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상품코드
1733810

세계의 임상 의사결정 지원 시스템(CDSS) 시장 : 컴포넌트별, 제공 형태별, 용도별, 지역별 및 예측

Global Clinical Decision Support Systems (CDSS) Market By Component (Service, & Hardware), By Delivery Mode (Web Based, Standalone), By Application (Medical Diagnosis, Alerts and Reminders), By Geographic Scope And Forecast

발행일: | 리서치사: Verified Market Research | 페이지 정보: 영문 202 Pages | 배송안내 : 2-3일 (영업일 기준)

    
    
    



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임상 의사결정 지원 시스템(CDSS) 시장 규모 및 전망

임상 의사결정 지원 시스템(CDSS) 시장 규모는 2024년 14억 1,669만 달러로 평가되었고, 2026-2032년 연평균 11.21% 성장하여 2032년에는 33억 1,456만 달러에 달할 것으로 예측됩니다.

임상 의사결정 지원 시스템(CDSS)은 근거에 기반한 추천, 경고, 인사이트를 제공하여 의료 전문가가 정보에 입각한 임상적 판단을 내릴 수 있도록 설계된 첨단 소프트웨어 툴입니다.

이러한 시스템은 주로 전자 의료 기록(EHR)에 통합되어 환자 데이터에 대한 원활한 액세스를 제공하고 임상의가 적절한 시기에 관련 정보를 이용할 수 있도록 합니다.

CDSS는 병원 및 클리닉에서 진단, 배합, 만성 질환 관리를 지원하기 위해 널리 사용되고 있습니다.

그 장점으로는 의료 실수 감소, 의료 품질 향상, 임상 워크플로우의 효율성 향상 등이 있습니다.

전자 의료 기록(EHR)에 통합된 CDSS는 임상의가 환자를 진료하는 동안 실시간 정보에 접근할 수 있도록 하여 실수를 줄이고, 워크플로우를 간소화하며, 전반적인 환자 치료 개선에 기여합니다.

CDSS는 권고의 정확성과 환자의 안전을 보장하기 위해 엄격한 규제 가이드라인을 준수하여 잘못된 임상적 판단이나 지연의 위험을 최소화합니다.

임상 의사결정 지원 시스템 세계 시장 역학

세계 임상 의사결정 지원 시스템 시장을 형성하는 주요 시장 역학은 다음과 같습니다.

주요 시장 성장 촉진요인

첨단 헬스케어 솔루션에 대한 수요 증가: 효율적인 의료 서비스 제공 시스템과 데이터 기반 임상적 판단에 대한 요구가 높아지면서 환자 결과를 개선하고 오류를 줄이는 CDSS의 도입이 증가하고 있습니다.

전자건강기록(EHR)의 보급: EHR 시스템의 보급은 CDSS 통합의 길을 열어 정확한 진단과 치료를 위한 환자 데이터에 대한 실시간 접근성을 향상시키고 있습니다.

인공지능(AI)과 머신러닝의 발전: CDSS에서 AI와 ML의 통합은 예측 분석과 의사결정을 강화하고 임상 결과를 개선할 수 있습니다.

개인 맞춤형 의료에 대한 관심 증가: CDSS 시스템은 환자별 데이터에 기반한 맞춤형 치료 계획을 제공하는 데 도움이 되기 때문에 정밀의료에 대한 채택이 증가하고 있습니다.

정부 지원책과 규제: 세계 각국 정부는 의료의 질과 환자의 안전을 높이기 위해 CDSS를 포함한 헬스케어 IT 시스템 활용을 장려하고 있습니다.

만성질환 증가: 당뇨병, 심혈관 질환과 같은 만성질환 증가로 인해 의료진이 복잡한 치료 계획을 효과적으로 관리할 수 있도록 돕는 임상 지원 도구의 필요성이 증가하고 있습니다.

주요 과제

기존 시스템과의 통합 문제: CDSS는 기존 전자의무기록(EHR) 시스템과의 원활한 통합이 어려운 경우가 많아 워크플로우의 혼란과 효율성 저하를 야기하고 있습니다.

데이터 프라이버시 및 보안 문제: 환자 데이터 사용이 증가함에 따라 기밀 정보의 프라이버시 및 보안을 보장하는 것은 특히 HIPAA와 같은 엄격한 헬스케어 규제 하에서 큰 도전이 되고 있습니다.

의료 전문가들의 거부감: 일부 의료인들은 CDSS가 의료인의 자율성에 미치는 영향에 대한 우려와 CDSS가 권장하는 진료 내용의 정확성 및 신뢰성에 대한 의구심 때문에 CDSS 도입에 거부감을 보이기도 합니다.

높은 도입 비용: 소프트웨어, 하드웨어, 교육을 포함한 CDSS 도입의 초기 비용은 예산이 한정된 소규모 의료 시설에 장벽이 될 수 있습니다.

데이터 품질에 대한 의존성: CDSS의 유효성은 시스템에 입력되는 데이터의 정확성과 완전성에 크게 의존합니다. 불완전하거나 부정확한 데이터는 잘못된 임상 권고로 이어질 수 있습니다.

법적, 윤리적 문제: CDSS가 잘못된 추천을 할 경우의 책임은 여전히 회색지대이며, 의료 서비스 제공업체에게 법적, 윤리적 문제를 야기할 수 있습니다.

주요 동향

AI와 머신러닝의 통합: CDSS에서 인공지능과 머신러닝의 활용이 확대되고 있으며, 보다 정확한 예측, 실시간 분석, 방대한 데이터 세트를 통한 개인화된 치료 추천을 가능하게 하고 있습니다.

클라우드 기반 CDSS: 클라우드 기반 CDSS에 대한 수요가 증가하고 있으며, 보다 쉬운 확장성, 실시간 업데이트, 임상 데이터에 대한 원격 액세스를 제공하여 의료 서비스 제공의 효율성을 향상시키고 있습니다.

모바일 및 원격 액세스: 원격 의료가 확대됨에 따라 CDSS는 모바일 플랫폼에 최적화되고 있으며, 의료 서비스 제공업체는 이동 중에도 중요한 의사결정 지원 도구에 액세스하여 원격지에서도 환자 치료를 개선할 수 있습니다.

EHR 시스템과의 상호운용성: 전자건강기록(EHR) 시스템과 원활하게 통합할 수 있는 CDSS의 개발에 점점 더 많은 관심이 집중되고 있으며, 더 나은 데이터 흐름을 가능하게 하고, 임상 워크플로우를 개선하고 있습니다.

개인 맞춤형 의료: CDSS는 환자의 유전자 프로파일, 병력, 실시간 건강 데이터를 기반으로 개인별 치료 계획을 제공하는 개인 맞춤형 의료에 대응하고 있습니다.

규제 준수 및 데이터 보안: HIPAA와 같은 엄격한 헬스케어 규제에 따라 CDSS 시스템이 컴플라이언스 기준을 충족하고 환자 데이터를 보호하는 것이 중요해지고 있습니다.

목차

제1장 서론

  • 시장의 정의
  • 시장 세분화
  • 조사 방법

제2장 주요 요약

  • 주요 조사 결과
  • 시장 개요
  • 시장 하이라이트

제3장 시장 개요

  • 시장 규모와 성장 가능성
  • 시장 동향
  • 시장 성장 촉진요인
  • 시장 성장 억제요인
  • 시장 기회
  • Porter의 Five Forces 분석

제4장 임상 의사결정 지원 시스템(CDSS) 시장 : 컴포넌트별

  • 하드웨어
  • 소프트웨어
  • 서비스

제5장 임상 의사결정 지원 시스템(CDSS) 시장 : 제공 형태별

  • 웹 기반
  • 스탠드얼론형
  • 통합형

제6장 임상 의사결정 지원 시스템(CDSS) 시장 : 용도별

  • 의료 진단
  • 경계체제와 리마인다
  • 배합 결정 지원
  • 정보 검색

제7장 지역별 분석

  • 북미
  • 미국
  • 캐나다
  • 멕시코
  • 유럽
  • 영국
  • 독일
  • 프랑스
  • 이탈리아
  • 아시아태평양
  • 중국
  • 일본
  • 인도
  • 호주
  • 라틴아메리카
  • 브라질
  • 아르헨티나
  • 칠레
  • 중동 및 아프리카
  • 남아프리카공화국
  • 사우디아라비아
  • 아랍에미리트(UAE)

제8장 시장 역학

  • 시장 성장 촉진요인
  • 시장 성장 억제요인
  • 시장 기회
  • COVID-19의 시장에 대한 영향

제9장 경쟁 구도

  • 주요 기업
  • 시장 점유율 분석

제10장 기업 개요

  • Cerner Corporation
  • McKesson Corporation
  • Epic Systems Corporation
  • IBM Watson Health
  • Allscripts Healthcare Solutions,Inc.
  • MEDITECH
  • Wolters Kluwer Health
  • Zynx Health
  • a subsidiary of Hearst Corporation
  • Siemens Healthineers
  • Elsevier B.V.
  • Oracle(Cerner Corporation)
  • NextGen Healthcare Inc
  • Koninklijke Philips N.V
  • Agfa-Gevaert Group

제11장 시장 전망과 기회

  • 신기술
  • 향후 시장 동향
  • 투자 기회

제12장 부록

  • 약어 리스트
  • 공급원과 참고 문헌
LSH 25.06.12

Clinical Decision Support Systems (CDSS) Market Size And Forecast

Clinical Decision Support Systems (CDSS) Market size was valued to be USD 1416.69 Million in the year 2024 and it is expected to reach USD 3314.56 Million by 2032, growing at a CAGR of 11.21% from 2026 to 2032.

Clinical Decision Support Systems (CDSS) are advanced software tools designed to aid healthcare professionals in making informed clinical decisions by providing evidence-based recommendations, alerts, and insights.

These systems are primarily integrated into Electronic Health Records (EHR), offering seamless access to patient data and ensuring that relevant information is available to clinicians at the right time.

CDSS is widely used in hospitals and clinics to assist with diagnosis, prescription, and chronic disease management.

Its benefits include reducing medical errors, improving the quality of care, and enhancing clinical workflow efficiency.

Integrated into Electronic Health Records (EHR), CDSS ensures that clinicians have access to real-time information during patient consultations, helping reduce errors, streamline workflows, and improve overall patient care.

CDSS is subject to strict regulatory guidelines to ensure the accuracy of recommendations and patient safety, minimizing risks of incorrect or delayed clinical decisions.

Global Clinical Decision Support System Market Dynamics

The key market dynamics that are shaping the global clinical decision support system Market include:

Key Market Drivers

Rising Demand for Advanced Healthcare Solutions: The growing need for efficient healthcare delivery systems and data-driven clinical decisions has driven the adoption of CDSS to enhance patient outcomes and reduce errors.

Increasing Adoption of Electronic Health Records (EHR): The widespread use of EHR systems has paved the way for the integration of CDSS, improving real-time access to patient data for accurate diagnosis and treatment.

Advancements in Artificial Intelligence (AI) and Machine Learning: The integration of AI and ML in CDSS enhances predictive analysis and decision-making, leading to improved clinical outcomes.

Growing Focus on Personalized Medicine: CDSS systems help in providing personalized treatment plans based on patient-specific data, which has increased their adoption in precision medicine.

Supportive Government Initiatives and Regulations: Governments across the globe are promoting the use of healthcare IT systems, including CDSS, to enhance healthcare quality and patient safety.

Rising Incidence of Chronic Diseases: The growing prevalence of chronic diseases like diabetes and cardiovascular disorders has increased the need for clinical support tools to assist healthcare professionals in managing complex treatment plans effectively.

Key Challenges

Integration Issues with Existing Systems: CDSS often face difficulties in integrating seamlessly with legacy electronic health record (EHR) systems, causing workflow disruptions and limiting efficiency.

Data Privacy and Security Concerns: With the increasing use of patient data, ensuring the privacy and security of sensitive information poses a significant challenge, especially with strict healthcare regulations like HIPAA.

Resistance to Adoption by Healthcare Professionals: Some clinicians may resist adopting CDSS due to concerns over its impact on their autonomy or doubts about the accuracy and reliability of the system's recommendations.

High Implementation Costs: The initial cost of implementing CDSS, including software, hardware, and training, can be a barrier for smaller healthcare facilities with limited budgets.

Dependence on Data Quality: The effectiveness of CDSS heavily relies on the accuracy and completeness of the data fed into the system. Incomplete or inaccurate data can lead to incorrect clinical recommendations.

Legal and Ethical Issues: Liability in cases where CDSS makes incorrect recommendations is still a grey area, posing potential legal and ethical challenges for healthcare providers.

Key Trends

AI and Machine Learning Integration: The use of artificial intelligence and machine learning in CDSS is growing, enabling more accurate predictions, real-time analytics, and personalized treatment recommendations based on vast datasets.

Cloud-based CDSS: There is a rising trend toward cloud-based CDSS, offering easier scalability, real-time updates, and remote access to clinical data, improving efficiency in healthcare delivery.

Mobile and Remote Access: As telemedicine expands, CDSS is being optimized for mobile platforms, allowing healthcare providers to access critical decision support tools on the go, enhancing patient care even in remote locations.

Interoperability with EHR Systems: Increasing focus is on developing CDSS that can seamlessly integrate with electronic health records (EHR) systems, enabling better data flow and improving clinical workflows.

Personalized Medicine: CDSS is increasingly being tailored for personalized medicine, offering individualized treatment plans based on patient's genetic profiles, medical history, and real-time health data.

Regulatory Compliance and Data Security: With stringent healthcare regulations like HIPAA, there is a growing emphasis on ensuring CDSS systems meet compliance standards and secure patient data.

Global Clinical Decision Support Systems Market Regional Analysis

Here is a more detailed regional analysis of the global clinical decision support systems Market:

North America

North America is substantially dominating the Global Clinical Decision Support Systems Market and is expected to continue its dominance throughout the forecast period.

The region, particularly the United States, benefits from a well-developed healthcare infrastructure that supports the integration of advanced technologies like CDSS.

The widespread adoption of electronic health records (EHR) systems has further facilitated the implementation of CDSS, allowing healthcare providers to enhance patient care by accessing real-time, evidence-based guidance.

The substantial investments in healthcare IT across the region have accelerated the deployment of CDSS. Government initiatives, such as the U.S.

The Health Information Technology for Economic and Clinical Health (HITECH) Act, has incentivized the adoption of health information technologies, further bolstering the market's growth.

The presence of major players in the CDSS industry, including companies like IBM, Cerner, and Allscripts, also contributes to North America's leadership in the market.

These companies invest heavily in research and development to advance CDSS technologies, improving their capabilities and making them more accessible to healthcare providers.

The favorable regulations that prioritize patient safety, clinical efficiency, and the use of technology in healthcare enhance the adoption of CDSS, solidifying North America's status as the leading region in the global market.

Asia Pacific

Asia Pacific is anticipated to be the fastest-growing region in the Global Clinical Decision Support Systems Market during the forecast period.

The increasing demand for advanced healthcare solutions in countries like China, India, Japan, and South Korea, where healthcare infrastructure is undergoing significant modernization.

With rising healthcare costs, there is a growing need for systems that enhance clinical efficiency and reduce medical errors, both of which CDSS are designed to address.

Governments in the Asia-Pacific region are increasingly investing in healthcare IT infrastructure to improve the quality of care and patient outcomes.

Countries like China and India are focusing on digitizing their healthcare systems, which creates opportunities for the adoption of CDSS.

The region's expanding population, coupled with an increase in chronic diseases such as diabetes and cardiovascular conditions, is fueling demand for advanced decision-making tools in clinical settings.

The adoption of electronic health records (EHR) in various Asia-Pacific countries further supports the growth of CDSS, as these systems are often integrated to provide real-time, data-driven insights for healthcare providers.

The region's growing focus on artificial intelligence and machine learning in healthcare is fostering innovation and advancements in CDSS technologies.

However, despite its rapid growth, the Asia-Pacific region faces challenges like inadequate healthcare IT infrastructure in rural areas and concerns around data security, which may slow down the adoption process.

Global Clinical Decision Support Systems Market: Segmentation Analysis

The Global Clinical Decision Support Systems Market is segmented based on Component, Delivery Mode, Application, And Geography.

Clinical Decision Support Systems Market, By Component

  • Service
  • Hardware
  • Software

Based on the Components, the Global Clinical Decision Support Systems (CDSS) Market is segmented into Service, Hardware, and Software. The Software segment is exhibiting growth in the Global Clinical Decision Support Systems (CDSS) Market owing to the increasing need for advanced analytical tools and algorithms that assist in clinical decision-making. This growth is driven by the rising adoption of electronic health records (EHRs) and the integration of artificial intelligence (AI) and machine learning technologies into healthcare systems. The demand for software solutions that can provide real-time, evidence-based recommendations is rising, as these tools enhance diagnostic accuracy and improve patient outcomes.

Clinical Decision Support Systems Market, By Delivery Mode

  • Web Based
  • Standalone
  • Integrated

Based on the Delivery Mode, Global Clinical Decision Support Systems (CDSS) Market is divided into Web-Based, Standalone, and Integrated Systems. The Web-Based segment is showing significant growth in the Global Clinical Decision Support Systems (CDSS) Market owing to the increasing preference for cloud-based solutions that offer accessibility from various locations and devices. This delivery mode provides healthcare professionals with real-time, remote access to decision support tools, enhancing collaborative and timely care.

Clinical Decision Support Systems Market, By Application

  • Medical Diagnosis
  • Alerts and Reminders
  • Prescription Decision Support
  • Information Retrieval

Based on the Application, Global Clinical Decision Support Systems (CDSS) Market is divided into Medical Diagnosis, Alerts and Reminders, Prescription Decision Support, and Information Retrieval. The Medical Diagnosis segment is experiencing significant growth in the Global Clinical Decision Support Systems (CDSS) Market owing to its critical role in assisting healthcare professionals with accurate and timely diagnostic support. The increasing complexity of medical conditions and the need for precise decision-making tools are driving this growth. Medical Diagnosis systems utilize advanced algorithms and vast medical databases to provide actionable insights and recommendations, enhancing diagnostic accuracy and improving patient care.

Clinical Decision Support Systems Market, By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Rest of the World

Based on the geographical distribution, the Clinical Decision Support Systems (CDSS) Market is segmented into North America, Europe, Asia-Pacific, and Rest of the World. The North American region is dominating the Global Clinical Decision Support Systems (CDSS) Market owing to its advanced healthcare infrastructure, high adoption rates of innovative technologies, and substantial investments in healthcare IT. The presence of key market players and a strong focus on enhancing healthcare delivery through advanced clinical decision-support tools contribute to the region's leading position. North America's emphasis on improving patient outcomes and efficiency in medical practices further supports the growth of the CDSS Market in this region.

Key Players

The "Global Clinical Decision Support Systems Market" study report provides valuable insight with an emphasis on the global market. The major players in the market are Cerner Corporation, McKesson Corporation, Epic Systems Corporation, IBM Watson Health, Allscripts Healthcare Solutions, Inc, MEDITECH, Wolters Kluwer Health, Zynx Health, a subsidiary of Hearst Corporation, Siemens Healthineers, Elsevier B.V, Oracle (Cerner Corporation), NextGen Healthcare Inc, Koninklijke Philips N.V, Agfa-Gevaert Group This section offers in-depth analysis through a company overview, position analysis, the regional and industrial footprint of the company, and the ACE matrix for insightful competitive analysis. The section also provides an exhaustive analysis of the financial performances of mentioned players in the given market.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Global Clinical Decision Support Systems Market Key Developments

  • In October 2023, Wolters Kluwer Health announced the launch of AI Labs, a collaborative resource designed to integrate generative AI with UpToDate, its clinical decision support (CDS) solution, enabling medical professionals to make better-informed decisions.
  • In August 2023, GE HealthCare announced the launch of CardioVisio for Atrial Fibrillation, a patient-centric, digital CDS tool aimed at facilitating precision care.
  • In February 2023, EBSCO Information Services enhanced the DynaMedex Mobile App with new features to improve clinical decision support. These enhancements optimized the mobile experience for users, allowing clinicians to deliver evidence-based patient care more efficiently.
  • In May 2020, DHIndia announced a partnership with EHRC@IIITB and Healthelife to develop a CDSS for COVID-19 screening. This collaboration also led to the creation of a minimal triage application for frontline doctors. In March 2020, IBM Watson Health partnered with EBSCO Information Services to enhance CDSS capabilities and operations for healthcare systems and providers.

TABLE OF CONTENTS

1. Introduction

  • Market Definition
  • Market Segmentation
  • Research Methodology

2. Executive Summary

  • Key Findings
  • Market Overview
  • Market Highlights

3. Market Overview

  • Market Size and Growth Potential
  • Market Trends
  • Market Drivers
  • Market Restraints
  • Market Opportunities
  • Porter's Five Forces Analysis

4. Clinical Decision Support System (CDSS) Market, By Components

  • Hardware
  • Software
  • Services

5. Clinical Decision Support System (CDSS) Market, By Delivery Mode

  • Web-based
  • Standalone
  • Integrated

6. Clinical Decision Support System (CDSS) Market, By Application

  • Medical Diagnosis
  • Alerts and Reminders
  • Prescription Decision Support
  • Information Retrieval

7. Regional Analysis

  • North America
  • United States
  • Canada
  • Mexico
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Asia-Pacific
  • China
  • Japan
  • India
  • Australia
  • Latin America
  • Brazil
  • Argentina
  • Chile
  • Middle East and Africa
  • South Africa
  • Saudi Arabia
  • UAE

8. Market Dynamics

  • Market Drivers
  • Market Restraints
  • Market Opportunities
  • Impact of COVID-19 on the Market

9. Competitive Landscape

  • Key Players
  • Market Share Analysis

10. Company Profiles

  • Cerner Corporation
  • McKesson Corporation
  • Epic Systems Corporation
  • IBM Watson Health
  • Allscripts Healthcare Solutions,Inc.
  • MEDITECH
  • Wolters Kluwer Health
  • Zynx Health
  • a subsidiary of Hearst Corporation
  • Siemens Healthineers
  • Elsevier B.V.
  • Oracle (Cerner Corporation)
  • NextGen Healthcare Inc
  • Koninklijke Philips N.V
  • Agfa-Gevaert Group

11. Market Outlook and Opportunities

  • Emerging Technologies
  • Future Market Trends
  • Investment Opportunities

12. Appendix

  • List of Abbreviations
  • Sources and References
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