Medicine in words and numbers: a cross-sectional survey comparing probability assessment scales

Contains fulltext : 56355.pdf ( ) (Open Access)Background / In the complex domain of medical decision making, reasoning under uncertainty can benefit from supporting tools. Automated decision support tools often build upon mathematical models, such as Bayesian networks. These networks require probabilities which often have to be assessed by experts in the domain of application. Probability response scales can be used to support the assessment process. We compare assessments obtained with different types of response scale. Methods / General practitioners (GPs) gave assessments on and preferences for three different probability response scales: a numerical scale, a scale with only verbal labels, and a combined verbal-numerical scale we had designed ourselves. Standard analyses of variance were performed. Results / No differences in assessments over the three response scales were found. Preferences for type of scale differed: the less experienced GPs preferred the verbal scale, the most experienced preferred the numerical scale, with the groups in between having a preference for the combined verbal-numerical scale. Conclusion / We conclude that all three response scales are equally suitable for supporting probability assessment. The combined verbal-numerical scale is a good choice for aiding the process, since it offers numerical labels to those who prefer numbers and verbal labels to those who prefer words, and accommodates both more and less experienced professionals.8 p

Scope and nature of prescribing decisions made by general practitioners

Background: This study describes cognitive processes of doctors who are deciding on the treatment for a patient. This helps to uncover how prescribing decisions could benefit from (computerised) support. Methods: While thinking aloud, 61 general practitioners made prescribing decisions for five patients with urinary tract infections or stomach complaints. The resulting 305 transcripts were analysed to determine the scope and nature of the decision processes. Differences in the process were related to case or doctor characteristics, and to differences in the quality of prescribing behaviour. Results: The decision processes were not extensive, particularly for patients with a urinary tract infection. The doctors did not actively consider all possible relevant information. Considerations referring to core aspects of the treatment were made in 159 cases (52%) and to contextual aspects in 111 cases (36%). Habitual behaviour, defined as making a treatment decision without any specific contemplation, was observed in 118 cases (40%) and resulted in prescribing first choice as well as second choice drugs. For stomach complaints, second choice drugs were often prescribed after considering other treatments or in view of specific circumstances. Experience of the doctor was not related to the type of decision process. Conclusions: The processes observed deviate from the decision theoretic norm of thoroughly evaluating all possible options, but these deviations do not always result in suboptimal prescribing. Decision support is useful for bringing pertinent information and first choice treatments to the prescriber's attention. In particular, information about relevant contra indications, interactions, and costs could improve the quality of prescribing

Decision-making in child welfare in The Neterlands

In J. Davidson, & A. Kendrick (Eds.), All our children: Positive experinces, successful outcomes for looked after chilren and other vulnerable children. Abstract book (p199). Glasgow, UK: CELCI

Decision-making in child welfare in The Neterlands

In J. Davidson, & A. Kendrick (Eds.), All our children: Positive experinces, successful outcomes for looked after chilren and other vulnerable children. Abstract book (p199). Glasgow, UK: CELCI