Healthcare Analytics Market Advances as Carta Healthcare Secures $18.25 Million to Scale AI-Powered Clinical Data Analytics

Carta Healthcare secured $18.25 million in Series B1 financing in May 2025, led by UPMC Enterprises with participation from healthcare-system investors including MemorialCare Innovation Fund, Rex Health Ventures, Tampa General Hospital Ventures, and Memorial Hermann Health System. The funding is supporting expansion of Carta's AI-powered clinical data abstraction and analytics platform, which automates the collection and analysis of structured and unstructured clinical data. The investment highlights growing demand for analytics that can convert fragmented healthcare information into actionable insights for quality improvement, clinical research, and operational decision-making.

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The development creates opportunities for healthcare analytics providers, AI developers, cloud platforms, and clinical-data specialists to expand products around automated data abstraction, predictive analytics, real-world evidence, and clinical decision support. Companies such as SAS, IBM, Oracle, IQVIA, and Health Catalyst are positioned to compete through AI-enabled analytics, interoperable data platforms, and cloud-based healthcare intelligence. SAS, for example, expanded its healthcare analytics portfolio in 2026 with new AI capabilities spanning clinical research, patient care, and health-system operations.

According to DataM Intelligence, the global healthcare analytics market is estimated to reach USD 31.33 billion in 2025 and is projected to grow to USD 53.01 billion by 2035, registering steady growth at a CAGR of 5.4% during the forecast period from 2026 to 2035. Software remains the dominant component as healthcare organizations increasingly require platforms to integrate, process, visualize, and analyze large volumes of clinical, financial, and operational data.

North America currently leads the healthcare analytics market, supported by advanced healthcare IT infrastructure, widespread EHR adoption, high healthcare spending, and established health technology ecosystems. Europe is the fastest-growing region, driven by government-backed healthcare digitization, eHealth adoption, telemedicine, and demand for data-driven care. Hospitals and healthcare providers are the fastest-growing end-user segment as organizations deploy analytics for patient outcomes, resource optimization, population health management, and cost control.

Recent Key Developments - United States & North America
✅ September 2026: The U.S. healthcare analytics ecosystem moved toward more standardized, reusable clinical data with the release of USCDI v7, which adds 30 new data elements and strengthens the data foundation available for analytics, interoperability, and AI-enabled healthcare applications.

✅ August 2026: Komodo Health and NCQA launched a multi-year collaboration to modernize HEDIS quality measures using real-world data and healthcare-native AI. The initiative is aimed at making quality measurement more continuously updated and actionable for health plans and healthcare organizations.

✅ July-September 2026: U.S. healthcare data companies are increasingly turning continuously refreshed EHR data into research and operational intelligence. Truveta highlighted daily refreshed data covering more than 130 million patients, while its recent work applied clinical-note extraction and real-world evidence methods to cancer staging, GLP-1 use, and other emerging healthcare questions.

Recent Key Developments - Japan & Asia-Pacific
✅ July 2026: Japan's Ministry of Health, Labour and Welfare released a new Medical DX dashboard, giving stakeholders a more structured view of progress in national healthcare digitalization. The ministry also continued work on electronic health-information sharing between medical and long-term-care services.

✅ August 2026: Singapore's Ministry of Health confirmed that AI-assisted clinical note-taking is being used with a human-in-the-loop requirement, with healthcare professionals required to review AI-generated notes before they enter clinical records. Singapore also confirmed that AI tools processing patient information remain subject to healthcare and personal-data security requirements, including additional safeguards for third-party cloud providers.

✅ September 2026: China announced plans to use AI and big data more extensively for disease prevention and control under its 2026-2030 national disease-control plan. Separately, Shanghai reported that its healthcare AI infrastructure has established a medical AI data lake and reduced data-preparation time by more than 60%, with a healthcare corpus targeted to exceed 2 PB by the end of 2026.

Recent Key Developments - Product & Technology Innovation
✅ 2026: Real-Time Healthcare Intelligence: Healthcare analytics is shifting from static retrospective datasets toward continuously refreshed clinical data. Recent Truveta work demonstrates how updated EHR records and clinical notes can support faster evidence generation, patient-level research, and emerging real-world analytics use cases.

✅ 2026: AI-Powered Clinical Risk Analytics: Singapore researchers developed a machine-learning tool combining genomic and clinical data to predict liver-cancer recurrence. The system outperformed conventional TNM staging across independent patient groups, showing how analytics is moving beyond descriptive reporting toward individualized risk prediction.

✅ 2026: Privacy-Preserving AI Evaluation: The WHO, ITU and WIPO's Global Initiative on AI for Health introduced a benchmarking approach that allows AI models to be evaluated against clinical datasets without disclosing the underlying data to model developers. The approach addresses a growing challenge for healthcare analytics: testing models on sensitive clinical information while keeping the data under institutional control.

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M&A / Strategic Activity
Recent strategic acquisitions, partnerships, and ecosystem developments shaping the Healthcare Analytics Market:

Datavant - Expansion into AI-powered medical data analysis and real-world evidence
Datavant completed the acquisition of Aetion in July 2025, adding an established real-world evidence platform to its healthcare data network. The combination is designed to connect privacy-protected healthcare data with analytics for evaluating the clinical impact of therapies across development and commercial use. Datavant also completed its acquisition of DigitalOwl in October 2025, bringing AI-based medical-record analysis, summarization and data structuring into its health-data ecosystem.

Tempus AI - Building an integrated clinical, genomic and analytics platform
Tempus expanded its healthcare analytics capabilities through multiple acquisitions, including Deep 6 AI in March 2025 for AI-based clinical-trial matching and real-world evidence generation and Paige in 2025 for digital pathology AI. Deep 6 brought connectivity across more than 750 provider locations and more than 30 million patients, while Paige added a dataset of almost 7 million digitized pathology slides with clinical annotations.

IQVIA - NVIDIA collaboration for agentic healthcare analytics
IQVIA and NVIDIA established a strategic collaboration in January 2025 to develop healthcare-grade AI agents using IQVIA's healthcare data, analytics and domain expertise alongside NVIDIA AI technologies. The work covers applications including clinical development, commercial analytics, literature review and multimodal data extraction. IQVIA subsequently launched IQVIA.ai in March 2026, bringing conversational AI and configurable agents into a unified platform for clinical, commercial and real-world workflows.

Boehringer Ingelheim - IQVIA commercial data transformation collaboration
In January 2026, Boehringer Ingelheim selected IQVIA's Data-as-a-Service+ technology to support global commercial data harmonization. The collaboration is intended to bring commercial datasets into a unified global data model connected to the company's cloud infrastructure, creating a common foundation for advanced analytics across therapeutic areas and regional teams.

M42 - Oracle Health Data Intelligence deployment in the UAE
In September 2026, M42 announced plans to adopt Oracle Health Data Intelligence to unify clinical, genomic and real-world data across its network. The initial deployment is focused on diabetes programs, where M42 plans to use advanced analytics and AI-driven exploration to identify disease patterns, risk factors and treatment opportunities.

New Product/Platform Launches & Deployments
Recent innovations and deployments in healthcare analytics:

Oracle - Life Sciences AI Data Platform
Oracle launched its Life Sciences AI Data Platform in January 2026, combining generative AI with Oracle Health Real-World Data and customer and third-party datasets. The platform is built around more than 129 million de-identified longitudinal records and is designed to support research, clinical trials, post-market safety and commercialization.

IQVIA - IQVIA.ai agentic analytics platform
IQVIA launched IQVIA.ai in March 2026, combining healthcare-grade AI, NVIDIA technologies and IQVIA data assets in a unified agentic platform. The initial applications span clinical, commercial and real-world workflows, allowing users to interact with healthcare intelligence through conversational AI and specialized agents.

Microsoft - Multimodal healthcare analytics through Microsoft Fabric
Microsoft introduced healthcare-data capabilities that allow organizations to orchestrate text, imaging, audio and other data modalities through Microsoft Fabric. The platform connects healthcare datasets with AI models for applications such as medical-image analysis, social-determinants-of-health extraction, patient outreach, care management and clinical research. CMS claims data ingestion through CCLF files was also made available for population-level analytics.

Veradigm - AI-based real-world evidence from EHR data
In May 2025, Veradigm demonstrated an AI-driven approach to extracting real-world evidence from de-identified EHR data, particularly around GLP-1 therapies. The approach can identify information embedded in physician notes, including treatment discontinuation reasons, side effects and social determinants of health that are difficult to capture through conventional structured datasets.

Oracle - Healthcare AI Data Intelligence deployments across provider networks
Healthcare providers are increasingly deploying analytics as part of broader EHR modernization rather than buying standalone analytics tools. For example, Baystate Health announced an expanded Oracle Health relationship in June 2026 that includes Oracle Health AI Data Platform and advanced predictive analytics, while Quorum Health selected Oracle Health Data Intelligence in September 2026 as part of a connected clinical, operational and financial technology platform across 11 hospitals.

R&D & Technological Advancements
Multimodal healthcare analytics
Healthcare analytics is moving beyond structured EHR and claims data toward combined analysis of clinical notes, medical images, conversations, genomics and other unstructured information. Microsoft's Fabric healthcare capabilities, for example, can combine conversational data with clinical datasets and use medical-imaging AI models to generate additional insights for care management and research.

Agentic AI for healthcare workflows
The latest development is shifting from AI that simply answers questions toward systems that can execute multi-step analytical workflows. IQVIA's work with NVIDIA and the subsequent IQVIA.ai platform are examples of this transition, with agents designed for literature review, clinical data analysis, target identification, market assessment and other specialized workflows.

Real-world data linked across clinical and claims sources
Truveta expanded its dataset in February 2025 by adding commercial, Medicare and Medicaid closed claims for more than 200 million patients, linked with EHR information covering more than 120 million patients. The development creates a more continuous view of patient journeys across clinical encounters and reimbursement records for RWE and outcomes research.

Large-scale multimodal foundation models for healthcare
Tempus reported in May 2026 that its oncology multimodal foundation-model work was using more than 500 petabytes of patient data, including over 45 million de-identified patient journeys and more than 400,000 cancer records containing genomic, transcriptomic, imaging and clinical information. The company is using these datasets to develop models for outcome prediction and precision-medicine applications.

Privacy-preserving analytics and federated healthcare data
Privacy-preserving approaches are becoming an important technical layer for analytics involving large patient datasets. IQVIA reported in August 2026 that its Privacy Analytics Platform was deployed within England's NHS Federated Data Platform, supporting analysis across health data from 55 million patients without requiring the underlying data to be centralized in a conventional analytics environment.

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Segments Covered in the Global Healthcare Analytics Market:
By Component:
The market is segmented into software and services. Software dominates due to its ability to analyze healthcare data from EHRs, medical devices, and patient monitoring systems, supporting better clinical decisions and operational efficiency. Services are also growing with demand for implementation, integration, consulting, and maintenance.

By Type:
The market includes descriptive, predictive, and prescriptive analytics. Descriptive analytics remains a key segment for analyzing historical healthcare data, while predictive analytics is growing rapidly due to demand for risk prediction, patient outcome forecasting, and early disease detection. Prescriptive analytics helps optimize treatment and resource allocation.

By Application:
The market is divided into financial, clinical, operational, population health analytics, and others. Clinical analytics represents a major segment, supporting diagnosis, treatment decisions, and patient outcomes. Financial, operational, and population health analytics are also gaining adoption for cost control, workflow optimization, and disease management.

By End User:
The market includes hospitals and healthcare providers, healthcare payers, pharmaceutical and biotechnology companies, and government organizations. Hospitals and healthcare providers are the fastest-growing segment, driven by demand for improved patient outcomes, efficiency, resource utilization, and cost management.

By Region:
North America - 49.03% Share: North America leads due to advanced healthcare IT infrastructure, high healthcare spending, EHR adoption, and demand for AI-enabled analytics. The region accounted for 49.03% of global revenue in 2025.

Europe: Europe is growing rapidly due to healthcare digitization, eHealth adoption, telemedicine, and supportive regulatory frameworks.

Asia-Pacific: Asia-Pacific is expanding with rising healthcare investments, digitalization, cloud adoption, and growing use of analytics across China, India, Japan, and Southeast Asia.

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