Mastering Patient Cohorts: The Key to Value-Based Care Success

Patient cohorts—groups of patients organized by shared characteristics, conditions, or risk factors—represent the cornerstone of effective population health management. As healthcare organizations navigate the complexities of value-based care (VBC), the ability to segment and analyze patient populations have become essential for driving both cost savings and improved health outcomes.

The importance of cohort-based analysis in population health management cannot be overstated. With 88.5 million lives in accountable care arrangements in 2023 across commercial, Medicare, and Medicaid, healthcare organizations are under increasing pressure to demonstrate measurable results.

The financial stakes are enormous. Value-based care is projected to grow from $4.01 trillion to 6.16 trillion by 2030, representing a fundamental shift in how healthcare is delivered and paid for. Organizations that master cohort-based analytics position themselves to capture this growth while delivering the improved outcomes that VBC demands.

When patient cohorts are managed through advanced data analytics, organizations gain unprecedented visibility into their populations, enabling targeted interventions that reduce costs while improving care quality. This approach transforms healthcare from reactive treatment to proactive management, creating sustainable value for all stakeholders.

Top 5 Common Patient Cohort Use Cases

1. Disease/Condition Management

Creating cohorts based on specific diseases or conditions allows healthcare organizations to monitor outcomes systematically and implement targeted interventions. This approach is particularly powerful for chronic conditions that drive significant healthcare costs and require ongoing management.

Key Applications:

• ‍Diabetes Management Initiatives: Tracking HbA1c levels, medication adherence, and complications across diabetic populations to optimize treatment protocols and prevent costly complications‍
• Cancer Patient Tracking and Analysis: Monitoring treatment pathways, survival rates, and quality of life measures to improve oncology care coordination‍
• COPD and CKD Patient Identification: Early identification and management of chronic obstructive pulmonary disease and chronic kidney disease patients to prevent exacerbations and slow disease progression‍
• Specialty Condition Management: Monitoring patients on high-cost medications like Ozempic for diabetes and weight management, tracking both clinical outcomes and cost-effectiveness

Value Delivered: Disease-specific cohorts enable targeted care interventions that improve patient outcomes while reducing unnecessary utilization. Organizations can measure the effectiveness of bundled payment programs, identify risk coding opportunities, manage pharmacy adherence and demonstrate improved quality metrics to payers and regulators.

2. Suspect Conditions & HCC Risk Coding

Hierarchical Condition Category (HCC) coding has become increasingly complex and valuable, with approximately 74,000 ICD-10-CM diagnosis codes now classified into 266 CMS-HCCs in the 2024 model. Organizations use cohorts to improve coding accuracy and risk adjustment, directly impacting revenue and care quality.

The 2024 CMS-HCC model represents a significant shift in risk adjustment methodology. Risk scores will blend 67% from the current model and 33% from the finalized2024 model in Payment Year 2024, shifting to 33% current and 67% new model in2025, with 100% of risk scores based on the finalized 2024 model by 2026.

Key Applications:

• ‍HCC Risk Coding Opportunities: Identifying patients with documented conditions that haven't been properly coded, ensuring accurate risk adjustment and appropriate reimbursement‍
• BMI-Based Morbid Obesity Identification: Using BMI data to identify patients who should be coded for obesity-related conditions but haven't been diagnosed‍
• Medication-Condition Mismatches: Analyzing prescription patterns to identify patients taking medications for conditions that aren't documented in their medical records ‍
• Historical Condition Recapture: Reviewing past medical records to identify chronic conditions that should be coded annually but may have been missed‍
• Lab Results Without Corresponding Diagnoses: Flagging abnormal lab values that suggest undiagnosed conditions requiring further evaluation and potential coding

Value Delivered: Proper HCC coding can significantly impact organizational revenue. Accurate risk adjustment is crucial for financial sustainability. Organizations see increased risk adjustment accuracy, revenue optimization through proper coding, early intervention opportunities, and improved provider workflow integration.

3. High-Cost Member Management

It’s estimated that the top 5% of patients account for nearly 50% of healthcare costs. Cohort-based analysis enables organizations to identify and manage these high-utilizers effectively.

Key Processes:

• ‍Identify Top 20% Highest-Cost Members: Systematically analyzing spending patterns across different programs and service lines to identify the most expensive patients‍
• Comprehensive KPI and Care History Analysis: Developing detailed profiles of high-cost members, including comorbidities, utilization patterns, and social determinants of health‍
• Care Management Program Enrollment: Implementing targeted outreach to enroll high-risk patients in appropriate care management programs‍
• Enrollment Tracking and Outcomes Measurement: Monitoring care management program participation and measuring outcomes compared to non-enrolled patients

Value Delivered: ACOs monitor quality measure gaps, readmission rates, recent visit patterns, primary diagnosis codes, and most importantly, care management enrollment outcomes to determine program effectiveness in reducing costs and utilization.

High-cost member management enables targeted resource allocation, demonstrates care management program ROI, implements effective cost containment strategies, and ultimately improves patient outcomes. Value-based care models have been associated with a 4.6% reduction in 30-day hospital readmission rates, directly impacting this high-cost population.

4. Care Management Enrollment

Creating targeted lists for care management program enrollment requires sophisticated cohort analysis that goes beyond simple demographic or diagnostic criteria. Organizations must identify patients who will benefit most from care management interventions.

Key Implementation Methods:

• ‍Data List Filtering and Extraction: Using multiple data sources to create comprehensive patient profiles for care management eligibility‍
• Custom Report Generation: Developing tailored reports for different care management programs based on specific enrollment criteria‍
• Integration with Care Management Platforms: Seamlessly connecting cohort analysis with existing care management systems for efficient workflow‍
• Monthly Automated Workflows: Establishing recurring processes to continuously identify new candidates for care management enrollment‍
• Multi-Platform Care Coordination: Ensuring care management cohorts are accessible across different healthcare delivery platforms and provider networks

Value Delivered: Effective care management enrollment streamlines workflows, enhances patient outreach efficiency, engages patients in their care journey, and creates scalable enrollment processes that can grow with organizational needs.

5. Annual Wellness Visit (AWV) Optimization

AWVs are critical for preventive care and for qualifying patients for CMS chronic care management and care coordination billing. Yet, only 60% of Medicare beneficiaries receive an AWV each year—leaving opportunity on the table in both patient health outcomes and revenue.

Key Applications:

• ‍AWV Compliance Tracking: Monitoring which patients are due for or have missed their annual wellness visits‍
• Provider Outreach Prioritization: Helping providers focus their outreach efforts on patients most likely to benefit from AWV completion‍
• CMS Care Management Code Qualification: Ensuring patients meet criteria for additional CMS CCM reimbursement opportunities‍
• Revenue Optimization: Maximizing appropriate coding and billing for AWV-related services

Value Delivered: ACOs analyze cost comparisons between AWV and non-AWV patients, quality measure performance, emergency department utilization patterns, and HCC recapture rates to demonstrate the comprehensive value of AWV programs.

The analyses reveal that AWV optimization increases preventive care engagement, generates additional revenue through CMS programs, improves patient satisfaction scores, and provides concrete demonstration of better health outcomes. A retrospective study across two physician-led ACOs (8,917 Medicare beneficiaries) found that an AWV was associated with a 5.7% reduction in total healthcare spending over the following 11 months, particularly among high-risk patients.

Finding the Right Partner

Successfully implementing cohort-based analytics requires solutions that empower ACOs and other value-based care organizations to drive measurable results. The right population health analytics partner should provide:

Flexibility in Cohort Creation: The ability to create complex cohorts based on multiple variables, including clinical, demographic, financial, and behavioral factors. Organizations need platforms that can adapt to changing business needs and regulatory requirements.

Multi-Condition Patient Identification: Advanced analytics capabilities that can identify patients meeting multiple criteria simultaneously, enabling more sophisticated risk stratification and care management approaches.

Provider-Specific Dashboards: Customized interfaces that present relevant cohort information to different provider types, ensuring actionable insights reach the right decision-makers at the right time.

Data Transparency and Audit Tools: Comprehensive tracking and reporting capabilities that provide full visibility into cohort methodology, data sources, and analytical processes for regulatory compliance and quality assurance.

Collaborative Custom Report Development: Partnerships that go beyond standard reporting create custom analytics solutions tailored to specific organizational needs and goals.

Benefits of Cohort-Based Approaches

Patient cohort analytics deliver measurable value across multiple dimensions.

Cost Savings Through Targeted Interventions: By identifying high-risk patients before they become high-cost, organizations can implement preventive interventions that reduce expensive acute care utilization.

Improved Care Quality Metrics: Cohort-based care management enables organizations to track and improve performance on quality measures that matter to patients, providers, and payers.

Enhanced Provider Efficiency: Giving providers actionable insights about their patient populations enables more efficient care delivery and better resource allocation.

Better Patient Outcomes: Ultimately, effective cohort management leads to improved health outcomes through more personalized, proactive care.

Measurable Success

Tracking specific metrics to demonstrate the value of cohort-based analytics:

ROI Tracking for Care Management Programs: Measuring the financial impact of care management interventions on total cost of care and utilization patterns.

Quality Measures Improvements: Tracking performance on key quality indicators such as HEDIS/CMS measures, MSSP APP submissions, and clinical outcomes.

Cost Per Member Reductions: Demonstrating overall efficiency improvements through reduced per-member costs while maintaining or improving care quality.

Provider Satisfaction and Adoption Rates: Ensuring that analytics tools are being used effectively by providers and are contributing to improved job satisfaction and clinical decision-making.

Embracing Cohort Analytics for Sustainable Success

Patient cohorts represent the foundation for value-based care success in an increasingly complex healthcare environment.

The importance of flexible, integrated analytics platforms cannot be overstated. As the healthcare industry continue sits shift toward value-based models, healthcare organizations need a population health analytics partner who can adapt to changing requirements while providing the deep insights necessary for effective population health management.

ACOs must embrace cohort-based analytics as a core competency for value-based care success. Choose a partner who provides flexibility, integration, and the analytical power necessary to define, manage, and analyze patient cohorts. With the right population health analytics partner, you can translate complex data into clear, actionable insights that improve outcomes and reduce costs for sustainable success in the value-based care era.

Let's talk about how Koan Health can help you maximize your performance in a value-based world.

‍