BAIT: A New Medical Decision Support Technology Based on Discrete Choice Theory

Annebel ten Broeke, Jan Hulscher, Nicolaas Heyning, Elisabeth Kooi and Caspar Chorus
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Annebel ten Broeke: Councyl, Delft, Netherlands
Jan Hulscher: Department of Surgery, Division of Pediatric Surgery, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
Nicolaas Heyning: Councyl, Delft, Netherlands
Elisabeth Kooi: University of Groningen, University Medical Center Groningen, Beatrix Kinder Ziekenhuis, Division of Neonatology, Groningen, Netherlands
Caspar Chorus: Councyl, Delft, Netherlands

Medical Decision Making, 2021, vol. 41, issue 5, 614-619

Abstract: We present a novel way to codify medical expertise and to make it available to support medical decision making. Our approach is based on econometric techniques (known as conjoint analysis or discrete choice theory) developed to analyze and forecast consumer or patient behavior; we reconceptualize these techniques and put them to use to generate an explainable, tractable decision support system for medical experts. The approach works as follows: using choice experiments containing systematically composed hypothetical choice scenarios, we collect a set of expert decisions. Then we use those decisions to estimate the weights that experts implicitly assign to various decision factors. The resulting choice model is able to generate a probabilistic assessment for real-life decision situations, in combination with an explanation of which factors led to the assessment. The approach has several advantages, but also potential limitations, compared to rule-based methods and machine learning techniques. We illustrate the choice model approach to support medical decision making by applying it in the context of the difficult choice to proceed to surgery v. comfort care for a critically ill neonate.

Keywords: decision aids; decision models; decision support systems; decision support techniques; end-of-life decision; necrotizing enterocolitis (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:41:y:2021:i:5:p:614-619

DOI: 10.1177/0272989X211001320

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