Introducing the Adherence Strategy Engineering Framework (ASEF)

Background: Patients performing self-care in the unsupervised setting do not always adhere to the instructions they were initially provided with. As a consequence, a patient’s ability to successfully comply with the treatment plan cannot be verified by the treating healthcare professional, possibly resulting in reduced data quality and suboptimal treatment. Objectives: The aim of this paper is to introduce the Adherence Strategy Engineering Framework (ASEF) as a method for developing novel technology-based adherence strategies to assess and improve patient adherence levels in the unsupervised setting. Methods: Key concepts related to self-care and adherence were defined, discussed, and implemented as part of the ASEF framework. ASEF was applied to seven self-care case studies, and the perceived usefulness and feasibility of ASEF was evaluated in a questionnaire study by the case study participants. Finally, we reviewed the individual case studies usage of ASEF. Results: A range of central self-care concepts were defined and the ASEF methodological framework was introduced. ASEF was successfully used in seven case studies with a total of 25 participants. Of these, 16 provided answers in the questionnaire study reporting ASEF as useful and feasible. Case study reviews illustrated the potential of using context-aware technologies to support self-care in the unsupervised setting as well as ASEF’s ability to support this. Conclusion: Challenges associated with moving healthcare to the unsupervised setting can be overcome by applying novel context-aware technology using the ASEF method. This could lead to better treatment outcomes and reduce healthcare expenditures.