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A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level
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Introducing the Adherence Strategy Engineering Framework (ASEF). Support for developing technology-based self-care

S Wagner1, T S Toftegaard, O W Bertelsen

  • 1Department of Engineering, Aarhus University, Finlandsgade 2, 8200 Aarhus N, Denmark. sw@iha.dk

Methods of Information in Medicine
|April 18, 2013
PubMed
Summary
This summary is machine-generated.

The Adherence Strategy Engineering Framework (ASEF) helps develop technology-based strategies to improve patient self-care adherence in unsupervised settings. This method, tested in seven case studies, proved useful and feasible for enhancing treatment outcomes.

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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

Area of Science:

  • Healthcare Technology
  • Patient Adherence
  • Self-Care Management

Background:

  • Patient adherence to self-care instructions in unsupervised settings is often suboptimal.
  • Lack of verification by healthcare professionals can lead to reduced data quality and poor treatment outcomes.

Purpose of the Study:

  • Introduce the Adherence Strategy Engineering Framework (ASEF) for developing technology-based adherence strategies.
  • Assess and improve patient adherence in unsupervised self-care settings.

Main Methods:

  • Defined and implemented key self-care and adherence concepts within the ASEF framework.
  • Applied ASEF to seven self-care case studies.
  • Evaluated ASEF's usefulness and feasibility via a questionnaire study with participants.

Main Results:

  • The ASEF methodological framework was introduced and successfully applied across seven case studies with 25 participants.
  • 16 participants reported ASEF as useful and feasible in a questionnaire study.
  • Case studies demonstrated the potential of context-aware technologies and ASEF in supporting unsupervised self-care.

Conclusions:

  • Novel context-aware technology, guided by ASEF, can overcome challenges in unsupervised healthcare.
  • This approach has the potential to improve patient treatment outcomes and reduce healthcare costs.