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市场调查报告书

商品编码

1735879

2024-2030 年全球临床决策支援系统 (CDSS) 市场

Clinical Decision Support System Market, Global, 2024-2030

出版日期: 2025年05月09日 | 出版商:

Frost & Sullivan | 英文 54 Pages | 商品交期: 最快1-2个工作天内

价格

简介目录

人工智慧整合可改善临床结果，推动转型成长

对有效人口健康管理的日益关注，促使医疗保健机构采用下一代临床决策支援工具，从而推动市场成长。医疗保健系统在临床品质和效率方面持续面临重大挑战，这导致人们更加重视采用临床决策支援系统 (CDSS)。这些工具有助于在医院和居家医疗环境中进行早期诊断和及时、有针对性的临床干预。它们还有助于预防患者併发症，从而减少住院和ICU入院等昂贵干预措施的需求。人工智慧 (AI) 和机器学习（包括互动式人工智慧）的技术进步，正在推动 CDSS 解决方案的持续创新。

Frost & Sullivan 报告概述了全球 CDSS 市场，并对决策证据/通讯协定、决策工作流程、决策分析和决策交付等应用领域进行了详细分析，并提供了收益预测。报告还检验了该市场的驱动因素和限制因素，并指出了该领域变化带来的机会，市场参与者和相关人员应该抓住这些机会。基准年为 2024 年，预测期间为 2025-2030 年。

收益预测

2024 年基准年预计收益为 107.528 亿美元，2024 年至 2030 年研究期间的复合年增长率为 7.6%。

主要竞争对手

Optum
EBSCO
Elsevier
Hearst Health
Merative
Medicomp Systems
Wolters Kluwer
RethinkFirst
Glass Health
UNORK
Premier Inc. (STANTON HEALTH)
Getinge
Motive Medical Intelligence
athenahealth
EvidenceCare
HCA Healthcare
MEDITECH
eClinicalWorks
Wolters Kluwer
RIMIDI
Inovalon
Vizio
Flatiron Health (Roche)
Medecision
MCG Health
Epic
Medical Informatics Corp.
Medtronic
Oracle Health
Philips Healthcare
GE Healthcare
Stat Pearls

CDSS的演变
主要用例
主要市场趋势
主要挑战和价值提案
消费者之声：将人工智慧融入 CDSS
CDSS 中潜在的 GenAI 用例
人工智慧驱动的供应商价值提案
监管情境：FDA 对 CDSS 的处理方法
成长指标
成长动力
成长抑制因素
预测考虑因素
收益预测
按应用分類的收益预测
收益预测分析
价格趋势及预测分析
各地区收益预测
CDSS解决方案吸引力分析
当地吸引力的排名和映射
各地区收益预测分析
收益占有率：竞争热图
收益占有率：竞争热图分析
公司聚焦

成长生成器：决策证据/通讯协定

成长指标
收益预测
各地区收益预测
预测分析

成长动力：决策分析

成长指标
收益预测
各地区收益预测
预测分析

成长引擎：决策工作流程

成长指标
收益预测
各地区收益预测
预测分析

成长动力：决策交付

成长指标
收益预测
各地区收益预测
预测分析

成长机会宇宙

成长机会1：CDSS 中的 AI
成长机会二：重症患者的即时数据
增长机会3：居家照护的照护现场CDSS

附录与后续步骤

成长机会的益处和影响
后续步骤Next steps
附件列表
免责声明

简介目录

Product Code: KB09-48

AI Integration is Driving Transformational Growth by Enabling Improvements in Clinical Outcomes

The increasing focus on effective population health management is prompting healthcare organizations to adopt next-generation clinical decision support tools that drive market growth. Healthcare systems continue to face significant clinical quality and efficiency challenges, leading to a heightened focus on implementing clinical decision support systems (CDSS). These tools facilitate early diagnosis and timely, precise clinical interventions in both hospital and home-based healthcare settings. They also help prevent complications in patient conditions, thereby reducing the need for costly interventions such as hospital readmissions and ICU admissions. Technological advancements in artificial intelligence (AI) and machine learning, including generative AI and conversational AI, are boosting ongoing innovation in CDSS solutions.

This Frost & Sullivan report provides an overview of the global CDSS market, offering a detailed analysis, including a revenue forecast, for each application segment, namely, decision evidence/protocols, decision workflow, decision analytics, and decision delivery. The report also examines the factors driving and restraining this market and identifies the opportunities emerging from the changes in this space for market players and stakeholders to leverage. The base year is 2024, and the forecast period is from 2025 to 2030.

Revenue Forecast

The revenue estimate for the base year 2024 is $10,752.8 million, with a CAGR of 7.6% for the study period from 2024 to 2030.

Scope of Analysis

Clinical decision support (CDS) provides clinicians and healthcare staff with knowledge and person-specific information that helps them improve clinical decisions and enhance patient healthcare.
A clinical decision support system (CDSS) is a broad concept with many definitions that are used variably. It encompasses a variety of tools to enhance decision-making in the clinical workflow.
CDSS includes a mix of evidence (content), analytics, workflow, devices, and software-based solutions that consist of the electronic health record (EHR) and are maintained by an IT platform.
This report delivers a detailed analysis of the CDSS market and its applications, specifically, decision evidence/protocols, decision workflow, decision analytics, and decision delivery.
The report analyzes industry challenges, drivers, and restraints, and offers a revenue forecast for each application area.
It covers important business models, the regulatory outlook, cost structures, and the competitive landscape.
Description of the top growth opportunities for the global CDSS market in the context of user relevance and calls to action has also been provided.
The revenue estimates in this study focus only on revenue attributed to CDSS. In some cases, such as analytics, electronic health records, and device companies, CDSS revenue represents a small part of a larger revenue stream.

The Impact of the Top 3 Strategic Imperatives on the CDSS Industry

Disruptive Technologies

WHY: The CDSS has witnessed significant advancements with the development and integration of new technologies such as AI, cloud, predictive analytics, and mobile platforms, and it will continue to impact CDSS workflows in the next few years. To achieve a highly accessible, flexible, and scalable CDSS solution, end users will continue to look for technology advancements.

FROST PERSPECTIVE: Companies need to identify new use cases and build a strong foundation of evidence-based content. The integration of dynamic AI, specifically, a combination of conversational AI and generative AI (GenAI), can empower end users with easy access to relevant information, enabling them to, for instance, create documents for administrative purposes.

Innovative Business Models

WHY: A high upfront installation and implementation cost has restrained the widespread adoption of CDSS solutions. CDSS has significant potential to improve healthcare outcomes with better clinical recommendations, ultimately benefiting patients and providers in terms of cost and resource utilization.

FROST PERSPECTIVE: Evolving business models such as software-as-a-service (SaaS), subscription models, and risk-based incentives created by technology vendors can provide flexibility in upfront investment and boost CDSS adoption. Growing awareness about the long-term benefits of improved health outcomes and economic growth will drive CDSS growth in the next few years.

Transformative Megatrends

WHY: Medical errors and staff burnout affect healthcare systems' ability to provide optimal patient care. Transitions to home care, a focus on value-based care, an increasing number of data sources, revisions of guidelines, and revenue losses also present significant challenges. Moreover, growing healthcare consumerism and a shift towards personalized care exhaust stakeholders in the face of critical decision-making moments. This is where CDSS has the biggest impact.

FROST PERSPECTIVE: This evolving market demands that vendors regularly update their products and features. Expanding offerings is critical to remaining a viable player. However, such developments cannot happen in isolation. Vendors need to include key end users and decision-makers in their research and development (R&D) programs to best target their investments toward those stakeholders' pain points. To stay ahead of the competition, companies must utilize both organic and inorganic growth pathways.

Key Competitors

Optum
EBSCO
Elsevier
Hearst Health
Merative
Medicomp Systems
Wolters Kluwer
RethinkFirst
Glass Health
UNORK
Premier Inc. (STANTON HEALTH)
Getinge
Motive Medical Intelligence
athenahealth
EvidenceCare
HCA Healthcare
MEDITECH
eClinicalWorks
Wolters Kluwer
RIMIDI
Inovalon
Vizio
Flatiron Health (Roche)
Medecision
MCG Health
Epic
Medical Informatics Corp.
Medtronic
Oracle Health
Philips Healthcare
GE Healthcare
Stat Pearls

Competitive Environment

Number of Competitors

>50 with revenue greater than $1.0 million

Competitive Factors

Cost, performance, support, technology, reliability, contractor relationships

Key End-user Industry Verticals

Providers, hospitals, primary care centers, medical devices, payers

Leading Competitors

Wolters Kluwer, Philips Healthcare, Optum, Hearst Health, Oracle Health

Revenue Share of Top 4 Competitors (2024)

18.3%

Other Notable Competitors

athenahealth, Elsevier, EBSCO, eClinicalWorks, Epic

Distribution Structure

OEMs, retail sales, direct sales, Cloud-based SaaS

Notable Acquisitions and Mergers

Health Catalyst acquired ARMUS Corporation; Oracle acquired Cerner

Growth Drivers

Value-based Care and Population Health Management: The shift towards value-based care models and population health management strategies has placed a greater emphasis on CDSS. These solutions can assist healthcare providers in identifying high-risk patients, stratifying populations, and developing targeted interventions. By supporting evidence-based decision-making, CDSS contribute to improved patient outcomes and better management of chronic conditions, aligning with the goals of value-based care.

Growing Demand for Personalized Medicine: Personalized medicine, which involves tailoring medical treatment to individual patients based on their unique characteristics, is gaining traction. CDSS can play a crucial role in facilitating personalized medicine by integrating patient-specific data, genetic information, and clinical guidelines to provide tailored recommendations. This growing demand for personalized medicine is a significant driver.

Rising Healthcare Costs and Resource Constraints: Healthcare systems worldwide are facing increasing financial pressures and resource constraints. CDSS can help optimize resource utilization by providing real-time clinical insights, reducing unnecessary tests and procedures, and improving overall efficiency. This cost-effectiveness aspect is a significant driver for the adoption of CDSS solutions.

Growth Restraints

Cost and Budgetary Constraints: Implementing and maintaining CDSS software can be costly, especially for smaller healthcare organizations or those with limited budgets. The investments in hardware, software licenses, infrastructure upgrades, and ongoing maintenance and support costs can be significant. Budgetary constraints may deter healthcare providers from adopting CDSS, especially if they perceive the benefits as uncertain or difficult to quantify.

Clinician Acceptance and Alert Fatigue: Clinicians may be skeptical of automated systems' accuracy or be concerned about a loss of autonomy. Moreover, too many or unimportant alerts may lead to alert fatigue among physicians, affecting the usage of CDSS.

System Integration Complexities: Variations in standards for healthcare records can present challenges in effective CDSS integration with existing hospital IT systems.