The global healthcare predictive analytics market size is expected to reach USD 67.5 billion by 2030, registering a CAGR of 24.4% over the forecast period, according to a new report by Grand View Research, Inc. The rising burden of chronic diseases on a global level coupled with the increasing cost of healthcare are the key factors driving the market for healthcare predictive analytics and is resulting in wider adoption rates of the same across the globe. With the increasing adoption of telehealth and other consultation methods, the adoption of EHRs has led to enormous patient data in the past few years. This can be leveraged by the healthcare IT companies for predictive analytics for risk management, disease management, understanding of disease spread & trajectory as well as in delivering proper medical care to the patient for the best outcomes.
All of these factors have been driving the global market growth. An increase in healthcare expenditure in developed and developing countries due to a rise in the number of chronic diseases will also support market growth. In the Europe region, the healthcare expenditure as a percentage of GDP in 2019 was 9.92%. Technological advancements as well as rapid generation of patient data, more so during the COVID-19 pandemic due to teleconsultations, EHRs, etc. have made it possible to analyze data and derive meaningful results, which are oriented towards better patient outcomes. The healthcare predictive analytics tools not only help reduce costs & assist the care providers to decide on the best treatment plans but also significantly reduce the risk of fraudulent claims made to recover money from insurance companies.
Annually, trillions of U.S. dollars’ worth of false insurance claims are made. For providers, predictive analytics has been a key to reducing costs significantly. The above-mentioned factors contribute significantly to the growth of the market. The financial application of predictive analytics is the largest in the segment owing to the massive amounts of money that can be saved by deploying these predictive tools in day-to-day work. The frauds alone when detected can be averted and result in trillions of dollars saved, moreover unnecessary tests and medication can be avoided with the help of predictive analytics, which can help determine the best treatment plans and evidence-based medicine or personalized medicines for the treatment of the disease.
A trial conducted studied the financial implications of continuous monitoring in patients with opioid-induced respiratory depression, the study found that a median hospital could save up to $535,531 annually, and can shorten the cumulative stay by 103 days. The payers had the majority share of the end-use segment, comprising insurance companies who assess risk related to false claims as well as the high cost of treatments that are a concern for the providers. Adoption of predictive analytics tools for cost reduction as well as for saving money by detecting frauds in insurance claims is a major factor driving the growth of the segment. The providers are the fastest-growing category owing to the reduction in the cost of treatments and wider adoption rates among both private as well as government-affiliated providers.
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The financial application segment accounted for the largest market share in 2022 due to the need to curb fraudulent insurance claims. Population health management is estimated to be the fastest-growing application segment from 2023 to 2030
North America led the market share in 2022 due to ever-improving healthcare infrastructure and advancements in technology and IT
Healthcare predictive analytics has played a major role in saving the region in terms of high-end fraudulent insurance claims as well as providing the best possible treatments on a personalized level for reaching optimum patient outcomes This has been a key driving force for the market
Asia Pacific is estimated to be the fastest-growing regional market from 2023 to 2030 due to the rapidly advancing healthcare sector, increasing expenditure, and overall improvement & adoption in healthcare IT
The COVID-19 pandemic had an adverse impact on how healthcare predictive analysis was looked at
Various studies on the virus that caused the outbreak could be studied due to the massive amount of patient data that was generated during the pandemic
This has been seen as an opportunity for the market. Healthcare predictive analytics tools for personalized treatment plans for each patient as well as reduced treatment costs are primary factors driving the market
Grand View Research has segmented the global healthcare predictive analytics market on the basis of application, end-use, and region:
Healthcare Predictive Analytics Application Outlook (Revenue, USD Million, 2018 - 2030)
Operations Management
Demand Forecasting
Workforce Planning And Scheduling
Inpatient Scheduling
Outpatient Scheduling
Financial
Revenue Cycle Management
Fraud Detection
Other Financial Applications
Population Health
Population Risk Management
Patient Engagement
Population Therapy Management
Clinical
Quality Benchmarking
Patient Care Enhancement
Clinical Outcome Analysis And Management
Healthcare Predictive Analytics End-use Outlook (Revenue, USD Million, 2018 - 2030)
Payers
Providers
Other End-user
Healthcare Predictive Analytics Regional Outlook (Revenue, USD Million, 2018 - 2030)
North America
U.S.
Canada
Europe
Germany
U.K.
Italy
Spain
France
Sweden
Denmark
Norway
Asia Pacific
China
India
Japan
Thailand
South Korea
Australia
Latin America
Brazil
Mexico
Argentina
MEA
South Africa
Saudi Arabia
UAE
Kuwait
List of Key Players of Healthcare Predictive Analytics Market
IBM
Cerner Corp.
Verisk Analytics, Inc.
McKesson Corp.
SAS
Oracle
Allscripts
Optum, Inc.
MedeAnalytics, Inc.
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