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Truven Health Risk Model Ranks High in Actuarial Evaluation

By John Azzolini/Monday, November 28, 2016

 

Healthcare payers today are facing the complexities of reform, increased competition, and budget constraints — all while dealing with pressures to reduce costs and improve member health. Managing health risk has become a necessity. But to manage risk, payers must first understand their population. To do this well, they need reliable, robust risk and cost of care models.

 

Last month, the Society of Actuaries (SOA) released a study showing that Truven Health Analytics’ cost of care model outperformed other risk models in 18 out of 22 measures. SOA’s Accuracy of Claims-Based Risk Scoring Models compared health risk-scoring models, building on their previous studies with similar objectives (the most recent was in 2007). In the medical claims category (predictions based only on medical claims data), the current study showed that, in 21 of the 22 measures, the Truven Health model was ranked either first or second. No other model came close to matching this performance. (See Table 1 for a summary of how Truven Health’s model ranked relative to the competition).

 

How the SOA Evaluates Risk Models

The SOA evaluated Truven Health Analytics’ cost of care model against six others:

 

  • ACG® System
  • Chronic Illness & Disability Payment System and MedicaidRx
  • DxCG Intelligence
  • HHS-HCC
  • Milliman Advanced Risk Adjusters
  • Wakely Risk Assessment Model

 

The SOA assessed all models on their ability to predict costs using the Truven Health Marketscan® commercial claims dataset of 1 million members, and used three methodologies to evaluate their precision: R-Squared, the mean absolute error statistics, and predictive ratios. All three methodologies measure the statistical difference between the prediction and the actual results. All models produced both a concurrent and prospective cost prediction and were evaluated using both a capped data set (where patient costs were capped at $250,000) and a non-capped data set.

 

The SOA evaluated the models’ predictive ability using a number of scenarios (total medical costs, simulated random groups, condition-specific predictions, patient cost). In the simulated random group scenario, the SOA created groups of 1,000 and 10,000 patients to simulate the application of the model to subgroups of the population.

 

Table 1: How the Truven Health Cost of Care Model Performed

The Truven Health model ranked first or second for its ability to predict costs in 21 of the 22 measures studied.

 

Scenario

Truven Health Model Ranking*

R-Squared

Mean Absolute Error

Non-Capped

Capped**

Non-Capped

Capped**

Total Medical Costs, Concurrent

2

1

2

1

Total Medical Costs, Prospective

1

1

1

1

Simulated Random Groups, Concurrent

2

3

1

1

Simulated Random Groups, Prospective

1

1

1

1

 

 

Predictive Ratios

 

 

Overall Condition Specific Prediction, Concurrent

 

1

 

 

Overall Condition Specific Prediction, Prospective

 

1

 

 

Very Low Cost Patients, Concurrent

 

1

 

 

Very Low Cost Patients, Prospective

 

1

 

 

Very High Cost Patients, Concurrent

 

1

 

 

Very High Cost Patients, Prospective

 

1

 

 

     * Compared with six other models.

** Capped at $250,000

 

Why Risk Models Are Important to Payers

Risk modeling is a very helpful tool for health plans and employers. It can provide valuable insights into member utilization patterns and risk– vital for benefit planning, disease management and wellness program management, and member communications. It can provide deep insights into provider performance, and aid in determining ideal reimbursement and premium rates. Such models are an integral part of a number of Truven Health databases and analytical tools. The SOA evaluation speaks to the high quality and reliability of the Truven Health solutions.

John Azzolini
Senior Consulting Scientist
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