TY - JOUR
T1 - Psychological cue use and implications for a clinical decision support system
AU - Buckingham, Christopher
PY - 2002/12
Y1 - 2002/12
N2 - Effective clinical decision making depends upon identifying possible outcomes for a patient, selecting relevant cues, and processing the cues to arrive at accurate judgements of each outcome's probability of occurrence. These activities can be considered as classification tasks. This paper describes a new model of psychological classification that explains how people use cues to determine class or outcome likelihoods. It proposes that clinicians respond to conditional probabilities of outcomes given cues and that these probabilities compete with each other for influence on classification. The model explains why people appear to respond to base rates inappropriately, thereby overestimating the occurrence of rare categories, and a clinical example is provided for predicting suicide risk. The model makes an effective representation for expert clinical judgements and its psychological validity enables it to generate explanations in a form that is comprehensible to clinicians. It is a strong candidate for incorporation within a decision support system for mental-health risk assessment, where it can link with statistical and pattern recognition tools applied to a database of patients. The symbiotic combination of empirical evidence and clinical expertise can provide an important web-based resource for risk assessment, including multi-disciplinary education and training.
AB - Effective clinical decision making depends upon identifying possible outcomes for a patient, selecting relevant cues, and processing the cues to arrive at accurate judgements of each outcome's probability of occurrence. These activities can be considered as classification tasks. This paper describes a new model of psychological classification that explains how people use cues to determine class or outcome likelihoods. It proposes that clinicians respond to conditional probabilities of outcomes given cues and that these probabilities compete with each other for influence on classification. The model explains why people appear to respond to base rates inappropriately, thereby overestimating the occurrence of rare categories, and a clinical example is provided for predicting suicide risk. The model makes an effective representation for expert clinical judgements and its psychological validity enables it to generate explanations in a form that is comprehensible to clinicians. It is a strong candidate for incorporation within a decision support system for mental-health risk assessment, where it can link with statistical and pattern recognition tools applied to a database of patients. The symbiotic combination of empirical evidence and clinical expertise can provide an important web-based resource for risk assessment, including multi-disciplinary education and training.
KW - base-rates
KW - classification
KW - clinical decision support systems
KW - cues
KW - mental health
KW - risk assessment
UR - http://www.scopus.com/inward/record.url?scp=84860420872&partnerID=8YFLogxK
UR - http://informahealthcare.com/doi/abs/10.1080/1463923031000063342
U2 - 10.1080/1463923031000063342
DO - 10.1080/1463923031000063342
M3 - Article
AN - SCOPUS:84860420872
SN - 1463-9238
VL - 27
SP - 237
EP - 251
JO - Medical Informatics and the Internet in Medicine
JF - Medical Informatics and the Internet in Medicine
IS - 4
ER -