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CC BY-NC-ND 4.0 · ACI open 2022; 06(02): e114-e122
DOI: 10.1055/s-0042-1758462
Original Article

Power of Heuristics to Improve Health Information Technology System Design

Don Roosan
1   Department of Pharmacy Practice and Administration, Western University of Health Sciences, Pomona, California, United States
,
Justin Clutter
2   Division of Internal Medicine, Deaconess Health System, Evansville, Indiana, United States
,
Brian Kendall
3   Division of Infectious Diseases, Providence Milwaukie Hospital, Portland, Oregon, United States
,
Charlene Weir
4   Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States
› Author Affiliations Funding This project was supported by a grant (R36HS023349) from the Agency of Healthcare Research and Quality (AHRQ).
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Abstract

Background Clinical decision-making can be prone to error if health system design does not match expert clinicians' higher cognitive skills. There is a gap in understanding the need for the importance of heuristics in clinical decision-making. The heuristic approach can provide cognitive support in designing intuitive health information systems for complex cases.

Objective We explored complex decision-making by infectious diseases (ID) clinicians focusing on fast and frugal heuristics. We hypothesized that ID clinicians use simple heuristics to understand complex cases using their experience.

Methods The study utilized cognitive task analysis and heuristics-based decision modeling. We conducted cognitive interviews and provided clinicians with a fast-and-frugal tree algorithm to convert complex information into simple decision algorithms. We conducted a critical decision method–based analysis to generate if–then logic sentences from the transcript. We conducted a thematic analysis of heuristics and calculated the average time to complete and the number of crucial information in the decision nodes.

Results A total of 27 if–then logic heuristics sentences were generated from analyzing the data. The average time to construct the fast-and-frugal trees was 1.65 ± 0.37 minutes, and the average number of crucial pieces of information clinicians focused on was 5.4 ± 3.1.

Conclusion Clinicians use shortcut mental models to reduce complex cases into simple mental model algorithms. The innovative use of artificial intelligence could allow clinical decision support systems to focus on creative and intuitive interface design matching the higher cognitive skills of expert clinicians.

Keywords

clinical decision support - heuristics - data processing - expert system - algorithm

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the University of Utah Institutional Review Board.


Author Contributions

All the authors contributed to the conception of the work, surveying participants, data curation, and drafting the paper.




Publication History

Received: 22 September 2021

Accepted: 20 September 2022

Article published online:
09 December 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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