Clinical Decision Support System Market (Usage Based: Knowledge-based Systems, Expert Laboratory Information Systems, and Machine Learning Systems; Mode of Advice: Passive CDSS and Active CDSS) - Global Industry Analysis, Size, Share, Growth, Trends, and

Clinical Decision Support System Market (Usage Based: Knowledge-based Systems, Expert Laboratory Information Systems, and Machine Learning Systems; Mode of Advice: Passive CDSS and Active CDSS) - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2022-2031

Clinical Decision Support System Market – Scope of Report
TMR’s report on the global clinical decision support system market studies the past as well as the current growth trends and opportunities to gain valuable insights of the indicators of the market during the forecast period from 2022 to 2031. The report provides revenue of the global clinical decision support system market for the period 2017–2031, considering 2021 as the base year and 2031 as the forecast year. The report also provides the compound annual growth rate (CAGR %) of the global clinical decision support system market from 2022 to 2031.

The report has been prepared after an extensive research. Primary research involved bulk of the research efforts, wherein analysts carried out interviews with key opinion leaders, industry leaders, and opinion makers. Secondary research involved referring to key players’ product literature, annual reports, press releases, and relevant documents to understand the clinical decision support system market.

Secondary research also included Internet sources, statistical data from government agencies, websites, and trade associations. Analysts employed a combination of top-down and bottom-up approaches to study various attributes of the global clinical decision support system market.

The report includes an elaborate executive summary, along with a snapshot of the growth behavior of various segments included in the scope of the study. Moreover, the report sheds light on the changing competitive dynamics in the global clinical decision support system market. These serve as valuable tools for existing market players as well as for entities interested in participating in the global clinical decision support system market.

The report delves into the competitive landscape of the global clinical decision support system market. Key players operating in the global clinical decision support system market have been identified and each one of these has been profiled, in terms of various attributes. Company overview, financial standings, recent developments, and SWOT are attributes of players in the global clinical decision support system market profiled in this report.

RESEARCH METHODOLOGY

The research methodology will be a combination of exhaustive primary and secondary research to analyze the market clinical decision support system.

Secondary Research

Secondary research includes a search of company literature, technical writing, patent data, Internet sources, and statistical data from government websites, trade associations, and agencies. This has proven to be the most reliable, effective, and successful approach for obtaining precise data, capturing industry participants’ insights, and recognizing business opportunities.

Secondary research sources that we typically refer, but are not limited to:

Company websites, presentations, annual reports, white papers, technical paper, product brochure
Internal and external proprietary databases and relevant patents
National government documents, statistical databases, and market reports
News articles, press releases, and webcasts specific to companies operating in the market

Specific Secondary Sources:

Industry Sources:
WorldWideScience.org
Elsevier, Inc.
National Institutes of Health (NIH)
PubMed
NCBI
Department of Health Care Service
Trade Data Sources
Trade Map
UN Comtrade
Trade Atlas
Company Information
OneSource Business Browser
Hoover’s
Factiva
Bloomberg
Mergers & Acquisitions
Thomson Mergers & Acquisitions
MergerStat
Profound

Primary Research

During the course of research, we conduct in-depth interviews and discussions with a wide range of key industry participants and opinion leaders. Primary research represents bulk of research efforts, supplemented by extensive secondary research.

We conduct primary interviews on the ongoing basis with industry participants and commentators to validate data and analysis. A typical research interview fulfills the following functions:

Provides first-hand information on market size, market trends, growth trends, competitive landscape, outlook, etc.
Helps in validating and strengthening secondary research findings
Further develops the analysis team’s expertise and market understanding
Primary research involves e-mail interactions, telephonic interviews, as well as face-to-face interviews for each market, category, segment, and sub-segment across geographies

Participants who typically take part in such a process include, but are not limited to:

Industry participants: Marketing/product managers, market intelligence managers, and regional sales managers
Purchasing/Sourcing managers, technical personnel, distributors
Outside experts: Investment bankers, valuation experts, and research analysts specializing in specific markets
Key opinion leaders specializing in different areas corresponding to different industry verticals

List of primary participants, but not limited to:

Advanced Oncotherapy PLC
Danfysik A/S
Hitachi, Ltd.
IBA Worldwide
Mevion Medical Systems, Inc.

Data Triangulation: Information culled from “Secondary & Primary Sources” is cross-checked with “TMR Knowledge Repository”, which is updated every quarter.

Market Estimation: Market size estimations involved in-depth study of product features, technology updates, geographic presence, product demand, sales data (value or volume), historical year-on-year growth, and others. Other approaches were also utilized to derive market size and forecasts. Where no hard data was available, we employed modeling techniques in order to produce comprehensive datasets. A rigorous methodology has been adopted, wherein the available hard data are cross-referenced with the following data types to produce estimates:

Demographic Data: Healthcare expenditure, inflation rates, and others
Industry Indicators: R&D investment, technology stage, and infrastructure, sector growth, and facilities

Market Forecasting: Market forecasts for various segments are derived taking into account drivers, restraints/challenges, and opportunities prevailing in the market and considering advantages/disadvantages of segments/sub-segments over other segments/sub-segments. Business environment, historical sales pattern, unmet needs, competitive intensity, and country-wise surgery data are some of the other pivotal factors, which are considered to derive market forecasts.


1. Preface
1.1. Market Definition and Scope
1.2. Market Segmentation
1.3. Key Research Objectives
1.4. Research Highlights
2. Assumptions and Research Methodology
3. Executive Summary: Global Clinical Decision Support System Market
4. Market Overview
4.1. Introduction
4.1.1. Usage Based Definition
4.1.2. Industry Evolution / Developments
4.2. Overview
4.3. Market Dynamics
4.3.1. Drivers
4.3.2. Restraints
4.3.3. Opportunities
4.4. Global Clinical Decision Support System Market Analysis and Forecast, 2017–2031
4.4.1. Market Revenue Projections (US$ Mn)
5. Key Insights
5.1. Technological Advancements
5.2. Key Industry Events (mergers, acquisitions, partnerships, etc.)
5.3. COVID-19 Pandemic Impact on Industry (value chain and short / mid / long term impact)
6. Global Clinical Decision Support System Market Analysis and Forecast. by Usage Based
6.1. Introduction & Definition
6.2. Key Findings / Developments
6.3. Market Value Forecast, by Usage Based, 2017–2031
6.3.1. Knowledge-based Systems
6.3.2. Expert Laboratory Information Systems
6.3.3. Machine Learning Systems
6.4. Market Attractiveness Analysis, by Usage Based
7. Global Clinical Decision Support System Market Analysis and Forecast. by Mode of Advice
7.1. Introduction & Definition
7.2. Key Findings / Developments
7.3. Market Value Forecast, by Mode of Advice, 2017–2031
7.3.1. Passive CDSS
7.3.2. Active CDSS
7.4. Market Attractiveness Analysis, by Mode of Advice
8. Global Clinical Decision Support System Market Analysis and Forecast. by Delivery Model
8.1. Introduction & Definition
8.2. Key Findings / Developments
8.3. Market Value Forecast, by Delivery Model, 2017–2031
8.3.1. On-premises
8.3.2. Web-based
8.3.3. Cloud-based
8.4. Market Attractiveness Analysis, by Delivery Model
9. Global Clinical Decision Support System Market Analysis and Forecast. by Application
9.1. Introduction & Definition
9.2. Key Findings / Developments
9.3. Market Value Forecast, by Application, 2017–2031
9.3.1. Drug Databases
9.3.2. Care Plans
9.3.3. Diagnostic Decision Support
9.3.4. Disease Reference
9.3.5. Others
9.4. Market Attractiveness Analysis, by Application
10. Global Clinical Decision Support System Market Analysis and Forecast. by End-user
10.1. Introduction & Definition
10.2. Key Findings / Developments
10.3. Market Value Forecast, by End-user, 2017–2031
10.3.1. Hospitals
10.3.2. Diagnostic Centers
10.3.3. Clinics
10.3.4. Others
10.4. Market Attractiveness Analysis, by End-user
11. Global Clinical Decision Support System Market Analysis and Forecast. by Region
11.1. Key Findings
11.2. Market Value Forecast, by Region
11.2.1. North America
11.2.2. Europe
11.2.3. Asia Pacific
11.2.4. Latin America
11.2.5. Middle East & Africa
11.3. Market Attractiveness Analysis, by Region
12. North America Clinical Decision Support System Market Analysis and Forecast
12.1. Introduction
12.1.1. Key Findings
12.2. Market Value Forecast, by Usage Based, 2017–2031
12.2.1. Knowledge-based Systems
12.2.2. Expert Laboratory Information Systems
12.2.3. Machine Learning Systems
12.3. Market Value Forecast, by Mode of Advice, 2017–2031
12.3.1. Passive CDSS
12.3.2. Active CDSS
12.4. Market Value Forecast, by Delivery Model, 2017–2031
12.4.1. On-premises
12.4.2. Web-based
12.4.3. Cloud-based
12.5. Market Value Forecast, by Application, 2017–2031
12.5.1. Drug Databases
12.5.2. Care Plans
12.5.3. Diagnostic Decision Support
12.5.4. Disease Reference
12.5.5. Others
12.6. Market Value Forecast, by End-user, 2017–2031
12.6.1. Hospitals
12.6.2. Diagnostic Centers
12.6.3. Clinics
12.6.4. Others
12.7. Market Value Forecast, by Country, 2017–2031
12.7.1. U.S.
12.7.2. Canada
12.8. Market Attractiveness Analysis
12.8.1. By Usage Based
12.8.2. By Mode of Advice
12.8.3. By Delivery Model
12.8.4. By Application
12.8.5. By End-user
12.8.6. By Country
13. Europe Clinical Decision Support System Market Analysis and Forecast
13.1. Introduction
13.1.1. Key Findings
13.2. Market Value Forecast, by Usage Based, 2017–2031
13.2.1. Knowledge-based Systems
13.2.2. Expert Laboratory Information Systems
13.2.3. Machine Learning Systems
13.3. Market Value Forecast, by Mode of Advice, 2017–2031
13.3.1. Passive CDSS
13.3.2. Active CDSS
13.4. Market Value Forecast, by Delivery Model, 2017–2031
13.4.1. On-premises
13.4.2. Web-based
13.4.3. Cloud-based
13.5. Market Value Forecast, by Application, 2017–2031
13.5.1. Drug Databases
13.5.2. Care Plans
13.5.3. Diagnostic Decision Support
13.5.4. Disease Reference
13.5.5. Others
13.6. Market Value Forecast, by End-user, 2017–2031
13.6.1. Hospitals
13.6.2. Diagnostic Centers
13.6.3. Clinics
13.6.4. Others
13.7. Market Value Forecast, by Country/Sub-region, 2017–2031
13.7.1. Germany
13.7.2. U.K.
13.7.3. France
13.7.4. Spain
13.7.5. Italy
13.7.6. Rest of Europe
13.8. Market Attractiveness Analysis
13.8.1. By Usage Based
13.8.2. By Mode of Advice
13.8.3. By Delivery Model
13.8.4. By Application
13.8.5. By End-user
13.8.6. By Country/Sub-region
14. Asia Pacific Clinical Decision Support System Market Analysis and Forecast
14.1. Introduction
14.1.1. Key Findings
14.2. Market Value Forecast, by Usage Based, 2017–2031
14.2.1. Knowledge-based Systems
14.2.2. Expert Laboratory Information Systems
14.2.3. Machine Learning Systems
14.3. Market Value Forecast, by Mode of Advice, 2017–2031
14.3.1. Passive CDSS
14.3.2. Active CDSS
14.4. Market Value Forecast, by Delivery Model, 2017–2031
14.4.1. On-premises
14.4.2. Web-based
14.4.3. Cloud-based
14.5. Market Value Forecast, by Application, 2017–2031
14.5.1. Drug Databases
14.5.2. Care Plans
14.5.3. Diagnostic Decision Support
14.5.4. Disease Reference
14.5.5. Others
14.6. Market Value Forecast, by End-user, 2017–2031
14.6.1. Hospitals
14.6.2. Diagnostic Centers
14.6.3. Clinics
14.6.4. Others
14.7. Market Value Forecast, by Country/Sub-region, 2017–2031
14.7.1. China
14.7.2. Japan
14.7.3. India
14.7.4. Australia & New Zealand
14.7.5. Rest of Asia Pacific
14.8. Market Attractiveness Analysis
14.8.1. By Usage Based
14.8.2. By Mode of Advice
14.8.3. By Delivery Model
14.8.4. By Application
14.8.5. By End-user
14.8.6. By Country/Sub-region
15. Latin America Clinical Decision Support System Market Analysis and Forecast
15.1. Introduction
15.1.1. Key Findings
15.2. Market Value Forecast, by Usage Based, 2017–2031
15.2.1. Knowledge-based Systems
15.2.2. Expert Laboratory Information Systems
15.2.3. Machine Learning Systems
15.3. Market Value Forecast, by Mode of Advice, 2017–2031
15.3.1. Passive CDSS
15.3.2. Active CDSS
15.4. Market Value Forecast, by Delivery Model, 2017–2031
15.4.1. On-premises
15.4.2. Web-based
15.4.3. Cloud-based
15.5. Market Value Forecast, by Application, 2017–2031
15.5.1. Drug Databases
15.5.2. Care Plans
15.5.3. Diagnostic Decision Support
15.5.4. Disease Reference
15.5.5. Others
15.6. Market Value Forecast, by End-user, 2017–2031
15.6.1. Hospitals
15.6.2. Diagnostic Centers
15.6.3. Clinics
15.6.4. Others
15.7. Market Value Forecast, by Country/Sub-region, 2017–2031
15.7.1. Brazil
15.7.2. Mexico
15.7.3. Rest of Latin America
15.8. Market Attractiveness Analysis
15.8.1. By Usage Based
15.8.2. By Mode of Advice
15.8.3. By Delivery Model
15.8.4. By Application
15.8.5. By End-user
15.8.6. By Country/Sub-region
16. Middle East & Africa Clinical Decision Support System Market Analysis and Forecast
16.1. Introduction
16.1.1. Key Findings
16.2. Market Value Forecast, by Usage Based, 2017–2031
16.2.1. Knowledge-based Systems
16.2.2. Expert Laboratory Information Systems
16.2.3. Machine Learning Systems
16.3. Market Value Forecast, by Mode of Advice, 2017–2031
16.3.1. Passive CDSS
16.3.2. Active CDSS
16.4. Market Value Forecast, by Delivery Model, 2017–2031
16.4.1. On-premises
16.4.2. Web-based
16.4.3. Cloud-based
16.5. Market Value Forecast, by Application, 2017–2031
16.5.1. Drug Databases
16.5.2. Care Plans
16.5.3. Diagnostic Decision Support
16.5.4. Disease Reference
16.5.5. Others
16.6. Market Value Forecast, by End-user, 2017–2031
16.6.1. Hospitals
16.6.2. Diagnostic Centers
16.6.3. Clinics
16.6.4. Others
16.7. Market Value Forecast, by Country/Sub-region, 2017–2031
16.7.1. GCC Countries
16.7.2. South Africa
16.7.3. Rest of Middle East & Africa
16.8. Market Attractiveness Analysis
16.8.1. By Usage Based
16.8.2. By Mode of Advice
16.8.3. By Delivery Model
16.8.4. By Application
16.8.5. By End-user
16.8.6. By Country/Sub-region
17. Competition Landscape
17.1. Market Player - Competition Matrix
17.2. Market Share Analysis, by Company, 2021
17.3. Company Profiles
17.3.1. Allscripts Healthcare Solutions, Inc.
17.3.1.1. Company Overview (HQ, Business Segments, Employee)
17.3.1.2. Product Portfolio
17.3.1.3. SWOT Analysis
17.3.1.4. Strategic Overview
17.3.2. First Databank, Inc.
17.3.2.1. Company Overview (HQ, Business Segments, Employee)
17.3.2.2. Product Portfolio
17.3.2.3. SWOT Analysis
17.3.2.4. Strategic Overview
17.3.3. Truven Health Analytics
17.3.3.1. Company Overview (HQ, Business Segments, Employee)
17.3.3.2. Product Portfolio
17.3.3.3. SWOT Analysis
17.3.3.4. Strategic Overview
17.3.4. Cerner
17.3.4.1. Company Overview (HQ, Business Segments, Employee)
17.3.4.2. Product Portfolio
17.3.4.3. SWOT Analysis
17.3.4.4. Strategic Overview
17.3.5. Philips Healthcare
17.3.5.1. Company Overview (HQ, Business Segments, Employee)
17.3.5.2. Product Portfolio
17.3.5.3. SWOT Analysis
17.3.5.4. 17.3.5.4.Strategic Overview
17.3.6. Siemens Healthcare
17.3.6.1. Company Overview (HQ, Business Segments, Employee)
17.3.6.2. Product Portfolio
17.3.6.3. SWOT Analysis
17.3.6.4. Strategic Overview
17.3.7. Optum, Inc. (UnitedHealth Group)
17.3.7.1. Company Overview (HQ, Business Segments, Employee)
17.3.7.2. Product Portfolio
17.3.7.3. SWOT Analysis
17.3.7.4. Strategic Overview
17.3.8. GE Healthcare
17.3.8.1. Company Overview (HQ, Business Segments, Employee)
17.3.8.2. Product Portfolio
17.3.8.3. SWOT Analysis
17.3.8.4. Strategic Overview
17.3.9. Epic Systems Corporation Inc.
17.3.9.1. Company Overview (HQ, Business Segments, Employee)
17.3.9.2. Product Portfolio
17.3.9.3. SWOT Analysis
17.3.9.4. Strategic Overview

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