DxCG Intelligence

Clearly identify, stratify, and manage individual and population risk

The facts

To effectively analyze healthcare outcomes and spending and appropriately manage clinical and financial risks, organizations need to be able to take into account the clinical complexity of each individual in a specific population. Risk adjustment is a statistical process that allows organizations to make fair comparisons of healthcare delivery and payment systems, and in so doing, identify opportunities for improvement.

Part of healthcare’s DNA for 20 years, DxCG Intelligence is at the core of Cotiviti’s performance analytics solutions. The gold standard in risk adjustment and predictive modeling, DxCG Intelligence analyzes and helps manage the clinical and financial risks associated with caring for populations, with specificity at the individual level.

DxCG Intelligence uses Cotiviti’s proprietary predictive models to turn healthcare data into risk scores for individual members. Scores correlate with the cost of their underlying illness burden. Aggregating the scores of individuals with key attributes generates group-level predictive results that can help answer critical questions about healthcare efficiency.

Benefits

Assess the disease burden of individuals, subgroups, and populations

Predict the future cost of care for a population

Measure efficiency in healthcare resource usage

Assess performance relative to peer groups or benchmarks

Develop fair and accurate risk-based provider payment systems

Inform care management and evaluate the impact of quality programs

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Superior predictive power

Cotiviti has been honored to advance the science of risk scoring by working with the Society of Actuaries (SOA) over the past two decades. SOA’s rigor and effort to resolve potential disparities in the analysis ensure a comprehensive evaluation of commercial risk adjustment and predictive models.

SOA’s latest study was published in 2016. Similar to their previous evaluation in 2007, DxCG models were top performers across the study.

DxCG is the clear industry leader in:

  • Longevity
  • Depth of validation
  • Breadth of scope and models
  • Model utility

 

Robust models and applications

DxCG Intelligence fully addresses cost, utilization, and risk across all populations. Our transparent, credible measures of population health risk are both clinically and financially grounded, increasing buy-in and making it easier for physicians, medical professionals, and analysts to see the impact of comorbidities, among other benefits.

 

Rapid time to value

DxCG Intelligence is easy to implement, whether an organization selects hosted or installed versions of the software, and integrates seamlessly with other software solutions. Our world-class customer support team supplies data acquisition and mapping support, software maintenance, educational resources, and access to our seasoned data scientists, statisticians, clinicians, and other subject-matter experts.

 

An unmatched legacy

A groundbreaker in the early 1990s, the DxCG models were developed in partnership with the U.S. Centers for Medicare & Medicaid Services (CMS) and served as the foundation for the Hierarchical Condition Category (HCC) model that CMS still uses as the foundation for risk-adjusted healthcare payments today.

Nearly 500 organizations use DxCG Intelligence, which provides a common language of risk adjustment for healthcare payers and providers, for employers, for government agencies, and for academic researchers investigating ways to improve healthcare administration and delivery.

 

Knowledge is power

DxCG Intelligence incorporates the industry’s broadest set of risk management and predictive models, which in turn put the power of science to work in addressing your most pressing clinical and financial performance challenges. Models are grouped into three primary functional bundles—budgeting and underwriting, medical management, and performance assessment—as well as tailored for commercial, Medicare, and Medicaid populations, building the successful foundation for optimal results.

Foundational models and analytics

 

Budgeting and underwriting 

  • Quantify the health risk of enrolled populations
  • Measure risk trends over time across lines of business
  • Budget for care delivery costs
  • Adjust premiums and payment rates
  • Assess reinsurance options based on risk tolerance
  • Substantiate insurance rate filing

 

Medical management

  • Identify high-risk individuals
  • Stratify clinical groups to define outreach strategies
  • Prioritize individuals for targeted interventions
  • Enable member outreach to improve care compliance

 

Performance assessment

  • Quantify physician panel risk burden
  • Establish risk-expected rate variation
  • Assess provider panel utilization variance
  • Support risk-based contracts and gain sharing
  • Promote accountability in healthcare systems
  • Analyze population health outcomes

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