Clinical Risk Grouping Solution Market by Deployment Mode (Cloud, On Premise), Solution Type (Software And Services, Software Only), Payment Model, Organization Size, End User - Global Forecast 2025-2032
Description
The Clinical Risk Grouping Solution Market was valued at USD 1.05 billion in 2024 and is projected to grow to USD 1.20 billion in 2025, with a CAGR of 14.68%, reaching USD 3.14 billion by 2032.
Set the context for decision-makers by outlining how clinical risk grouping solutions are reshaping care coordination, analytics, and reimbursement models across the ecosystem
The clinical risk grouping landscape is evolving rapidly as health systems pursue value beyond episodic care. This introduction frames the core dynamics shaping adoption of risk stratification engines, integrated analytics, and decision support that together influence care management, payment integrity, and research cohorts. Clinicians, payers, and research organizations are converging on the need for consistent, auditable grouping methodologies that reconcile claims, clinical, and social determinants data to surface actionable patient risk profiles.
Across care settings, leaders are prioritizing interoperability, explainability of grouping logic, and alignment with quality measures to ensure operational adoption. Technology vendors are responding by modularizing solutions, embedding APIs, and offering flexible deployment architectures to better meet varying IT maturity levels. Regulatory scrutiny and payer program evolution are increasing the demand for transparent algorithms and robust validation processes. This introduction lays out the strategic context for stakeholders evaluating solutions, highlighting the importance of vendor selection criteria, integration sequencing, and metrics for measuring clinical and operational value.
Illuminate the pivotal technological, regulatory, and operational shifts that are transforming risk grouping adoption, integration, and governance across healthcare organizations
Fundamental shifts are redefining how organizations approach clinical risk grouping, driven by cloud adoption, algorithmic transparency, and rising demand for integrated care pathways. The transition from point solutions to platform-centric architectures enables longitudinal patient views, while hybrid deployment patterns preserve investments in on-premise infrastructure and support phased cloud migrations. Concurrently, the expectation for model interpretability has risen, with clinicians and regulators insisting on audit trails and rationale for classification outcomes.
Data democratization and the proliferation of standardized APIs are accelerating interoperability, allowing risk grouping outputs to be consumed by care management platforms, utilization review systems, and payer adjudication workflows. This integration fosters closed-loop decision making where risk signals drive both clinical interventions and financial controls. Moreover, commercial pressures and policy shifts are pushing vendors to demonstrate measurable clinical outcomes and operational efficiencies, prompting a pivot toward outcome-linked payment arrangements and evidence-based validation approaches. These transformative shifts together are altering procurement criteria, vendor roadmaps, and the practical timelines for enterprise-wide adoption.
Explain how evolving United States tariff policies are affecting procurement, supply chains, and deployment choices for technology vendors and healthcare purchasers
Recent tariff adjustments and trade policy developments in the United States have introduced additional complexity for procurement, deployment, and cross-border vendor operations. Changes in tariff schedules affect hardware and imported components used in on-premise infrastructure, influencing total cost calculations and compelling some buyers to reassess deployment mode decisions to mitigate supply chain exposure. For vendors that depend on international supply chains for servers, networking gear, or specialized appliances, tariffs can propagate into longer lead times and higher capital expenditures, thereby influencing delivery schedules for implementation projects.
The tariff landscape also shapes partner ecosystems, as regional distributors and integrators shift sourcing strategies to optimize landed costs and maintain service-level commitments. For cloud-native providers, indirect effects arise from increased costs for edge devices, partner hardware, and co-located infrastructure, which may influence pricing and contractual terms. In response, procurement and IT leaders are increasingly factoring supply chain resilience and tariff risk into vendor selection criteria, negotiating flexible contract clauses, and prioritizing modular architectures that can adapt to changing hardware and logistics constraints. These dynamics underscore the need for scenario planning and supplier diversification to sustain implementation timelines and service continuity.
Offer nuanced segmentation-driven insights that reveal how deployment, solution composition, payment structures, organizational scale, and end-user needs shape adoption pathways
Insightful segmentation reveals how deployment preferences, solution composition, payment frameworks, organizational scale, and end-user needs drive differentiated adoption pathways. When examining deployment mode, organizations evaluate Cloud versus On Premise approaches, with cloud options including Hybrid Cloud, Private Cloud, and Public Cloud variants that each present distinct trade-offs around control, latency, and compliance. The choice of deployment is often informed by integration complexity and existing infrastructure commitments, which in turn shape implementation timelines and operational support models.
Solution type distinguishes between Software And Services and Software Only offerings, where Software And Services bundles Implementation Services and Support And Maintenance to reduce internal burden and accelerate time to operationalization. Decision-makers weighing software-only options must ensure internal capabilities for integration and ongoing maintenance are sufficient to sustain performance and governance. Payment model segmentation highlights Fee For Service and Value Based Care approaches, which create divergent incentive structures and data requirements; organizations working under value-based arrangements demand tighter linkage between risk outputs and care management outcomes.
Organization size influences procurement strategy, with Large Enterprises seeking centralized governance, enterprise-grade security, and multi-site orchestration while Small And Medium Enterprises prioritize lower total cost of ownership and turnkey implementations. End user segmentation across Hospitals, Payers, and Research Institutes further refines requirements: Hospitals differentiate between Large Hospitals and Small Hospitals in their capacity to absorb integration work and customize workflows, and Payers separate Private Payers and Public Payers based on regulatory constraints and contracting models. Research Institutes emphasize reproducibility and cohort definition clarity to support scientific inquiry. Together, these segmentation dimensions intersect to create tailored solution profiles and procurement criteria that vendors and buyers must navigate thoughtfully.
Detail regional strategic priorities and operational considerations across major global areas that influence deployment, compliance, and partnership strategies
Regional dynamics materially influence vendor strategies and deployment considerations, with distinct regulatory frameworks, payer constructs, and technology maturities across global geographies. In the Americas, stakeholders emphasize interoperability with legacy claims systems, alignment with evolving payer programs, and scalability to support diverse provider networks. This region often leads in the operationalization of risk-based contracting and the integration of social determinants data into stratification approaches, prompting solution enhancements that prioritize longitudinal data ingestion and cross-organizational data sharing agreements.
In Europe, Middle East & Africa, regulatory diversity and varying healthcare delivery models necessitate adaptable architectures and strong localization capabilities. Vendors operating across this region invest in configurable privacy controls, multilingual support, and compliance workflows that can address both stringent data protection regimes and variable reimbursement mechanisms. Meanwhile, the Asia-Pacific region demonstrates rapid adoption of cloud-native offerings as organizations leverage public and hybrid cloud environments to accelerate analytics deployment. Variances in digital health maturity across the region mean that vendors must offer flexible implementation tracks and local partnership networks to succeed. These regional insights underscore the importance of regulatory alignment, partner ecosystems, and localization strategies for sustainable deployment and adoption.
Summarize the competitive environment and vendor differentiation factors including integration capabilities, managed services, partnerships, and evidence-based validation approaches
Competitive dynamics in the clinical risk grouping space are characterized by a mix of established platform providers, specialized analytics firms, and emerging entrants that blend clinical expertise with data science capabilities. Leading companies differentiate on the basis of algorithmic transparency, integration APIs, and proven interoperability with electronic health records and claims systems. Some vendors emphasize end-to-end managed services to reduce buyer implementation burden, while others focus on modular components that allow customers to integrate only the capabilities they need, such as cohorting engines or real-time risk feeds.
Partnerships between technology firms, system integrators, and domain-specialist consultancies are increasingly central to delivering comprehensive solutions that span data ingestion, normalization, grouping logic, and downstream workflow activation. Strategic alliances with cloud hyperscalers and regional systems integrators help vendors meet requirements for scalability, security, and localized delivery. Competitive positioning also reflects investment in validation studies, clinician-facing explainability features, and professional services that support change management. For buyers, vendor selection hinges on demonstrated interoperability, referenceable deployments in analogous care settings, and the availability of configurable governance frameworks that align with institutional risk tolerance and regulatory obligations.
Provide practical, high-impact recommendations for leaders to accelerate adoption, ensure governance, and secure measurable operational and clinical outcomes through phased execution
Industry leaders should prioritize interoperability, algorithmic transparency, and practical governance frameworks to accelerate adoption while managing clinical and regulatory risk. They should adopt phased implementation roadmaps that start with high-impact use cases and progressively expand to support broader care coordination objectives. This incremental approach reduces operational disruption and permits early validation of clinical impact, enabling iterative refinement of grouping logic and integration touchpoints.
Procurement teams are advised to require demonstrable explainability and auditability for classification outcomes, to stipulate clear service-level commitments for data exchange, and to negotiate flexible licensing that accommodates pilot-to-scale transitions. Organizational leaders should invest in cross-disciplinary governance councils that bring together clinical, data science, compliance, and IT stakeholders to oversee model performance and change management. Vendors should offer configurable deployment templates for Hybrid Cloud, Private Cloud, and Public Cloud scenarios to meet diverse infrastructure constraints, and provide bundled Implementation Services and Support And Maintenance options to support clients with limited internal resources. Finally, building strategic partnerships with system integrators and local providers can de-risk implementations and accelerate time to operational value.
Describe a rigorous, multi-source research methodology that blends stakeholder interviews, vendor capability assessment, and scenario-based analysis to validate findings
The research behind these insights combines qualitative assessments, vendor capability reviews, and synthesis of publicly available regulatory and policy materials to build a cohesive understanding of the space. Primary inputs include structured interviews with clinical leaders, payer executives, and implementation specialists, augmented by vendor whitepapers, product documentation, and case study analyses. Comparative evaluation criteria focus on interoperability, deployment flexibility, explainability, validation practices, and professional services capabilities to ensure assessments are grounded in operational realities.
Analytical methods prioritize triangulation across sources to validate claims about product features and deployment outcomes, including cross-verification of vendor functionality with third-party integrations and client testimonials. The methodology also incorporates scenario analysis to surface implications of policy changes and supply chain disruptions, and a governance lens to evaluate controls for data privacy and algorithmic accountability. Transparency in methodology and source attribution supports reproducibility of findings and enables buyers to align insights with their internal requirements during vendor selection and procurement processes.
Provide a conclusive synthesis that ties together strategic imperatives, operational risks, and practical prerequisites for successful adoption and governance of risk grouping solutions
In conclusion, clinical risk grouping solutions are at an inflection point where technological maturity, regulatory scrutiny, and changing payment models converge to reshape procurement and deployment strategies. Organizations that prioritize transparent algorithms, robust interoperability, and phased implementation approaches will be better positioned to translate risk stratification into tangible clinical and operational benefits. Supply chain and policy considerations, such as tariff shifts, add an additional layer of complexity that requires deliberate planning around hardware sourcing and deployment sequencing.
Successful adoption depends on aligning solution capabilities with organizational needs defined by deployment preferences, solution type bundling, payment model alignment, enterprise scale considerations, and end-user requirements. Regional variations further necessitate localization and partnership strategies that respect regulatory and cultural differences. By integrating these elements into procurement, governance, and implementation plans, stakeholders can reduce adoption risk and accelerate value realization while maintaining compliance and operational continuity.
Please Note: PDF & Excel + Online Access - 1 Year
Set the context for decision-makers by outlining how clinical risk grouping solutions are reshaping care coordination, analytics, and reimbursement models across the ecosystem
The clinical risk grouping landscape is evolving rapidly as health systems pursue value beyond episodic care. This introduction frames the core dynamics shaping adoption of risk stratification engines, integrated analytics, and decision support that together influence care management, payment integrity, and research cohorts. Clinicians, payers, and research organizations are converging on the need for consistent, auditable grouping methodologies that reconcile claims, clinical, and social determinants data to surface actionable patient risk profiles.
Across care settings, leaders are prioritizing interoperability, explainability of grouping logic, and alignment with quality measures to ensure operational adoption. Technology vendors are responding by modularizing solutions, embedding APIs, and offering flexible deployment architectures to better meet varying IT maturity levels. Regulatory scrutiny and payer program evolution are increasing the demand for transparent algorithms and robust validation processes. This introduction lays out the strategic context for stakeholders evaluating solutions, highlighting the importance of vendor selection criteria, integration sequencing, and metrics for measuring clinical and operational value.
Illuminate the pivotal technological, regulatory, and operational shifts that are transforming risk grouping adoption, integration, and governance across healthcare organizations
Fundamental shifts are redefining how organizations approach clinical risk grouping, driven by cloud adoption, algorithmic transparency, and rising demand for integrated care pathways. The transition from point solutions to platform-centric architectures enables longitudinal patient views, while hybrid deployment patterns preserve investments in on-premise infrastructure and support phased cloud migrations. Concurrently, the expectation for model interpretability has risen, with clinicians and regulators insisting on audit trails and rationale for classification outcomes.
Data democratization and the proliferation of standardized APIs are accelerating interoperability, allowing risk grouping outputs to be consumed by care management platforms, utilization review systems, and payer adjudication workflows. This integration fosters closed-loop decision making where risk signals drive both clinical interventions and financial controls. Moreover, commercial pressures and policy shifts are pushing vendors to demonstrate measurable clinical outcomes and operational efficiencies, prompting a pivot toward outcome-linked payment arrangements and evidence-based validation approaches. These transformative shifts together are altering procurement criteria, vendor roadmaps, and the practical timelines for enterprise-wide adoption.
Explain how evolving United States tariff policies are affecting procurement, supply chains, and deployment choices for technology vendors and healthcare purchasers
Recent tariff adjustments and trade policy developments in the United States have introduced additional complexity for procurement, deployment, and cross-border vendor operations. Changes in tariff schedules affect hardware and imported components used in on-premise infrastructure, influencing total cost calculations and compelling some buyers to reassess deployment mode decisions to mitigate supply chain exposure. For vendors that depend on international supply chains for servers, networking gear, or specialized appliances, tariffs can propagate into longer lead times and higher capital expenditures, thereby influencing delivery schedules for implementation projects.
The tariff landscape also shapes partner ecosystems, as regional distributors and integrators shift sourcing strategies to optimize landed costs and maintain service-level commitments. For cloud-native providers, indirect effects arise from increased costs for edge devices, partner hardware, and co-located infrastructure, which may influence pricing and contractual terms. In response, procurement and IT leaders are increasingly factoring supply chain resilience and tariff risk into vendor selection criteria, negotiating flexible contract clauses, and prioritizing modular architectures that can adapt to changing hardware and logistics constraints. These dynamics underscore the need for scenario planning and supplier diversification to sustain implementation timelines and service continuity.
Offer nuanced segmentation-driven insights that reveal how deployment, solution composition, payment structures, organizational scale, and end-user needs shape adoption pathways
Insightful segmentation reveals how deployment preferences, solution composition, payment frameworks, organizational scale, and end-user needs drive differentiated adoption pathways. When examining deployment mode, organizations evaluate Cloud versus On Premise approaches, with cloud options including Hybrid Cloud, Private Cloud, and Public Cloud variants that each present distinct trade-offs around control, latency, and compliance. The choice of deployment is often informed by integration complexity and existing infrastructure commitments, which in turn shape implementation timelines and operational support models.
Solution type distinguishes between Software And Services and Software Only offerings, where Software And Services bundles Implementation Services and Support And Maintenance to reduce internal burden and accelerate time to operationalization. Decision-makers weighing software-only options must ensure internal capabilities for integration and ongoing maintenance are sufficient to sustain performance and governance. Payment model segmentation highlights Fee For Service and Value Based Care approaches, which create divergent incentive structures and data requirements; organizations working under value-based arrangements demand tighter linkage between risk outputs and care management outcomes.
Organization size influences procurement strategy, with Large Enterprises seeking centralized governance, enterprise-grade security, and multi-site orchestration while Small And Medium Enterprises prioritize lower total cost of ownership and turnkey implementations. End user segmentation across Hospitals, Payers, and Research Institutes further refines requirements: Hospitals differentiate between Large Hospitals and Small Hospitals in their capacity to absorb integration work and customize workflows, and Payers separate Private Payers and Public Payers based on regulatory constraints and contracting models. Research Institutes emphasize reproducibility and cohort definition clarity to support scientific inquiry. Together, these segmentation dimensions intersect to create tailored solution profiles and procurement criteria that vendors and buyers must navigate thoughtfully.
Detail regional strategic priorities and operational considerations across major global areas that influence deployment, compliance, and partnership strategies
Regional dynamics materially influence vendor strategies and deployment considerations, with distinct regulatory frameworks, payer constructs, and technology maturities across global geographies. In the Americas, stakeholders emphasize interoperability with legacy claims systems, alignment with evolving payer programs, and scalability to support diverse provider networks. This region often leads in the operationalization of risk-based contracting and the integration of social determinants data into stratification approaches, prompting solution enhancements that prioritize longitudinal data ingestion and cross-organizational data sharing agreements.
In Europe, Middle East & Africa, regulatory diversity and varying healthcare delivery models necessitate adaptable architectures and strong localization capabilities. Vendors operating across this region invest in configurable privacy controls, multilingual support, and compliance workflows that can address both stringent data protection regimes and variable reimbursement mechanisms. Meanwhile, the Asia-Pacific region demonstrates rapid adoption of cloud-native offerings as organizations leverage public and hybrid cloud environments to accelerate analytics deployment. Variances in digital health maturity across the region mean that vendors must offer flexible implementation tracks and local partnership networks to succeed. These regional insights underscore the importance of regulatory alignment, partner ecosystems, and localization strategies for sustainable deployment and adoption.
Summarize the competitive environment and vendor differentiation factors including integration capabilities, managed services, partnerships, and evidence-based validation approaches
Competitive dynamics in the clinical risk grouping space are characterized by a mix of established platform providers, specialized analytics firms, and emerging entrants that blend clinical expertise with data science capabilities. Leading companies differentiate on the basis of algorithmic transparency, integration APIs, and proven interoperability with electronic health records and claims systems. Some vendors emphasize end-to-end managed services to reduce buyer implementation burden, while others focus on modular components that allow customers to integrate only the capabilities they need, such as cohorting engines or real-time risk feeds.
Partnerships between technology firms, system integrators, and domain-specialist consultancies are increasingly central to delivering comprehensive solutions that span data ingestion, normalization, grouping logic, and downstream workflow activation. Strategic alliances with cloud hyperscalers and regional systems integrators help vendors meet requirements for scalability, security, and localized delivery. Competitive positioning also reflects investment in validation studies, clinician-facing explainability features, and professional services that support change management. For buyers, vendor selection hinges on demonstrated interoperability, referenceable deployments in analogous care settings, and the availability of configurable governance frameworks that align with institutional risk tolerance and regulatory obligations.
Provide practical, high-impact recommendations for leaders to accelerate adoption, ensure governance, and secure measurable operational and clinical outcomes through phased execution
Industry leaders should prioritize interoperability, algorithmic transparency, and practical governance frameworks to accelerate adoption while managing clinical and regulatory risk. They should adopt phased implementation roadmaps that start with high-impact use cases and progressively expand to support broader care coordination objectives. This incremental approach reduces operational disruption and permits early validation of clinical impact, enabling iterative refinement of grouping logic and integration touchpoints.
Procurement teams are advised to require demonstrable explainability and auditability for classification outcomes, to stipulate clear service-level commitments for data exchange, and to negotiate flexible licensing that accommodates pilot-to-scale transitions. Organizational leaders should invest in cross-disciplinary governance councils that bring together clinical, data science, compliance, and IT stakeholders to oversee model performance and change management. Vendors should offer configurable deployment templates for Hybrid Cloud, Private Cloud, and Public Cloud scenarios to meet diverse infrastructure constraints, and provide bundled Implementation Services and Support And Maintenance options to support clients with limited internal resources. Finally, building strategic partnerships with system integrators and local providers can de-risk implementations and accelerate time to operational value.
Describe a rigorous, multi-source research methodology that blends stakeholder interviews, vendor capability assessment, and scenario-based analysis to validate findings
The research behind these insights combines qualitative assessments, vendor capability reviews, and synthesis of publicly available regulatory and policy materials to build a cohesive understanding of the space. Primary inputs include structured interviews with clinical leaders, payer executives, and implementation specialists, augmented by vendor whitepapers, product documentation, and case study analyses. Comparative evaluation criteria focus on interoperability, deployment flexibility, explainability, validation practices, and professional services capabilities to ensure assessments are grounded in operational realities.
Analytical methods prioritize triangulation across sources to validate claims about product features and deployment outcomes, including cross-verification of vendor functionality with third-party integrations and client testimonials. The methodology also incorporates scenario analysis to surface implications of policy changes and supply chain disruptions, and a governance lens to evaluate controls for data privacy and algorithmic accountability. Transparency in methodology and source attribution supports reproducibility of findings and enables buyers to align insights with their internal requirements during vendor selection and procurement processes.
Provide a conclusive synthesis that ties together strategic imperatives, operational risks, and practical prerequisites for successful adoption and governance of risk grouping solutions
In conclusion, clinical risk grouping solutions are at an inflection point where technological maturity, regulatory scrutiny, and changing payment models converge to reshape procurement and deployment strategies. Organizations that prioritize transparent algorithms, robust interoperability, and phased implementation approaches will be better positioned to translate risk stratification into tangible clinical and operational benefits. Supply chain and policy considerations, such as tariff shifts, add an additional layer of complexity that requires deliberate planning around hardware sourcing and deployment sequencing.
Successful adoption depends on aligning solution capabilities with organizational needs defined by deployment preferences, solution type bundling, payment model alignment, enterprise scale considerations, and end-user requirements. Regional variations further necessitate localization and partnership strategies that respect regulatory and cultural differences. By integrating these elements into procurement, governance, and implementation plans, stakeholders can reduce adoption risk and accelerate value realization while maintaining compliance and operational continuity.
Please Note: PDF & Excel + Online Access - 1 Year
Table of Contents
189 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Integration of multi-source data including EHR, social determinants, and genomics for comprehensive clinical risk grouping
- 5.2. Utilization of machine learning models for dynamic real-time adjustment of patient risk categories in value-based care
- 5.3. Implementation of cloud-native risk stratification platforms with enhanced interoperability across healthcare networks
- 5.4. Expansion of predictive analytics incorporating behavioral health and socioeconomic indicators for population health management
- 5.5. Development of explainable AI frameworks to ensure transparency and clinician trust in risk score recommendations
- 5.6. Adoption of standardized risk adjustment methodologies aligned with CMS guidelines for reimbursement optimization
- 5.7. Deployment of remote monitoring data streams from wearable devices to refine risk assessment models in chronic disease management
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Clinical Risk Grouping Solution Market, by Deployment Mode
- 8.1. Cloud
- 8.1.1. Hybrid Cloud
- 8.1.2. Private Cloud
- 8.1.3. Public Cloud
- 8.2. On Premise
- 9. Clinical Risk Grouping Solution Market, by Solution Type
- 9.1. Software And Services
- 9.1.1. Implementation Services
- 9.1.2. Support And Maintenance
- 9.2. Software Only
- 10. Clinical Risk Grouping Solution Market, by Payment Model
- 10.1. Fee For Service
- 10.2. Value Based Care
- 11. Clinical Risk Grouping Solution Market, by Organization Size
- 11.1. Large Enterprises
- 11.2. Small And Medium Enterprises
- 12. Clinical Risk Grouping Solution Market, by End User
- 12.1. Hospitals
- 12.2. Payers
- 12.3. Research Institutes
- 13. Clinical Risk Grouping Solution 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. Clinical Risk Grouping Solution Market, by Group
- 14.1. ASEAN
- 14.2. GCC
- 14.3. European Union
- 14.4. BRICS
- 14.5. G7
- 14.6. NATO
- 15. Clinical Risk Grouping Solution 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. 3M Company
- 16.3.2. Allscripts Healthcare Solutions, Inc.
- 16.3.3. Cognizant Technology Solutions Corporation
- 16.3.4. Conduent, Inc.
- 16.3.5. Cotiviti, Inc.
- 16.3.6. Epic Systems Corporation
- 16.3.7. Evolent Health, Inc.
- 16.3.8. HBI Solutions, Inc.
- 16.3.9. Health Catalyst, Inc.
- 16.3.10. HMS Holdings Corp.
- 16.3.11. Lightbeam Health Solutions
- 16.3.12. Oracle Corporation
- 16.3.13. R1 RCM Inc.
- 16.3.14. UnitedHealth Group Incorporated
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