SAS® Analytics help high-risk patients stay on therapeutic track
Express Scripts uses SAS® to identify, assist patients likely to stop medications
CARY, NC (Jun. 15, 2011) – When patients stop taking prescribed drugs or reduce frequency or dosages, the effect can be devastating, causing health complications or even death. Express Scripts, one of the largest pharmacy benefit management companies in North America, trusts SAS Analytics to keep patients on their drug regimens to live healthier lives.
Express Scripts handles millions of prescriptions annually. Using software from SAS, the leader in business analytics, the company predicts patients likely to abandon medication, offering intervention programs to address potential issues before the patient becomes noncompliant.
"When patients stop taking a prescribed drug against doctors' advice, it can significantly set back treatment," said Jason Burke, Managing Director and Chief Strategist for the SAS Center for Health Analytics and Insights (CHAI). "It's a widespread problem. A Harris Interactive poll estimated that between 14 and 30 percent of US patients have stopped or altered their prescription drug regimens."
SAS predictive models developed by Express Scripts analyze more than 400 factors related to patients, drugs, conditions, physicians and other issues. Based on that analysis, Express Scripts tailors proactive interventions to an individual's likely barriers to compliance. Actions might include automated reminder calls, individualized education and support, or automated refills, for example.
"For patients requiring medications with chronic disease classes, such as hypertension, diabetes or high cholesterol, it's in their best interest for better health outcomes, as well as in the payer's best interest, that they continue their prescription regimens," said Express Scripts Director of Advanced Analytics Dave Tomala. "Even if medication costs increase marginally, overall medical costs are minimized through better health outcomes."
Express Scripts uses the predictive models created with SAS Analytics to continually improve its services and become a proactive partner in patients' health.
"We're talking about treating patients proactively. We can predict who will comply with their medication or not,"
Tomala explained. "Our outreach programs address an individual's risk factors. People too busy to order a refill can be moved into an automated refill program before a lapse occurs. Patients concerned about side effects might benefit from talking to a pharmacist. We analyze each patient to offer the most effective programs to keep them healthy."
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