Personal Visualization of Medication Information
Medication compliance is taking medication as instructed. Non-compliance is caused by a complex field of multiple factors. In terms of compliance, becoming healthy is essentially the most important factor; patients need to take the medication as intended to achieve the best health benefit. If medication is not taken or taken the wrong way, the patient might remain ill or even get worse. Prolonged treatments, additional hospitalizations and the waste of medications not taken also contribute to the financial impact.
Part of the responsibility for medication compliance lies with the pharmaceutical industry and the medical professionals. Where possible, they have to provide clearly tailored information and instructions. At home, medical compliance becomes the responsibility of the patient. There are many reasons why a patient at home does not do as instructed. If information or instructions are not clear or get lost or if there is a lack of understanding or trust in the medication, it will affect a patient’s motivation to comply with instructions on how to take it.
In this practice-oriented thesis, the aim has been to find a solution to improve both understanding and recall and, thus, compliance with medication at home, by showing a visualization of the respective ailment (the reason) together with a visual of the related medication. To achieve this goal, a concept for a smartphone application was designed. This medication management application allows users to visually record the medication information and add any available written information and instructions.
There is a cause and effect relation between the two images (ailment and medication) presented in the overview of medication in the application. This relation establishes that the two images strictly belong together. The meaning conveyed enhances users’ comprehension of the purpose of a medication. The familiarity of the uploaded personal visualization of the reason results in recognition, which then results in a recall of prior knowledge.
Background research focussed on the typology of medical images. An online survey collected data on the preference of image styles that represent a specific health problem. The application offers users different stock images and access to the camera and their own library to visualize the reason for taking the respective medication.