID-19 on healthcare predictive analytics market forecast
The current COVID-19 pandemic not only triggered a massive blow to the global economy but has also instigated a substantial transformation across multiple facets of human life, including lifestyle patterns. While the imposition of nationwide lockdowns, multi-facility closures, and trade barriers significantly contributed to the upheaval of multiple businesses, it proved to be a considerable boost for the healthcare predictive analytics market.
In a bid to better understand the virus in terms of disease outcomes, risks as well as the potential impact on resources, healthcare providers are increasingly seeking big data and predictive analytics tools. Other than long-term forecasting, these models are assisting organizations to garner insights on the surges and dips of the COVID-19 infection count, whilst ensuring optimum planning and helping hospitals in resuming their complete spectrum of necessary services.
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