市場調查報告書
商品編碼
1466428
醫療保健分析市場:按技術、組件、部署、應用程式、最終用戶分類 - 2024-2030 年全球預測Healthcare Analytics Market by Technology (Descriptive Analytics, Predictive Analytics, Prescriptive Analytics), Component (Services, Software), Deployment, Application, End-User - Global Forecast 2024-2030 |
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2023年醫療保健分析市場規模預計為362.9億美元,預計2024年將達到449.3億美元,複合年成長率為24.07%,到2030年將達到1643.3億美元。
醫療保健分析分析與醫療保健服務相關的資料,以提供有助於改善患者護理和健康結果的見解。適當的醫療保健資料分析使醫療保健和醫療專業人員能夠做出更具成本效益的決策,從而影響患者照護。資料可用於改善患者健康和臨床結果。隨著技術的進步,醫療保健產業正在採用電子健康記錄(EHR) 和分析來簡化醫療流程。世界各國政府都致力於遏制與支付相關的醫療保健詐欺,而醫療保健分析技術可以協助該行業監控詐欺。然而,與現有模型的整合、互通性和有限的資料隱私條款正在阻礙產品的普及。基於人工智慧和巨量資料的先進醫療分析技術可以透過更加重視安全來幫助解決這些問題。此外,全球對智慧醫院設施的投資正在增加,醫療分析軟體和服務的部署預計將加速。市場參與者透過引入各種醫療保健分析套件(包括預測分析和臨床決策支援系統)來增加其在醫療保健領域的影響力。
主要市場統計 | |
---|---|
基準年[2023] | 362.9億美元 |
預測年份 [2024] | 449.3億美元 |
預測年份 [2030] | 1643.3億美元 |
複合年成長率(%) | 24.07% |
技術 擴大預測和說明分析的技術進步,以實現更好的患者照護和系統效能
說明分析挖掘歷史資料來識別病患結果、護理服務品質和業務效率的模式。在醫療保健領域,說明分析用於管理患者關係、了解人員配置和資金需求以及監控設備和藥品銷售。預測分析使用機器學習和人工智慧技術來識別醫療資料中的模式,這些模式可以預測未來的患者結果和護理服務品質。預測建模可幫助醫療機構更準確地預測患者需求,並針對特定人群(例如患有慢性病或有再入院風險的患者)制定有針對性的干涉措施。規範性分析有助於預測醫療保健結果,同時提案採取哪些措施來最佳化患者結果和業務效率。處方模型使用基於多個來源的資料的先進演算法,包括人口統計、病歷、接受的治療和提供者行為。處方模型會推薦最佳治療計劃或提案對組織流程進行更改,以幫助改善醫療實踐。
組件:醫療保健分析服務和軟體,可增強醫療保健提供者的工作流程並支援資料主導的決策。
醫療保健分析服務包括幫助組織建立解決方案來實現其當前和未來業務目標的諮詢。這些服務包括應用程式開發、研究報告、預測模型、模擬和其他最佳化醫療保健業務的分析解決方案。除了醫療保健分析專家提供的服務之外,醫療保健專業人員還可以使用許多強大的軟體工具。這些工具允許使用者收集、儲存、分析、視覺化和解釋大量資料,並獲得有關醫療保健組織績效的寶貴見解。流行的軟體程式包括資料透視表、神經網路、資料探勘演算法和人工智慧系統,可用於臨床分析和醫院營運最佳化。資料採集軟體包括從電子健康記錄、患者調查、實驗室測試、醫院就診、申請記錄、保險申請和其他來源收集資料,然後利用統計技術和演算法從資料中揭示相關性和見解,以改善醫療保健結果。
部署:雲端基礎的醫療保健服務在學術機構和生物技術應用中的需求日益成長,且具有較低的初始成本和擴充性。
醫療保健分析服務提供諮詢,幫助組織建立解決方案來實現其當前和未來的業務目標。這些服務包括應用程式開發、研究報告、預測模型、模擬和其他最佳化醫療保健業務的分析解決方案。除了醫療保健分析專家提供的服務之外,醫療保健專業人員還可以使用許多強大的軟體工具。這些工具允許使用者收集、儲存、分析、視覺化和解釋大量資料,並獲得有關醫療保健組織績效的寶貴見解。流行的軟體程式包括資料透視表、神經網路、資料探勘演算法和人工智慧系統,可用於臨床分析和醫院營運最佳化。資料收集軟體從電子健康記錄、患者調查、實驗室測試、醫院就診、申請記錄、保險申請和其他資訊來源收集資料,並使用統計技術和演算法從收集的資料中得出相關性和見解,並改善醫療保健結果。
醫療保健分析在臨床和人口健康分析應用中的廣泛部署
臨床分析使用資料和分析來確定患者照護的改進並提供可行的見解。這個概念已被廣泛使用,特別是由於預測分析在臨床實踐中的高度部署。財務分析著重於提高醫院環境中具有成本效益的資源利用率和財務績效。這包括衡量治療的成本效益、了解報銷模式以及確定降低成本的機會。營運和管理分析透過分析 IT、財務和人力資源的職能成本來最佳化營運效率。人口健康分析從人口觀點研究醫療保健,重點關注不同類別患者和地區的健康結果。檢視各種疾病的發生率和治療方法隨時間變化的趨勢,並評估政策和舉措對特定族群的影響。
最終用戶:醫療保健支付者和生物技術公司擴大醫療保健分析的使用
學術機構使用分析來深入了解醫療問題、開發循證治療方法並設計研究,而生物技術行業則使用醫療保健分析來簡化藥物開發、確定新產品的潛在市場並最佳化定價。此外,生技公司可以使用來自各種資訊來源的個人化資料,包括電子病歷、穿戴式裝置、公共衛生資料庫和環境資料,以就產品開發和行銷宣傳活動做出明智的決策。分析資料可幫助醫療保健付款人最大限度地提高業務效率並降低成本,同時提供優質照護。醫療保健分析可協助保險公司評估大量複雜的健康和醫療資料,例如申請、醫療記錄、診斷和治療、藥房記錄、實驗室測試結果和其他相關患者資料,以提高業務。包括醫院和診所在內的醫療保健提供者正在利用分析透過改善決策、供應鏈管理和財務績效來實現個人化患者照護。透過這種方式,醫療保健分析可以為醫療保健行業的所有相關人員做出更明智的決策。
區域洞察
美洲的醫療保健分析市場是創新主導的,受到資料科學技術進步的持續研究活動的推動,並更加關注該地區的醫院,以提供更好的患者治療效果並節省成本。該地區擁有許多成熟的巨量資料技術供應商,他們不斷致力於擴展其醫療保健知識以升級其現有產品組合。醫療保健分析的採用在亞太地區正在緩慢而穩定地成長,許多數位轉型舉措和醫療保健新興企業為突破性的診斷解決方案獲得了新的資金。在亞洲,各國政府越來越認知到採用電子病歷和人口分析來擴大資料的可用性,以便更好地監測區域健康狀況。歐洲醫療保健分析的使用預計將大幅增加,其標誌是該地區醫療保健基礎設施的進步以及擴大智慧醫院的舉措。 Horizon Europe 和 EU4Health舉措等計劃正在幫助改善醫療保健領域的數位化和分析。
FPNV定位矩陣
FPNV 定位矩陣對於評估醫療保健分析市場至關重要。我們檢視與業務策略和產品滿意度相關的關鍵指標,以對供應商進行全面評估。這種深入的分析使用戶能夠根據自己的要求做出明智的決策。根據評估,供應商被分為四個成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市場佔有率分析
市場佔有率分析是一種綜合工具,可以對醫療保健分析市場中供應商的現狀進行深入而深入的研究。全面比較和分析供應商在整體收益、基本客群和其他關鍵指標方面的貢獻,以便更好地了解公司的績效及其在爭奪市場佔有率時面臨的挑戰。此外,該分析還提供了對該行業競爭特徵的寶貴見解,包括在研究基準年觀察到的累積、分散主導地位和合併特徵等因素。這種詳細程度的提高使供應商能夠做出更明智的決策並制定有效的策略,從而在市場上獲得競爭優勢。
1. 市場滲透率:提供有關主要企業所服務的市場的全面資訊。
2. 市場開拓:我們深入研究利潤豐厚的新興市場,並分析其在成熟細分市場的滲透率。
3. 市場多元化:提供有關新產品發布、開拓地區、最新發展和投資的詳細資訊。
4.競爭評估與資訊:對主要企業的市場佔有率、策略、產品、認證、監管狀況、專利狀況、製造能力等進行全面評估。
5. 產品開發與創新:提供對未來技術、研發活動和突破性產品開發的見解。
1. 醫療保健分析市場的市場規模和預測是多少?
2.在醫療保健分析市場的預測期內,需要考慮投資哪些產品、細分市場、應用程式和領域?
3. 醫療保健分析市場的技術趨勢和法規結構是什麼?
4.醫療保健分析市場主要供應商的市場佔有率為何?
5. 進入醫療保健分析市場的適當型態和策略手段是什麼?
[190 Pages Report] The Healthcare Analytics Market size was estimated at USD 36.29 billion in 2023 and expected to reach USD 44.93 billion in 2024, at a CAGR 24.07% to reach USD 164.33 billion by 2030.
Healthcare analytics involves analyzing data related to healthcare services to gain insights that can be used to improve patient care and health outcomes. Hospitals and healthcare professionals can make more cost-effective decisions that impact patient care with proper healthcare data analysis. The data can be used to improve patient health and clinical outcomes. The healthcare industry is transforming technology advances, adopting electronic health records (EHR) and analytics to streamline healthcare processes. Governments worldwide focus on controlling healthcare fraud related to payments, and healthcare analytics technologies can assist the industry in monitoring fraud activities. However, integration and interoperability with existing models and their limited data privacy provisions impede product penetration. Advanced healthcare analytics technologies based on AI & Big Data with a better focus on safety can assist in addressing these issues. Moreover, increased investments in smart hospital facilities worldwide are expected to accelerate the deployment of healthcare analytics software and services. Market players are introducing different suites of products within healthcare analytics, such as predictive analytics or clinical decision support systems, to elevate their presence across the healthcare sector.
KEY MARKET STATISTICS | |
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Base Year [2023] | USD 36.29 billion |
Estimated Year [2024] | USD 44.93 billion |
Forecast Year [2030] | USD 164.33 billion |
CAGR (%) | 24.07% |
Technology: Growing technological advancements in predictive and prescriptive analytics for better patient care and system performance
Descriptive analytics involves mining historical data to identify patterns in patient outcomes, quality of care delivery, and operational efficiency. In healthcare, descriptive analytics is used for patient relationship management, understanding staffing and funding needs, or monitoring equipment or pharmaceutical sales. Predictive analytics uses ML and AI techniques to identify patterns in healthcare data that may predict future patient outcomes or quality of care delivery. Predictive modeling can help healthcare organizations anticipate patient needs more accurately and develop targeted interventions for specific populations, such as those at risk for chronic disease or readmissions. Prescriptive analytics helps in predicting healthcare results while also suggesting actions that should be taken to optimize patient outcomes or operational efficiency. Prescriptive models use advanced algorithms based on data from multiple sources, including demographics, medical history, treatments received, and provider behavior. Prescriptive models recommend optimal treatment plans or suggest changes to organizational processes that can aid in improving medical practices.
Component: Pertaining advantage of healthcare analytics services and software for enhancing the workflow of healthcare providers in making data-driven decisions
Healthcare analytics services involve consulting with organizations to help them build solutions to address their current and future business objectives. These services often include the development of applications, research reports, predictive models, simulations, and other analytical solutions that optimize healthcare operations. In addition to the services provided by healthcare analytics experts, many powerful software tools are available for healthcare professionals to use. These tools allow users to collect, store, analyze, visualize, and interpret large amounts of data to gain valuable insights into their healthcare organization's performance. Popular software programs include pivot tables, neural networks, data mining algorithms, and artificial intelligence systems that can be used for clinical analysis and hospital operational optimization. Data capture software includes collecting data from electronic medical records, patient surveys, lab tests, hospital visits, billing records, insurance claims, and other sources, which then utilizes statistical methods and algorithms to uncover correlations and insights from collected data to improve healthcare outcomes.
Deployment: Increasing demand for cloud-based healthcare services in academic organizations & biotechnology applications providing lower upfront costs and scalability
Healthcare analytics services involve consulting with organizations to help them build solutions to address their current and future business objectives. These services often include the development of applications, research reports, predictive models, simulations, and other analytical solutions that optimize healthcare operations. In addition to the services provided by healthcare analytics experts, many powerful software tools are available for healthcare professionals to use. These tools allow users to collect, store, analyze, visualize, and interpret large amounts of data to gain valuable insights into their healthcare organization's performance. Popular software programs include pivot tables, neural networks, data mining algorithms, and artificial intelligence systems that can be used for clinical analysis and hospital operational optimization. Data capture software includes collecting data from electronic medical records, patient surveys, lab tests, hospital visits, billing records, insurance claims, and other sources, which then utilizes statistical methods and algorithms to uncover correlations and insights from collected data to improve healthcare outcomes.
Application: Extensive deployment of healthcare analytics in the clinical and population health analytics
Clinical analytics involves using data and analytics to identify areas of improvement in patient care, providing actionable insights. This concept has grown to be widely used, particularly with the high deployment of predictive analytics in clinical practice. Financial analytics focuses on cost-effective resource utilization and improving financial performance in hospital settings. This can involve measuring the cost-effectiveness of treatments, understanding reimbursement models, and identifying opportunities for cost savings. Operational & administrative analytics optimize operational efficiency by analyzing functional costs across IT, finance, and HR departments. Population health analytics approaches healthcare from a population perspective, focusing on health outcomes in different categories of patients or regions. It involves examining trends in various disease rates or treatments over time and assessing the impact of policies or initiatives on specific people.
End-User: Growing utilization of healthcare analytics by healthcare payers and biotechnological companies
Academic organizations are using analytics to gain insights into healthcare issues, develop evidence-based treatments, and design research studies, while the biotechnology industry is applying healthcare analytics to increase the efficiency of drug development, identify potential markets for new products, and optimize pricing. Moreover, biotechnology companies can make informed decisions about product development and marketing campaigns with personalized data from various sources such as EHRs, wearables, public health databases, environmental data, and more. Analytics data help healthcare payers to maximize operational efficiency and reduce costs while still providing quality care, which increasingly focuses on preventive care rather than reactive interventions. Insurance companies can leverage healthcare analytics to enhance their business operations and assess large volumes of complex health and medical data such as claims, medical records, diagnoses and treatments, pharmacy records, laboratory test results, and other relevant patient data. Healthcare providers, including hospitals & clinics, use analytics to personalize patient care through improved decision-making, supply chain management, and financial performance. As such, healthcare analytics enables more informed decisions across all stakeholders in the healthcare industry.
Regional Insights
The healthcare analytics market in the Americas is highly innovation-driven, characterized by consistent research activities on advancing data science technologies and a growing focus on the region's hospitals to offer better patient outcomes and cost savings. The region is home to many established big data technology providers constantly working on expanding their healthcare knowledge to upgrade their existing portfolio. The Asia-Pacific region observes a slow and steady growth in healthcare analytics adoption, with many digital transformation initiatives and healthcare startups obtaining new funds for breakthrough diagnostic solutions. Increasing recognition from governments has been observed regarding deploying EHR and population analytics in the Asian region to expand data availability for better monitoring of regional health. Europe is expected to observe a vital increase in the use of healthcare analytics, characterized by the rising number of advances in healthcare infrastructure in the region and a growing number of initiatives for expanding smart hospitals. Programs such as Horizon Europe and the EU4Health initiative have supported digitalization and improved analytics in healthcare.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Healthcare Analytics Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Healthcare Analytics Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Healthcare Analytics Market, highlighting leading vendors and their innovative profiles. These include Alteryx, Inc., Apixio, Inc., Arcadia Solutions, LLC, Athenahealth, Inc., Cisco Systems, Inc., CitiusTech Inc., Clarify Health Solutions, Inc., ClosedLoop.ai Inc., Cloudticity, L.L.C, Cotiviti, Inc., Epic Systems Corporation, GE HealthCare Technologies Inc., Google LLC by Alphabet Inc., Health Catalyst, Inc., HealthVerity, Inc., HOKUTO Inc., Inovalon Holdings, Inc., International Business Machines Corporation, IQVIA Inc., McKesson Corporation, MedeAnalytics, Inc., Microsoft Corporation, Optum, Inc., Oracle Corporation, RIB Datapine GmbH, SAP SE, SAS Institute, Inc., Veradigm LLC, Verinovum, Virgin Pulse, and Wipro.
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the Healthcare Analytics Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Healthcare Analytics Market?
3. What are the technology trends and regulatory frameworks in the Healthcare Analytics Market?
4. What is the market share of the leading vendors in the Healthcare Analytics Market?
5. Which modes and strategic moves are suitable for entering the Healthcare Analytics Market?