According to the recent report by Future Market Insights (FMI), the predictive disease analytics market size is estimated to stand at US$ 18.64 billion by 2033. Over the forecast period, the market is assessed to trail at a CAGR of 22.5%. For the year 2023, the market is estimated to be worth US$ 2.45 billion.
Market Propellers for Predictive Disease Analytics
Don't pay for what you don't need
Customize your report by selecting specific countries or regions and save 30%!
The healthcare industry has been facing challenges in the form of spiking treatment expenses, a dearth of improved patient care, and low patient engagement and retention. Therefore, predictive data analysis techniques are being deployed throughout the healthcare sector to offer enhanced patient care and upgrade operations. These are some key factors propelling the healthcare analytics industry.
In November 2022, for instance, Google Cloud and Hartford HealthCare officially declared their long-term partnership. The partnership is to digitally transform their healthcare system to enhance patient care and data analytics.
Surging Governmental Support
The rise in government initiatives and huge finance invested in the healthcare industry bolstered the market. In February 2023, the European Commission invested US$ 7.2 million for a new project aimed at developing an AI-based platform. This platform is going to collect and analyze clinical data on new medicines of oncology to encourage their assessment via regulators and health technology assessment agencies (HTA).
Likewise, the United States government is launching the HealthData.gov portal. The portal captures information from various federal databases on clinical data, medical and patient knowledge, and community health performance.
| Attributes | Details |
|---|---|
| Predictive Disease Analytics Market Value (2023) | US$ 2.45 billion |
| Predictive Disease Analytics Market Forecast Value (2033) | US$ 18.64 billion |
| Predictive Disease Analytics Market CAGR (2023 to 2033) | 22.5% |
The market generated a revenue of US$ 2 billion in 2022. The market is set to register a CAGR of 22.5% to reach US$ 2.45 billion in 2023.
The predictive disease analytics industry is being driven by the following factors
Predicted Growth of Predictive Disease Analytics Market Over the Forecast Period
| Duration | Market Analysis |
|---|---|
| Short-term Growth | The market is anticipated to stand at a valuation of US$ 3.68 billion by 2025. Increasing emphasis on preventive care is propelling the deployment of disease prediction using symptoms dataset. With the help of predictive disease analytics, healthcare providers are better able to identify patients who are at risk of suffering from certain conditions. These solutions help in potentially minimizing healthcare expenditure. |
| Medium-term Growth | By 2028 end, the market is estimated to surpass a market worth of US$ 6.76 billion. The market is expected to be led by the accelerating telehealth sector, particularly for predictive disease analytics. These solutions are predicted to be used to support telemedicine consultations and remote patient monitoring. |
| Long-term Growth | The market is projected to amass a total of US$ 18.64 billion by 2033. In the long run, integration of these solutions with blockchain technology is anticipated to boost the transparency and security of patient data. As a result, making it is convenient to share and analyze health insights spanning different healthcare organizations. |
Principal Consultant
The software and services segment accounted for a maximum share of 69.9% in 2022. The segment is also anticipated to observe a significant CAGR over the forecast period. Digitalization of data and the development of platforms has led to considerable investments by the healthcare sector into the IT sector.
Since a significant amount of businesses don’t have an in-house data analytics department, they outsource data analytics work to their IT team. Due to the aforesaid factor, data analytics firms are growing in business and more of these firms are coming into the business. These firms offer an entire range of services to businesses. The growing scope of services and new services aimed to meet evolving business demands are further enhancing segment growth.
The on-premise section led the predictive disease analytics industry by acquiring a total revenue share of 65.9% in 2022. Due to the high security and convenience of access offered by on-premise deployment, several institutions are focusing on installing instruments and software to accumulate data at their premises. This comes in handy for small businesses. However, in case it is scaled up to manage a sizeable dataset of businesses, it can make data management tiring and challenging.
The cloud-based solutions segment is projected to register a prominent CAGR in the assessment period. Growing demand for solutions that offer easy storage, more flexibility and efficiency, and low capital requirements is boosting the adoption of cloud-based solutions. Further, these solutions also help enhance user engagement and obtain medical evidence from anywhere and at any given time. Companies offering predictive disease analytics are actively concentrating on multiple strategic initiatives to bolster segment growth.
The payer segment is expected to rule the market, on the basis of the end user. The market share of this segment is anticipated to be 40.9% in 2022. The payer segment consists of government agencies, insurance companies, third-party payers, and health plan sponsors (unions and employers). These companies or institutions are employing predictive disease analytics tools. To properly evaluate insurance claims before payment settlement, disease risk assessment, and detecting and detecting and preventing fraudulent claims. Increasing utilization of historical as well as current data by payers to predict future trends is expected to boost segment growth.
The provider segment is expected to expand expeditiously in the upcoming years. Some key drivers of the market include soaring healthcare outlay and increasing investment in healthcare infrastructure. Surging chronic disorders and the rising geriatric population is also pushing several providers to invest in predictive disease analytics solutions. These solutions enable providers to identify patterns and trends and make shrewd decisions regarding treatment and allocation of resources.
These services also help by offering insights and forecasting demand for healthcare services and strategizing for future needs. In October 2022, the research team at the University of Pennsylvania Perelman School of Medicine and the University of Florida made an announcement. The declaration was to establish a set of predictive analytics algorithms to find out which patients are likely to develop a rare disease.
The United States predictive disease analytics industry occupied a huge market share in 2022. The country is home to significantly advanced healthcare facilities that boast predictive disease analytics. In addition to this, a rise in chronic disorders and a surging density of the geriatric population has been witnessed in the country. This has led to heightened demand for analytics tools from hospitals, clinics, and other organizations.
Moreover, the high count of key players in the United States market is also contributing to market growth. In September 2020, Microsoft introduced Microsoft Cloud for Healthcare aimed to unite providers and patients in gaining better insights pertaining to patient care.
The China predictive disease analytics industry is expected to account for robust CAGR in the stipulated time frame. Favorable government policies and support are catalyzing market development in this country. Additionally, increasing expenditure on healthcare is the propelling market expansion and opening up new avenues for growth.
The increasing geriatric population and surging cases of chronic disorders are two crucial factors for market growth in China. As per the United States Census Bureau’s survey, in 2020, the geriatric population amounted to 414 million individuals in Asia. Moreover, by 2060 end, that figure is going to reach 1.2 billion.
Get the data you need at a Fraction of the cost
Personalize your report by choosing insights you need
and save 40%!
Top players in the market are concentrating their efforts on developing new solutions and tools. These efforts are made to cater to the surging demand for predictive disease analytics from the life sciences and healthcare industry. Moreover, mergers and acquisitions and extension in geographic footprint are some key tactics adopted by these players.
In January 2023, SwitchPoint Ventures and Ardent Health Service partnered together to release an innovation studio. This studio focuses on creating and deploying data-driven solutions. Additionally, Ardent has also adopted Polaris, which is SwitchPoint’s new solution to precisely predict patient volume in a clinical set-up.
Escalating investments in healthcare further bolsters startups to enter the market, thereby increasing the competition. FMI has profiled the following players in the market report
| Attribute | Details |
|---|---|
| Forecast Period | 2023 to 2033 |
| Historical Data Available for | 2018 to 2022 |
| Market Analysis | US$ billion for Value |
| Key Regions Covered |
|
| Key Countries Covered | The United States, Canada, Germany, the United Kingdom, France, Italy, NORDICS, Spain, Russia, Poland, BENELUX, China, Japan, India, ASEAN, Oceania, South Korea, Brazil, Mexico, Argentina, GCC Countries, South Africa, Northern Africa, Türkiye |
| Key Segments Covered | Component, Deployment, End User, and Region |
| Key Companies Profiled |
|
| Report Coverage | Market Forecast, Company Share Analysis, Competition Intelligence, DROT Analysis, Market Dynamics and Challenges, and Strategic Growth Initiatives |
| Customization & Pricing | Available upon Request |
The market is valued at US$ 2.45 billion in 2023.
The market is expected to record a 22.5% CAGR through 2033.
The market is estimated to reach US$ 18.64 billion by 2033.
Healthcare tourism is positively influencing the market growth.
Oracle, IBM, and SAS are key predictive disease analytics market players.
1. Executive Summary | Predictive Disease Analytics Market
1.1. Global Market Outlook
1.2. Demand-side Trends
1.3. Supply-side Trends
1.4. Technology Roadmap Analysis
1.5. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations
3. Market Background
3.1. Market Dynamics
3.1.1. Drivers
3.1.2. Restraints
3.1.3. Opportunity
3.1.4. Trends
3.2. Scenario Forecast
3.2.1. Demand in Optimistic Scenario
3.2.2. Demand in Likely Scenario
3.2.3. Demand in Conservative Scenario
3.3. Opportunity Map Analysis
3.4. Investment Feasibility Matrix
3.5. PESTLE and Porter’s Analysis
3.6. Regulatory Landscape
3.6.1. By Key Regions
3.6.2. By Key Countries
3.7. Regional Parent Market Outlook
4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033
4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022
4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033
4.2.1. Y-o-Y Growth Trend Analysis
4.2.2. Absolute $ Opportunity Analysis
5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Component
5.1. Introduction / Key Findings
5.2. Historical Market Size Value (US$ Million) Analysis By Component, 2018 to 2022
5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Component, 2023 to 2033
5.3.1. Hardware
5.3.2. Software
5.3.3. Services
5.4. Y-o-Y Growth Trend Analysis By Component, 2018 to 2022
5.5. Absolute $ Opportunity Analysis By Component, 2023 to 2033
6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Deployment
6.1. Introduction / Key Findings
6.2. Historical Market Size Value (US$ Million) Analysis By Deployment, 2018 to 2022
6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment, 2023 to 2033
6.3.1. On-premise
6.3.2. Cloud-based
6.4. Y-o-Y Growth Trend Analysis By Deployment, 2018 to 2022
6.5. Absolute $ Opportunity Analysis By Deployment, 2023 to 2033
7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By End User
7.1. Introduction / Key Findings
7.2. Historical Market Size Value (US$ Million) Analysis By End User, 2018 to 2022
7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By End User, 2023 to 2033
7.3.1. Healthcare Payers
7.3.2. Healthcare Providers
7.3.3. Research Institutions
7.4. Y-o-Y Growth Trend Analysis By End User, 2018 to 2022
7.5. Absolute $ Opportunity Analysis By End User, 2023 to 2033
8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Application
8.1. Introduction / Key Findings
8.2. Historical Market Size Value (US$ Million) Analysis By Application, 2018 to 2022
8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2023 to 2033
8.3.1. Clinical Data Analytics
8.3.2. Financial Data Analytics
8.3.3. Administrative Data Analytics
8.3.4. Research Data Analytics
8.4. Y-o-Y Growth Trend Analysis By Application, 2018 to 2022
8.5. Absolute $ Opportunity Analysis By Application, 2023 to 2033
9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region
9.1. Introduction
9.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022
9.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033
9.3.1. North America
9.3.2. Latin America
9.3.3. Europe
9.3.4. South Asia
9.3.5. East Asia
9.3.6. Oceania
9.3.7. MEA
9.4. Market Attractiveness Analysis By Region
10. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
10.2.1. By Country
10.2.1.1. USA
10.2.1.2. Canada
10.2.2. By Component
10.2.3. By Deployment
10.2.4. By End User
10.2.5. By Application
10.3. Market Attractiveness Analysis
10.3.1. By Country
10.3.2. By Component
10.3.3. By Deployment
10.3.4. By End User
10.3.5. By Application
10.4. Key Takeaways
11. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
11.2.1. By Country
11.2.1.1. Brazil
11.2.1.2. Mexico
11.2.1.3. Rest of Latin America
11.2.2. By Component
11.2.3. By Deployment
11.2.4. By End User
11.2.5. By Application
11.3. Market Attractiveness Analysis
11.3.1. By Country
11.3.2. By Component
11.3.3. By Deployment
11.3.4. By End User
11.3.5. By Application
11.4. Key Takeaways
12. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
12.2.1. By Country
12.2.1.1. Germany
12.2.1.2. United kingdom
12.2.1.3. France
12.2.1.4. Spain
12.2.1.5. Italy
12.2.1.6. Rest of Europe
12.2.2. By Component
12.2.3. By Deployment
12.2.4. By End User
12.2.5. By Application
12.3. Market Attractiveness Analysis
12.3.1. By Country
12.3.2. By Component
12.3.3. By Deployment
12.3.4. By End User
12.3.5. By Application
12.4. Key Takeaways
13. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
13.2.1. By Country
13.2.1.1. India
13.2.1.2. Malaysia
13.2.1.3. Singapore
13.2.1.4. Thailand
13.2.1.5. Rest of South Asia
13.2.2. By Component
13.2.3. By Deployment
13.2.4. By End User
13.2.5. By Application
13.3. Market Attractiveness Analysis
13.3.1. By Country
13.3.2. By Component
13.3.3. By Deployment
13.3.4. By End User
13.3.5. By Application
13.4. Key Takeaways
14. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
14.2.1. By Country
14.2.1.1. China
14.2.1.2. Japan
14.2.1.3. South Korea
14.2.2. By Component
14.2.3. By Deployment
14.2.4. By End User
14.2.5. By Application
14.3. Market Attractiveness Analysis
14.3.1. By Country
14.3.2. By Component
14.3.3. By Deployment
14.3.4. By End User
14.3.5. By Application
14.4. Key Takeaways
15. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
15.2.1. By Country
15.2.1.1. Australia
15.2.1.2. New Zealand
15.2.2. By Component
15.2.3. By Deployment
15.2.4. By End User
15.2.5. By Application
15.3. Market Attractiveness Analysis
15.3.1. By Country
15.3.2. By Component
15.3.3. By Deployment
15.3.4. By End User
15.3.5. By Application
15.4. Key Takeaways
16. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
16.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
16.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
16.2.1. By Country
16.2.1.1. GCC Countries
16.2.1.2. South Africa
16.2.1.3. Israel
16.2.1.4. Rest of MEA
16.2.2. By Component
16.2.3. By Deployment
16.2.4. By End User
16.2.5. By Application
16.3. Market Attractiveness Analysis
16.3.1. By Country
16.3.2. By Component
16.3.3. By Deployment
16.3.4. By End User
16.3.5. By Application
16.4. Key Takeaways
17. Key Countries Market Analysis
17.1. USA
17.1.1. Pricing Analysis
17.1.2. Market Share Analysis, 2022
17.1.2.1. By Component
17.1.2.2. By Deployment
17.1.2.3. By End User
17.1.2.4. By Application
17.2. Canada
17.2.1. Pricing Analysis
17.2.2. Market Share Analysis, 2022
17.2.2.1. By Component
17.2.2.2. By Deployment
17.2.2.3. By End User
17.2.2.4. By Application
17.3. Brazil
17.3.1. Pricing Analysis
17.3.2. Market Share Analysis, 2022
17.3.2.1. By Component
17.3.2.2. By Deployment
17.3.2.3. By End User
17.3.2.4. By Application
17.4. Mexico
17.4.1. Pricing Analysis
17.4.2. Market Share Analysis, 2022
17.4.2.1. By Component
17.4.2.2. By Deployment
17.4.2.3. By End User
17.4.2.4. By Application
17.5. Germany
17.5.1. Pricing Analysis
17.5.2. Market Share Analysis, 2022
17.5.2.1. By Component
17.5.2.2. By Deployment
17.5.2.3. By End User
17.5.2.4. By Application
17.6. United kingdom
17.6.1. Pricing Analysis
17.6.2. Market Share Analysis, 2022
17.6.2.1. By Component
17.6.2.2. By Deployment
17.6.2.3. By End User
17.6.2.4. By Application
17.7. France
17.7.1. Pricing Analysis
17.7.2. Market Share Analysis, 2022
17.7.2.1. By Component
17.7.2.2. By Deployment
17.7.2.3. By End User
17.7.2.4. By Application
17.8. Spain
17.8.1. Pricing Analysis
17.8.2. Market Share Analysis, 2022
17.8.2.1. By Component
17.8.2.2. By Deployment
17.8.2.3. By End User
17.8.2.4. By Application
17.9. Italy
17.9.1. Pricing Analysis
17.9.2. Market Share Analysis, 2022
17.9.2.1. By Component
17.9.2.2. By Deployment
17.9.2.3. By End User
17.9.2.4. By Application
17.10. India
17.10.1. Pricing Analysis
17.10.2. Market Share Analysis, 2022
17.10.2.1. By Component
17.10.2.2. By Deployment
17.10.2.3. By End User
17.10.2.4. By Application
17.11. Malaysia
17.11.1. Pricing Analysis
17.11.2. Market Share Analysis, 2022
17.11.2.1. By Component
17.11.2.2. By Deployment
17.11.2.3. By End User
17.11.2.4. By Application
17.12. Singapore
17.12.1. Pricing Analysis
17.12.2. Market Share Analysis, 2022
17.12.2.1. By Component
17.12.2.2. By Deployment
17.12.2.3. By End User
17.12.2.4. By Application
17.13. Thailand
17.13.1. Pricing Analysis
17.13.2. Market Share Analysis, 2022
17.13.2.1. By Component
17.13.2.2. By Deployment
17.13.2.3. By End User
17.13.2.4. By Application
17.14. China
17.14.1. Pricing Analysis
17.14.2. Market Share Analysis, 2022
17.14.2.1. By Component
17.14.2.2. By Deployment
17.14.2.3. By End User
17.14.2.4. By Application
17.15. Japan
17.15.1. Pricing Analysis
17.15.2. Market Share Analysis, 2022
17.15.2.1. By Component
17.15.2.2. By Deployment
17.15.2.3. By End User
17.15.2.4. By Application
17.16. South Korea
17.16.1. Pricing Analysis
17.16.2. Market Share Analysis, 2022
17.16.2.1. By Component
17.16.2.2. By Deployment
17.16.2.3. By End User
17.16.2.4. By Application
17.17. Australia
17.17.1. Pricing Analysis
17.17.2. Market Share Analysis, 2022
17.17.2.1. By Component
17.17.2.2. By Deployment
17.17.2.3. By End User
17.17.2.4. By Application
17.18. New Zealand
17.18.1. Pricing Analysis
17.18.2. Market Share Analysis, 2022
17.18.2.1. By Component
17.18.2.2. By Deployment
17.18.2.3. By End User
17.18.2.4. By Application
17.19. GCC Countries
17.19.1. Pricing Analysis
17.19.2. Market Share Analysis, 2022
17.19.2.1. By Component
17.19.2.2. By Deployment
17.19.2.3. By End User
17.19.2.4. By Application
17.20. South Africa
17.20.1. Pricing Analysis
17.20.2. Market Share Analysis, 2022
17.20.2.1. By Component
17.20.2.2. By Deployment
17.20.2.3. By End User
17.20.2.4. By Application
17.21. Israel
17.21.1. Pricing Analysis
17.21.2. Market Share Analysis, 2022
17.21.2.1. By Component
17.21.2.2. By Deployment
17.21.2.3. By End User
17.21.2.4. By Application
18. Market Structure Analysis
18.1. Competition Dashboard
18.2. Competition Benchmarking
18.3. Market Share Analysis of Top Players
18.3.1. By Regional
18.3.2. By Component
18.3.3. By Deployment
18.3.4. By End User
18.3.5. By Application
19. Competition Analysis
19.1. Competition Deep Dive
19.1.1. Oracle
19.1.1.1. Overview
19.1.1.2. Product Portfolio
19.1.1.3. Profitability by Market Segments
19.1.1.4. Sales Footprint
19.1.1.5. Strategy Overview
19.1.1.5.1. Marketing Strategy
19.1.2. IBM
19.1.2.1. Overview
19.1.2.2. Product Portfolio
19.1.2.3. Profitability by Market Segments
19.1.2.4. Sales Footprint
19.1.2.5. Strategy Overview
19.1.2.5.1. Marketing Strategy
19.1.3. SAS
19.1.3.1. Overview
19.1.3.2. Product Portfolio
19.1.3.3. Profitability by Market Segments
19.1.3.4. Sales Footprint
19.1.3.5. Strategy Overview
19.1.3.5.1. Marketing Strategy
19.1.4. Allscripts Healthcare Solutions Inc.
19.1.4.1. Overview
19.1.4.2. Product Portfolio
19.1.4.3. Profitability by Market Segments
19.1.4.4. Sales Footprint
19.1.4.5. Strategy Overview
19.1.4.5.1. Marketing Strategy
19.1.5. Medeanalytics, Inc.
19.1.5.1. Overview
19.1.5.2. Product Portfolio
19.1.5.3. Profitability by Market Segments
19.1.5.4. Sales Footprint
19.1.5.5. Strategy Overview
19.1.5.5.1. Marketing Strategy
19.1.6. Health Catalyst
19.1.6.1. Overview
19.1.6.2. Product Portfolio
19.1.6.3. Profitability by Market Segments
19.1.6.4. Sales Footprint
19.1.6.5. Strategy Overview
19.1.6.5.1. Marketing Strategy
19.1.7. Apixio Inc.
19.1.7.1. Overview
19.1.7.2. Product Portfolio
19.1.7.3. Profitability by Market Segments
19.1.7.4. Sales Footprint
19.1.7.5. Strategy Overview
19.1.7.5.1. Marketing Strategy
19.1.8. Optum, Inc.
19.1.8.1. Overview
19.1.8.2. Product Portfolio
19.1.8.3. Profitability by Market Segments
19.1.8.4. Sales Footprint
19.1.8.5. Strategy Overview
19.1.8.5.1. Marketing Strategy
19.1.9. Mckesson Corporation
19.1.9.1. Overview
19.1.9.2. Product Portfolio
19.1.9.3. Profitability by Market Segments
19.1.9.4. Sales Footprint
19.1.9.5. Strategy Overview
19.1.9.5.1. Marketing Strategy
19.1.10. Cerner Corporation
19.1.10.1. Overview
19.1.10.2. Product Portfolio
19.1.10.3. Profitability by Market Segments
19.1.10.4. Sales Footprint
19.1.10.5. Strategy Overview
19.1.10.5.1. Marketing Strategy
20. Assumptions & Acronyms Used
21. Research Methodology
Explore Healthcare Insights
View Reports
Predictive Disease Analytics Market
