The global predictive disease analytics market size was estimated at around USD 2.02 billion in 2022 and it is projected to hit around USD 15.68 billion by 2032, growing at a CAGR of 22.74% from 2023 to 2032.
Key Pointers
Report Scope of the Predictive Disease Analytics Market
Report Coverage | Details |
Market Size in 2022 | USD 2.02 billion |
Revenue Forecast by 2032 | USD 15.68 billion |
Growth rate from 2023 to 2032 | CAGR of 22.74% |
Base Year | 2022 |
Forecast Period | 2023 to 2032 |
Regions Covered | North America, Europe, Asia Pacific, Latin America, Middle East & Africa |
Companies Covered | Oracle; IBM; SAS; Allscripts Healthcare Solutions Inc.; MedeAnalytics, Inc.; Health Catalyst; Apixio Inc. |
Predictive analytics is a branch of advanced analytics that helps make predictions and better decision-making by using various techniques such as modelling, data mining, statistics, and artificial intelligence (AI). Big data and predictive analytics help in improving the operational management of healthcare organization, the accuracy of diagnosis and treatment in personal medicine, and increased insights to enhance cohort treatment.
The healthcare industry has been challenged with issues like skyrocketing treatment costs, lack of better patient care, and less patient retention and engagement. Thus, predictive disease analytics are being adopted throughout the industry to provide better care to patients and improved operations. These factors are the major reasons for the growth of the healthcare analytics industry. For instance, in November 2022, Hartford HealthCare and Google Cloud announced their long-term partnership to improve their healthcare system's digital transformation to improve data analytics and enhance patient care.
The rapid advancement in technology and huge investment by the healthcare industry helps in the rapid digitization of the healthcare sector. These analytical platforms are deployed throughout the globe that will help manage patient and their retention. Furthermore, the deployment of healthcare analytics increases staff productivity, improves patient management and reduces caregivers' burden. In March 2022, Databricks introduced Lakehouse paradigm for Healthcare and Life Science industry to deliver innovation in research and care. The single platform can be used for analytics, data management and advanced AI for disease prediction, medical image classification and biomarker discovery.
The rise in government initiatives and an increasing amount of money being invested in the healthcare industry are two key reasons for increasing adoption of predictive analytical tools in the healthcare sector. For instance, February 2023, European Commission has invested USD 7.2 million for a new project that focuses on developing AI based platform that will be used for collecting and analyzing clinical data on new oncology medicines to support their assessment through regulators and health technology assessment (HTA) agencies. Similarly, the U.S. government is taking various initiatives in this direction, such as introducing the HealthData.gov portal that collects information from several federal databases on topics such as clinical data, community health performance, and medical and scientific knowledge. Other than hospitals, policy makers are also adopting these platforms for analyzing statistics and models for making better decisions and policies regarding healthcare establishments and delivering care to patients. Major key players also focus on developing technologically advanced tools to expand their market dominance.
COVID-19 boosted the industry's market growth due to the rising need for digital solutions and advanced analytical tools for managing the patient population. A huge amount of clinical data was generated during the pandemic that required proper management with the help of analytics solutions; this will help researchers and caregivers to derive greater outcomes, predict trends and understand the dynamics of the spread of disease. However, factors such as privacy issues, lack of regulations, and algorithm bias are projected to hamper the market growth.
Predictive Disease Analytics Market Segmentations:
By Component | By Deployment | By End User |
Software & Services Hardware |
On-premise Cloud-based |
Healthcare Payers Healthcare Providers Other End Users |