Innovative Approaches to Enhance and Measure Medication Adherence in Chronic Disease Management: A Review.
Michał GackowskiMagdalena Jasińska-StroscheinTomasz Zbigniew OsmałekMagdalena Waszyk-NowaczykPublished in: Medical science monitor : international medical journal of experimental and clinical research (2024)
Medication non-adherence is a problem that affects up to 50% of patients with chronic diseases. The result is a failure to achieve therapeutic goals and an increased burden on the healthcare system. It is, therefore, highly appropriate to develop models to assess patient adherence to prescribed therapy. To date, there are many methods for doing this. However, several tools have been developed that subjectively or objectively, directly or indirectly, assess the level of patient adherence. Electronic medication packaging devices are among the most rapidly evolving methods of measuring adherence. Other emerging technologies include the use of artificial intelligence algorithms and ingestible biosensors. The former is being used to create applications for mobile phones and laptops. The latter appears to be the least susceptible to the risk of overestimating adherence but remains very expensive. Here, we present recent developments in measuring patient adherence, and provide details of achievements in objective methods for assessing adherence, such as electronic monitoring devices, video-observed therapy, and ingestible biosensors. A dedicated section on using artificial intelligence and machine learning in adherence measurement and reviewing questionnaires and scales used in specific diseases is also included. Methods are discussed along with their advantages and potential limitations. This article aimed to review current measures and future initiatives to improve patient medication adherence.
Keyphrases
- artificial intelligence
- machine learning
- deep learning
- big data
- case report
- glycemic control
- healthcare
- emergency department
- adipose tissue
- physical activity
- type diabetes
- bone marrow
- quality improvement
- risk assessment
- risk factors
- insulin resistance
- mesenchymal stem cells
- weight loss
- electronic health record
- replacement therapy
- psychometric properties