3 Ways Express Scripts Uses Data To Improve Health Outcomes

Jan 18, 2018

Pharmacy data are often considered the best predictors of a patient’s health. Unlike medical claims data, which may appear weeks after the healthcare action and only a few times per year, pharmacy data come in real-time upon each prescription fill.

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The healthcare industry produces an incredible amount of data. Yet, in many cases, the information and insights derived from this data are inadequate.

At Express Scripts, we believe big data is useless until it is made actionable. Using big data to generate actionable insights helps us to improve healthcare by making it more accessible, affordable and effective for the 83 million Americans we serve.

The Value of Pharmacy Data

We recently highlighted three examples of how we leverage data to improve health outcomes in CIO Applications magazine. Here are these examples in action:

1. Addressing the opioid epidemic through proactive intervention

The fast-growing opioid epidemic has been called the worst drug crisis in American history. As we looked for a solution that worked across the care continuum of physician, pharmacy and patient, we leveraged data to proactively identify areas of risk.

Our advanced analytics, including MediCUBE®, supports Express Scripts’ Advanced Opioid Management solution. MediCUBE's power comes from a proprietary analytic engine that processes 15 billion prescription claim records and 5 billion medical claim records for nearly 200 million patients. When we identify an outlier – a doctor, pharmacy or patient behaving in ways we would not expect, possibly indicating opioid drug abuse – we are able to intervene before it’s too late.

This may result in outreach from a specialist pharmacist to the patient to discuss the risks associated with opioid use even before filling a prescription. It could also include academic detailing to empower physicians with more information as they make opioid prescribing decisions.

2. Avoiding downstream costs and negative health events

To address nonadherence, Express Scripts’ ScreenRx® solution has leveraged machine learning algorithms to uncover the more than 300 features about patients, physicians, diseases, and prescribed therapies to identify the individuals most likely to stop taking their medication.

For example, machine learning uncovered that males with female physicians are less likely to be adherent to their treatment plan. Conversely, living with a partner, or having a higher income, will increase your likelihood for adherence. It’s not enough to know who is going to be nonadherent. It also requires proactive intervention.

If a patient is likely to become nonadherent due to behavioral factors such as procrastination or forgetfulness (most frequently cited factors), Express Scripts may send the patient daily alerts, 90-day fills, or schedule auto-renewals. If a patient is likely to have clinical questions or concerns about the medication, the patient will receive a pharmacist consultation. If high cost is the primary concern, Express Scripts may contact the patient about payment assistance programs, lower cost medication alternatives and lower cost pharmacy options such as home delivery.

3. Predicting personalized risk to influence better health

Advanced analytics and artificial intelligence provide the cutting edge capability to determine the health risk of individuals. By layering medical, lab and nontraditional data onto our already robust pharmacy data, we can identify very personalized healthcare gaps. More importantly, we can recommend actions necessary to change patient behavior and close the identified gaps.

For example, using our advanced integrated data insights, Express Scripts identified a patient with diabetes, depression and chronic pain with open pharmacy and medical gap opportunities. One of our diabetes specialist pharmacists counseled the patient to work with her physician to measure her A1C, a leading indicator of well-managed diabetes. We highlighted clinically-equivalent generic medication options that may be more affordable to the patient. And finally, we shared tips for better adherence to treatment plan, which prevents downstream health costs. By closing these very specific, very actionable gaps, we can move a patient with high risk index to low risk index.

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