Key result
Qualitative interviews identified five main categories regarding digital adherence solutions, which were summarized as the Adherence Radar framework to assess the potential of adherence tools.
Why the study?
Digital adherence solutions are rarely used and have low acceptance among elderly patients, prompting a need to understand how to evaluate them and identify factors driving wider acceptance.
A qualitative study identified five main categories of patient attitudes toward digital adherence solutions, summarized as the Adherence Radar framework to guide patient-centric app design.
Supports evaluation of digital adherence tools in research; leaves open clinical utility pending validation.
BACKGROUND: Nonadherence to medication is a driver of morbidity and mortality, and complex medication regimens in patients with chronic diseases foster the problem. Digital technology might help, but despite numerous solutions being developed, none are currently widely used, and acceptance rates remain low, especially among the elderly. OBJECTIVE: This study aimed to better understand and operationalize how new digital solutions can be evaluated. Particularly, the goal was to identify factors that help digital approaches targeting adherence to become more widely accepted. METHODS: A qualitative study using a conceptual grounded theory approach was conducted. We included patients aged 65 years and older who routinely took new oral anticoagulants. To generate theses about the digital competencies of the target group with daily medication intake, face-to-face interviews were conducted, recorded, and anonymized. After coding the interviews, categories were generated, discussed, and combined with several theses until saturation of the statements was reached. RESULTS: The methodological approach led to the finding that after interviews in 20 of 77 potentially available patients, a saturation of statements was reached. The average patient's age was 75 years, and 50% (10/20) of the subjects were female. The data identified five main coding categories-Diseases and medicine, Technology, Autonomy, Patient narrative, and Attitude toward technologies-each including positive and negative subcategories. Main categories and subcategories were summarized as Adherence Radar, which can be considered as a framework to assess the potential of adherence solutions in the process of prototyping and can be applied to all adherence tools in a holistic manner. CONCLUSIONS: The Adherence Radar can be used to increase the acceptance rate of digital solutions targeting adherence. For a patient-centric design, an app should be adapted to the individual patient's needs. According to our results, this application should be based on gender and educational background as well as the individual physician-patient relationship. If used in a proper, individualized manner, digital adherence solutions could become a new cornerstone for the treatment of chronically ill individuals.
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Herrmann et al. (2019) studied Patients taking new oral anticoagulants (n=20). Digital adherence solutions was evaluated on Factors that help digital approaches targeting adherence to become more widely accepted. Qualitative interviews identified five main categories regarding digital adherence solutions, which were summarized as the Adherence Radar framework to assess the potential of adherence tools.
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