SAS^® for Disease Management

Managed healthcare providers, health insurers and other organizations that pay for healthcare are constantly seeking ways to reduce the burden of healthcare costs. Because the majority of all healthcare costs – a staggering 70 percent – is attributable to patients with chronic illnesses, the best way to decrease these costs (and patient suffering) is to identify those patients who have or are likely to develop a chronic illness, and to take measures to stave off the onset of associated complications.

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But how do you identify which patients are at risk? How do you know which interventions make the most medical and financial sense? Will the demand for medical resources match your supply? The answers to these critical questions and more can be found using SAS for Disease Management.

SAS for Disease Management delivers accurate, timely information that enables you to predict risk and optimize interventions, so you can achieve improved outcomes. By leveraging award-winning data warehousing and data mining software for predictive modeling, SAS for Disease Management goes beyond traditional disease management solutions to offer:

A single view of the patient or member. Advanced analytics for predicting risk. Optimization of interventions. Improved clinical outcomes.

SAS for Disease Management supports the four-step disease management process:

Data Acquisition and Management
Medical and pharmaceutical claims are the core information source for most disease management activities. However, claims records are designed to facilitate billing – not to provide a complete representation of population health characteristics. The SAS solution supplements claims data with data on membership and provider eligibility, pharmaceutical records, in-patient and out-patient billing, dental and vision billing, lab results and medical assessment questionnaires. The result is a more complete picture based on a variety of data sources.

Identification and Severity Classification
The SAS solution uses a variety of methods for identifying patients and assigning a severity classification, including:

• Pre-designated lists (as determined by medical evaluations and diagnoses or hospital discharge data).
• Rules-based algorithms based on diagnosis or procedure codes, pharmacy scripts, lab results and medical assessment questionnaires.
• Advanced analytical methods, such as data mining.

Intervention
The SAS solution supplements the critical business activities associated with the intervention stage by:

• Optimizing the intervention method by using data mining techniques to increase the likelihood of first contact and predict which intervention method may be the most effective.
• Employing advanced reporting capabilities, such as scorecards and Web-based reporting, to facilitate the intervention process.

Outcome Management
The SAS solution supports both utilization and expenditure reporting to track the progress and effect of the disease intervention.