암정보 시스템 시장 : 제공 서비스, 기능, 배포 형태, 용도, 최종사용자별 - 세계 예측(2025-2032년)

The Oncology Information Systems Market is projected to grow by USD 13.42 billion at a CAGR of 7.78% by 2032.

Navigating a transforming oncology information ecosystem driven by precision medicine, interoperability imperatives, and patient-centric digital care pathways

The oncology care continuum is being reshaped by converging technological, clinical, and regulatory forces that demand new forms of information management. Providers are balancing rising complexity in treatment regimens with an imperative to capture and harmonize multi-source clinical data, and as a result the role of oncology information systems has shifted from administrative enablers to strategic infrastructure. In this context, leaders must understand not only product capabilities but how systems integrate across care pathways, support multidisciplinary teams, and sustain long-term interoperability.

Clinicians and administrators are now asking for platforms that reduce cognitive load, accelerate decision making, and enable seamless data exchange across oncology-specific workflows and enterprise IT estates. As precision oncology expands, so too does the requirement for solutions that combine chemotherapy management, radiation planning, imaging integration, laboratory data, and longitudinal electronic health records into coherent user journeys. Consequently, investment decisions increasingly prioritize systems that demonstrate clinical efficacy, ease of integration, and measurable improvements in patient safety and operational efficiency.

This introduction frames the ensuing analysis by highlighting the strategic consequences of these trends for vendors, health systems, and policymakers. The focus that follows is practical and operational: identifying critical inflection points, examining segmentation-driven implications for product strategy, and outlining immediate actions that leaders can take to align technology adoption with patient-centered care objectives

Identifying transformative shifts reshaping oncology technology adoption including AI-enabled diagnostics, cloud-native architectures, and clinician workflow reengineering

The landscape of oncology information systems is experiencing transformative shifts that extend beyond incremental product enhancements to encompass new delivery models, analytic paradigms, and clinical workflows. Artificial intelligence and advanced visualization are moving into clinical practice, augmenting diagnostic confidence and helping prioritize cases, while clinical decision support is becoming more deeply embedded into treatment planning and scheduling to reduce variability and improve guideline adherence. Parallel to this, cloud-native deployments are accelerating, enabling distributed teams to access consolidated patient records and facilitating faster updates to clinical content and regulatory compliance modules.

Interoperability remains a central axis of change. New standards and APIs are lowering the barriers to connecting laboratory information systems, imaging archives, radiation planning software, and oncology electronic records into cohesive clinical flows. This shift encourages vendors to adopt modular, API-first architectures and to pursue partnerships with clinical integrators and imaging specialists. At the same time, workforce implications are profound: clinicians expect intuitive user interfaces that support multidisciplinary collaboration, and health systems are investing in training and change management to secure adoption and realize projected patient safety gains.

Taken together, these shifts are redefining vendor relevance and buyer expectations. Organizations that combine strong clinical validation, flexible deployment options, and clear implementation roadmaps will be best positioned to support evolving care models and to deliver measurable improvements in both clinical and operational outcomes

Assessing the cumulative operational and procurement impacts of United States tariff measures enacted in 2025 on oncology information system supply chains and services

Tariff measures introduced in the United States in 2025 have introduced a new variable into procurement and supply chain planning for oncology information system providers and their customers. While software is inherently portable, the broader value chain for oncology IT encompasses hardware, imaging equipment, specialized servers, and integration services that are sensitive to trade policy. As such, tariff-driven cost pressures have required procurement teams to re-evaluate vendor sourcing, total cost of ownership, and contingency strategies for equipment and service delivery.

Operationally, health systems and technology vendors have responded by diversifying supplier footprints and accelerating local sourcing for physical infrastructure where feasible. This has led to renewed emphasis on validating configurations that minimize dependence on tariff-exposed components, optimizing virtualized and cloud-hosted functions, and renegotiating service-level agreements to account for potential supply delays. In parallel, some vendors have adjusted commercial models to absorb part of the incremental burden through bundled service offerings, extended warranties, or localized installation teams.

Beyond immediate procurement tactics, tariffs have also influenced strategic conversations around manufacturing localization, contractual flexibility, and investment prioritization. Organizations are increasingly factoring supply chain resilience into vendor selection criteria, preferring partners that demonstrate transparent sourcing, robust logistics capabilities, and established contingency plans. These adaptations reflect a broader industry recognition that policy-driven cost dynamics can materially affect deployment timelines, project margins, and operational risk profiles

Translating segmentation intelligence into practical product and service strategies across offerings, functionalities, deployment modes, applications, and end user profiles

A nuanced understanding of segmentation is essential for aligning product development and go-to-market strategies with clinical and operational needs. Based on Offering, the landscape divides into Services and Solution, where Services include Consulting & Training, Installation & Integration, and Maintenance & Support, and Solution encompasses Chemotherapy Information System, Clinical Integration Solutions, Laboratory Information Systems (LIS), Medical Image Analysis & Advanced Visualization, Oncology Electronic Health Record (EHR), Picture Archiving & Communication System (PACS) & Vendor-Neutral Archive (VNA), Radiation Treatment Planning System, and Radiology Information Systems (RIS). This duality underscores that buyers are procuring bundles of functionality plus implementation expertise rather than standalone products.

Based on Functionality, offerings range from Billing & Revenue Cycle Management to Clinical Decision Support, Patient Information & Care Management, Regulatory Compliance & Reporting, and Treatment Planning & Scheduling, indicating that commercial success depends on addressing both administrative and high-acuity clinical workflows. Based on Deployment Mode, choices between Cloud-Based and On-Premise continuums influence procurement cadence, security posture, and integration complexity, and these options must be reflected in commercial and technical roadmaps.

Based on Application, differentiation across Medical Oncology, Radiation Oncology, and Surgical Oncology requires product teams to prioritize domain-specific workflows and decision support. Finally, Based on End User, solutions must account for the distinct needs of Ablation & Cancer Care Centers, Hospitals & Diagnostic Imaging Centers, and Research Facilities. In practice, successful strategies translate this segmentation into modular product architectures, configurable workflows, and services that reduce integration burden while delivering measurable clinician and operational value

Deciphering regional adoption patterns and strategic imperatives across the Americas, Europe, Middle East & Africa, and Asia-Pacific healthcare markets for oncology systems

Regional dynamics will increasingly dictate where and how oncology information systems are adopted, integrated, and scaled. In the Americas, health systems tend to prioritize interoperability with enterprise electronic health records, value-based care reporting, and advanced chemotherapy and radiation planning features, which drives demand for tightly integrated platforms and sophisticated clinical decision support. Procurement cycles in this region often emphasize contractual clarity, clinical validation, and demonstrable improvements in safety and throughput.

In Europe, Middle East & Africa, regulatory heterogeneity and diverse infrastructure maturity create opportunities for flexible deployment modes; cloud-based solutions can accelerate adoption in well-connected urban centers, while on-premise configurations remain important where data residency or bandwidth constraints persist. Regional priorities include harmonizing standards across health networks, supporting multilingual interfaces, and addressing local reimbursement and compliance frameworks.

In Asia-Pacific, rapid modernization of oncology services combined with significant private sector investment has spawned demand for scalable, cloud-enabled platforms and advanced imaging analytics. Markets in this region frequently value cost-effective, modular solutions that can be deployed quickly across multiple sites, alongside strong local implementation capabilities. Across all regions, successful vendors tailor propositions to local clinical practices, regulatory requirements, and procurement norms while supporting interoperability and clinician adoption through localized training and robust support models

Profiling competitive company behaviors and strategic moves that determine differentiation in oncology information systems including partnerships, integrations, and compliance focus

Company strategies in the oncology information systems space are converging on a few consistent themes: clinical validation, strategic partnerships, and platform extensibility. Leading vendors are investing in clinical studies and real-world evidence programs to demonstrate safety and workflow impact, while also seeking alliances with imaging specialists, laboratory providers, and systems integrators to deliver end-to-end solutions. At the same time, smaller, more agile companies are leveraging niche expertise in areas such as medical image analysis or radiation planning to gain footholds and to become attractive partners for larger platform vendors.

Commercial differentiation increasingly depends on the ability to provide certified interfaces and to support both cloud-based and on-premise deployments with clear security and compliance controls. Additionally, companies are refining pricing and service models to address the dual demands of capital-constrained providers and enterprise buyers seeking predictable operating costs. Talent acquisition and retention remain critical challenges; firms that can combine clinical informatics expertise with strong engineering teams will be better positioned to accelerate feature development and reduce time-to-deploy.

Mergers and partnerships continue to reshape competitive dynamics, but strategic success hinges on the ability to integrate disparate systems seamlessly, to back claims with clinical evidence, and to present a compelling value proposition to diverse end users including specialized cancer centers, hospital networks, and research institutions

Executive-level actionable recommendations to accelerate adoption, manage risk, and optimize commercial and clinical value from oncology information system investments

Industry leaders should adopt a prioritized, pragmatic set of actions that bridge clinical requirements and commercial viability. First, embed clinicians into product development cycles early and continuously, using structured clinical advisory boards and iterative usability testing to ensure that features align with real-world workflows and reduce cognitive burden. Second, adopt an API-first architecture and publish well-documented integration patterns to lower implementation friction and to enable faster interoperability with EHRs, LIS, PACS, and radiation planning tools.

Next, establish clear deployment playbooks that support both cloud-based and on-premise scenarios, including tested deployment templates, security baselines, and transition pathways for hybrid configurations. Invest in change management services-training, role-based learning pathways, and on-site support-to accelerate adoption and to secure measurable safety and efficiency outcomes. From a commercial perspective, consider offering outcome-linked service bundles or performance guarantees that align incentives with provider goals.

Finally, strengthen supply chain resilience by diversifying component sourcing, formalizing contingency plans, and offering transparent disclosure of sourcing and logistics. Governance and regulatory readiness should be continuous programs rather than discrete activities, and vendors should proactively engage with clinical and regulatory stakeholders to ease certification and compliance pathways. Taken together, these measures will materially reduce deployment risk and increase the likelihood of achieving sustained clinical and operational benefits

Outlining a rigorous mixed-methods research methodology combining primary stakeholder engagement, technical audits, and multi-source data triangulation for market evidence

The research underpinning this analysis combined mixed methods to ensure robustness and practical relevance. Primary research included structured interviews with clinicians, health system executives, IT leaders, and vendor product managers to capture firsthand perspectives on clinical workflow needs, procurement priorities, and implementation challenges. These conversations were supplemented by technical audits of representative solutions to evaluate integration architectures, security postures, and functional coverage across chemotherapy management, radiation planning, imaging, and laboratory interfaces.

Secondary research involved a systematic review of peer-reviewed clinical literature, regulatory guidance, standards documentation, and publicly available product specifications to contextualize vendor claims and to identify domain-specific best practices. Data triangulation was applied to reconcile differing viewpoints and to validate thematic findings across sources. Analytical methods included capability mapping against the defined segmentation framework, scenario analysis to stress-test supply chain and deployment assumptions, and gap analysis to highlight unmet clinical and operational needs.

Limitations are acknowledged: stakeholder perspectives reflect current adoption patterns and organizational priorities at the time of inquiry, and implementations can vary widely by institution. Nonetheless, the methodology prioritizes transparency, reproducibility, and practitioner validation to produce insights that are directly actionable for product, clinical, and commercial leaders

Concluding strategic synthesis that aligns clinical priorities, technology investments, and policy considerations to strengthen oncology information system outcomes and ROI

The synthesis of clinical priorities, technological capabilities, and policy drivers leads to a clear strategic imperative: oncology information systems must be both clinically intelligent and operationally adaptable. Stakeholders should prioritize solutions that demonstrate seamless interoperability across chemotherapy systems, radiation planning, imaging archives, laboratory data, and electronic records while also supporting advanced decision support, scheduling, and compliance workflows. Equally important is the need for flexible deployment models and service constructs that reduce implementation friction and support incremental rollouts.

Organizations that succeed will combine robust clinical validation, modular architectures, and strong local implementation capabilities to deliver measurable improvements in patient safety and care coordination. Supply chain resilience and procurement agility have emerged as additional differentiators, particularly in environments affected by policy-driven cost pressures. Finally, the pursuit of clinician-centric design and continuous performance monitoring will determine adoption and long-term value realization. This conclusion underscores an actionable focus: align investments with demonstrable clinical outcomes, prioritize interoperability, and institutionalize governance to sustain performance over time

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. AI-driven predictive analytics integration in oncology information systems for personalized treatment planning
• 5.2. Integration of comprehensive genomic sequencing data into oncology information platforms for precision medicine
• 5.3. Cloud-based oncology information systems enabling secure remote collaboration across multidisciplinary care teams
• 5.4. Implementation of HL7 FHIR interoperability standards for seamless oncology data exchange and reporting
• 5.5. Advanced patient-reported outcome tracking modules for real-time quality-of-life insights in cancer care
• 5.6. Machine learning algorithms predicting adverse drug reactions from electronic oncology records for improved safety monitoring
• 5.7. Teleoncology virtual care integration in oncology information systems to expand rural patient access and support

6. Cumulative Impact of United States Tariffs 2025

7. Cumulative Impact of Artificial Intelligence 2025

8. Oncology Information Systems Market, by Offering

• 8.1. Services
  • 8.1.1. Consulting & Training
  • 8.1.2. Installation & Integration
  • 8.1.3. Maintenance & Support
• 8.2. Solution
  • 8.2.1. Chemotherapy Information System
  • 8.2.2. Clinical Integration Solutions
  • 8.2.3. Laboratory Information Systems (LIS)
  • 8.2.4. Medical Image Analysis & Advanced Visualization
  • 8.2.5. Oncology Electronic Health Record (EHR)
  • 8.2.6. Picture Archiving & Communication System (PACS) & Vendor-Neutral Archive (VNA)
  • 8.2.7. Radiation Treatment Planning System
  • 8.2.8. Radiology Information Systems (RIS)

9. Oncology Information Systems Market, by Functionality

• 9.1. Billing & Revenue Cycle Management
• 9.2. Clinical Decision Support
• 9.3. Patient Information & Care Management
• 9.4. Regulatory Compliance & Reporting
• 9.5. Treatment Planning & Scheduling

10. Oncology Information Systems Market, by Deployment Mode

• 10.1. Cloud-Based
• 10.2. On-Premise

11. Oncology Information Systems Market, by Application

• 11.1. Medical Oncology
• 11.2. Radiation Oncology
• 11.3. Surgical Oncology

12. Oncology Information Systems Market, by End User

• 12.1. Ablation & Cancer Care Centers
• 12.2. Hospitals & Diagnostic Imaging Centers
• 12.3. Research Facilities

13. Oncology Information Systems Market, by Region

• 13.1. Americas
  • 13.1.1. North America
  • 13.1.2. Latin America
• 13.2. Europe, Middle East & Africa
  • 13.2.1. Europe
  • 13.2.2. Middle East
  • 13.2.3. Africa
• 13.3. Asia-Pacific

14. Oncology Information Systems Market, by Group

• 14.1. ASEAN
• 14.2. GCC
• 14.3. European Union
• 14.4. BRICS
• 14.5. G7
• 14.6. NATO

15. Oncology Information Systems Market, by Country

• 15.1. United States
• 15.2. Canada
• 15.3. Mexico
• 15.4. Brazil
• 15.5. United Kingdom
• 15.6. Germany
• 15.7. France
• 15.8. Russia
• 15.9. Italy
• 15.10. Spain
• 15.11. China
• 15.12. India
• 15.13. Japan
• 15.14. Australia
• 15.15. South Korea

16. Competitive Landscape

• 16.1. Market Share Analysis, 2024
• 16.2. FPNV Positioning Matrix, 2024
• 16.3. Competitive Analysis
  • 16.3.1. Accuray Incorporated
  • 16.3.2. Advanced Data Systems Corporation
  • 16.3.3. CompuGroup Medical, Inc.
  • 16.3.4. CureMD.com, Inc.
  • 16.3.5. DOSIsoft SA
  • 16.3.6. Elekta AB
  • 16.3.7. EndoSoft LLC by Utech Products Inc.
  • 16.3.8. Epic Systems Corporation
  • 16.3.9. F. Hoffmann-La Roche Ltd.
  • 16.3.10. FUJIFILM Corporation
  • 16.3.11. GE HealthCare Technologies Inc.
  • 16.3.12. International Business Machines Corporation
  • 16.3.13. Karkinos Healthcare Private Limited
  • 16.3.14. McKesson Corporation
  • 16.3.15. Medical Information Technology, Inc.
  • 16.3.16. MICA Information Systems, Inc.
  • 16.3.17. N-Power Medicine, Inc.
  • 16.3.18. NextGen Healthcare, Inc.
  • 16.3.19. Novarad Corporation
  • 16.3.20. Oracle Corporation
  • 16.3.21. RaySearch Laboratories
  • 16.3.22. Royal Philips
  • 16.3.23. Tempus AI, Inc.
  • 16.3.24. Varian Medical Systems, Inc. by Siemens Healthineers AG