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External tools for collaborative medication scheduling

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Abstract

Medication adherence—taking medication as prescribed—is critical for successful self-care, especially among older adults. Adherence depends on developing and implementing plans for taking medications. Age-related cognitive declines that affect adherence may be mitigated using external tools that support patient-provider collaboration needed to develop these adherence plans. We tested the effectiveness of structured collaborative medication tools to support better medication planning and adherence practices. Evidence for benefits of collaborative tools has been mixed in terms of their usefulness for medication-scheduling tasks, perhaps because the tools have not been explicitly designed to support patient-provider collaboration. A total of 144 community-dwelling older adults participated in pairs and performed the role of a patient or provider in a simulated patient-provider medication-scheduling task. Each pair worked with a structured (MedTable™ and e-MedTable) or unstructured (Medcard) scheduling tool and completed four problems (2 simple and 2 complex). Performance was measured using the following: problem-solving (medication schedule) accuracy, problem-solving time, solution (schedule) optimality, tool usability, collaborative effectiveness, and subjective workload involved in creating the medication schedules. Participants using structured tools produced more accurate and optimal schedules. They also rated subjective workload as lower and thought that the structured tools were easier to use, reduced subjective workload associated with creating the schedules. There was also suggestive evidence that participants using the structured tools rated more highly the quality of their collaboration. Structured medication-scheduling tools have the potential to improve medication adherence among older adults because they support collaborative planning and reduce the cognitive load involved in creating these adherence plans.

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Acknowledgments

We are grateful for the support from the UIUC Research Board and the National Institute of Nursing Research (R01 NR011300-01A1). We also thank Laura D’Andrea and Shreyans Ranka for their help in running the experiments. This study is part of the Kevin Waicekauskas’s Masters thesis completed at the University of Illinois, Urbana-Champaign. Partial results were presented at the 54th Annual Meeting of the Human Factors Society (Waicekauskas et al. 2010). This study was conducted when the first author was a visiting researcher at University of Illinois, Urbana-Champaign.

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Authors and Affiliations

  1. Center for Cognitive Informatics and Decision Making, School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, USA

    Thomas G. Kannampallil

  2. Department of Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Kevin Waicekauskas

  3. Department of Educational Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Daniel G. Morrow

  4. Human Factors Division, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Kathryn M. Kopren

  5. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Wai-Tat Fu

Authors
  1. Thomas G. Kannampallil
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  2. Kevin Waicekauskas
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  3. Daniel G. Morrow
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  4. Kathryn M. Kopren
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  5. Wai-Tat Fu
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Correspondence to Thomas G. Kannampallil.

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Kannampallil, T.G., Waicekauskas, K., Morrow, D.G. et al. External tools for collaborative medication scheduling. Cogn Tech Work 15, 121–131 (2013). https://doi.org/10.1007/s10111-011-0190-7

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  • DOI: https://doi.org/10.1007/s10111-011-0190-7

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