Appl Clin Inform 2022; 13(01): 252-262
DOI: 10.1055/s-0042-1743237
State of the Art/Best Practice Paper

Opportunities and Challenges of Integrating Food Practice into Clinical Decision-Making

Mustafa Ozkaynak
1   College of Nursing, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, United States
,
Stephen Voida
2   Department of Information Science, University of Colorado Boulder, Boulder, Colorado, United States
,
Emily Dunn
1   College of Nursing, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, United States
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Abstract

Background Food practice plays an important role in health. Food practice data collected in daily living settings can inform clinical decisions. However, integrating such data into clinical decision-making is burdensome for both clinicians and patients, resulting in poor adherence and limited utilization. Automation offers benefits in this regard, minimizing this burden resulting in a better fit with a patient's daily living routines, and creating opportunities for better integration into clinical workflow. Although the literature on patient-generated health data (PGHD) can serve as a starting point for the automation of food practice data, more diverse characteristics of food practice data provide additional challenges.

Objectives We describe a series of steps for integrating food practices into clinical decision-making. These steps include the following: (1) sensing food practice; (2) capturing food practice data; (3) representing food practice; (4) reflecting the information to the patient; (5) incorporating data into the EHR; (6) presenting contextualized food practice information to clinicians; and (7) integrating food practice into clinical decision-making.

Methods We elaborate on automation opportunities and challenges in each step, providing a summary visualization of the flow of food practice-related data from daily living settings to clinical settings.

Results We propose four implications of automating food practice hereinafter. First, there are multiple ways of automating workflow related to food practice. Second, steps may occur in daily living and others in clinical settings. Food practice data and the necessary contextual information should be integrated into clinical decision-making to enable action. Third, as accuracy becomes important for food practice data, macrolevel data may have advantages over microlevel data in some situations. Fourth, relevant systems should be designed to eliminate disparities in leveraging food practice data.

Conclusion Our work confirms previously developed recommendations in the context of PGHD work and provides additional specificity on how these recommendations apply to food practice.

Keywords

clinical decision-making - workflow - food practice - clinical informatics - self-tracking

Protection of Human and Animal Subjects

No human and/or animal subjects were included.




Publication History

Received: 08 June 2021

Accepted: 03 January 2022

Article published online:
23 February 2022

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