Could this be the way to get lapsed patients back on track?

What is the best way to make sure a patient continues to take their medication? With 25-50 % of patients around the world stopping or interrupting their treatment, it’s a question that still needs a reliable answer. Healthcare providers may think it’s obvious that people should follow the treatment prescribed to them. But there many reasons why they might stop, including concerns about cost, choosing to change the prescribed dosage, and just plain forgetfulness. Although there are many patient education programs in place in hospitals and medical centers, it’s clear that these methods don’t work for a significant number of patients. For Amy Parke and Mary Anne Greenberg, authors of a recent Pharmacy Times article on this issue, these programs are missing something: a focus on understanding patients. Parke and Greenberg suggest a method that may work better. Developed by psychologist Susan Michie and her team, the COM-B model is a strategy that takes behavioral influences into consideration. Here’s how it works. Behaviors that can contribute to not taking medication are divided into three main categories: - Capability: How capable is a person, physically and mentally, to behave a certain way? - Opportunity: What outside forces either encourage or hinder a person’s behavior? - Motivation: What causes a person to behave a certain way? Healthcare providers can apply these questions in a variety of ways when they work with patients. One of the easiest is by changing how they talk to patients about why they’ve stopped treatment. Parke and Greenberg point out that patients might feel intimidated or nervous about direct questions like “Are you still taking your medication?” This could result in incomplete or untrue answers. One way to avoid this is to create a list of statements based on the COM-B model that can be used with patients in conversation or in a written document where patients could indicate their agreement on a scale from one to ten (or another similar measurement). The article gives a helpful list of example statements related to the three behavioral categories. For example, statements related to capability include: -My medicine is difficult to use. -I am not sure if the medicine is really helping me. -I cannot afford the medication. It’s also important to gain insight into how a patient views healthcare in general. Sample statements related to this issue include: -I tend to self-treat my illnesses. -I rely on home remedies more than OTC or prescription medications. The COM-B model also recommends that healthcare workers ask patients about how they prefer to communicate and get information about their health, using statements like: -I would rather get information from a member of my health care team than from the pharmaceutical company that manufactures my medication.

-If I were to contact a pharmaceutical company, my preference is to communicate via email. Healthcare providers can gain a lot of insight from their patients’ responses to these statements -- and the fact that they’re not direct questions makes it much more likely that the patients’ responses will be honest. The statements also serve as prompts for a conversation around a patient’s current treatment and how to help them adhere to it in the future. The article points out that healthcare providers can integrate the COM-B method with their current practices. For instance, a telehealth platform could make the statements available to answer via patients’ mobile devices. In fact, Parke and Greenberg write, responding to the statements on a mobile device before meeting with a healthcare provider may have an additional benefit. They cite research that shows that people tend to be more honest when answering digital health behavior assessments, as opposed to direct questions from their doctor. This may be a sad reflection on our times but it’s important to know. After all, changing our approach to the way we get information from and communicate with patients could be what it takes to get them back on track.


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