Side Effects: irreconcilable differences or is there still hope?
Why health plan managers need to understand the barriers behind medication adherence before they can effectively address them.
Two patients are sitting in the waiting room of their doctor’s office: Diane is a lively 63-year-old woman in good overall health. Diane generally prefers to avoid the health system unless she absolutely needs to. She is managing one chronic condition for which her physician prescribed a medication that she promptly filled and stopped after just ten days.
Diane is what we call the ‘Feel Finer’.
Sitting across from her is Jake, who just turned 67. Jake is managing two chronic conditions; he filled the doctor’s prescription and shortly after, he began experiencing side effects that disrupted his workdays. Jake was reluctant to call his physician and did not want to confront the issue about his medication and side effects. Furthermore, he was not aware of alternative treatments that were available to him. Instead, he ceased taking the medication, increasing the risk of complications from his underlying conditions in the future. Jake’s decision is triggered by side effects. Studies show that the ‘side effect’ factor is the most critical determinant of medication adherence among members between 60-75 years of age with an annual income over $60K.
As we discover, similar patient profiles are motivated by very different human factors, and require different persuasion strategies. By understanding what is triggering non-adherence, we can help Diane and Jake, and support the physician’s efforts to keep their health on track.
How does Medorion mediate the behavior?
Let’s walk through the different communication strategies required to increase medication adherence in these two respective cases. In the first round of data analysis, the Behavioral AI engine sifts through thousands of clinical and demographic factors (chronic conditions, doctor visitations, income, and age are elementary – we dig deeper) and translates billions of data points into a rich canvas of behavioral patterns to reveal what motivates people’s decisions and why.
In the second round, Medorion experts segment the data and provide insights on what theory explains the highlighted behavior. The engine then identifies the four or five most significant and diverse predictors and conducts a randomized experiment, pulling out a sample of the population and sending each member each one of the messages.
Based on who opened the message, the system matches the results with other similar members who may also open it, helping to improve machine prediction. The engine constantly checks the assumptions that underline the data, helping to improve the prediction model continuously and in turn, empowering health plans to learn insights about their population that are applicable to other members, too. This, in essence, is the Medorion constellation.
In this case, we know that some members will be more like Diane, while others will identify with Jake. When it comes to members like Diane who do not understand the necessity of taking the medication even if they are feeling good, health plan marketers would send a message that targets this belief and attempt to influence her decision to take the medication:
“Even though you may feel fine, it is important to keep taking the medication prescribed by your doctor to treat your condition and ensure your health in the long-term. Consult your doctor to understand how the medication works; they can help adjust the treatment program if needed.”
In contrast, members like Jake command a different approach. In his mind is a belief: “My doctor gave me a prescription but I felt awful with the medication. I don’t want to confront her about this and find out what other medications I could take.”
The discomforting idea of having the day hijacked by side effects, or feeling uncomfortable about calling the doctor with ‘unimportant issues’ is a real struggle. While his decision to stop taking the medication is not a rational one since it is motivated by fear and anxiety, we can help Jake by acknowledging his experience with side effects, and encouraging him to share this experience with his doctor in order to find a better treatment option:
“Side effect worries are common, especially when taking a new medication. Speak with your doctor if you are experiencing any discomfort with your current medication. Whether you need to change the medication or dosage plan, there are alternatives available to you.”
What does this teach us?
Health behavior is an inside job that starts with an awareness, not just on the part of the patient but also the outside world that is constantly sending us messages, trying to convince us to perform desired actions. The slightest nuance can either repel us or motivate us.
The obvious answer is that we are complex beings. The simple answer is that while we cannot change people, we can help them to understand that they always have an option.
We know what works because we build our Behavioral AI engine by applying knowledge and human behavioral insight to develop the most powerful algorithms that motivate awareness when and where we need it most.
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