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D Timmermans

Publications and source records attributed to D Timmermans.

8 recordsLinked to original sources
PubMed2001

Improving the quality of surgeons' treatment decisions: a comparison of clinical decision making with a computerised evidence based decision analytical model.

OBJECTIVES: The purpose of this study is to demonstrate to what extent an evidence based decision model can improve physicians' decisions and whether a selective use of the decision model is feasible. METHODS: Four experienced vascular surgeons were asked to make a treatment decision for 137 "paper patient" cases with asymptomatic abdominal aneurysms. Their decisions were compared with the optimal treatment as calculated by a computerised evidence based decision analytical model. RESULTS: Surgeons agreed with the model's advice based on life expectancy in 81% of the cases, and decided to operate in only 12% of the cases for which there was no agreement. Surgeons' decisions differed from the decision model's calculated optimal treatment, in particular, for older patients with aneurysms of intermediate size and with many risk factors, and for younger patients with small aneurysms and few risk factors. Not all these decisions, however, were reported to be more difficult. CONCLUSION: Use of a decision analytical model might lead to more appropriate decisions and a better quality of care. Selective use of the decision tool for difficult decisions only would be more efficient but is not yet feasible because reported decision difficulty is not strongly related to disagreement with the decision tool.

Aged↗
PubMed1996

Effects on Decision Quality of Supporting Multi-attribute Evaluation in Groups

In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and were asked to reach a decision about the same problem. Groups received either MAU support or no support. Results show that for relatively simple problems the most effective method is to provide subjects with both individual and group decision support. Here, decision support had a clear impact on subjects' preferences and the level of agreement between group members. In addition, satisfaction with the decision and the decision procedure was relatively high. Overall, decision support improved communication; subjects reported to find the problem easier, to have more influence on the group decision, and to find it easier to express their opinions. For more complex problems, however, decision making without group support (whether preceded by individual support or not) was evaluated most favorably. Individual decision support in this condition was sometimes better than no support; i.e., there was a lower reported problem difficulty, a higher satisfaction with the group decision, and a higher reported influence on the group decision. The effectiveness of group MAU decision support for complex problems was evaluated less favorably.

Journal Article↗
PubMed1996

How do surgeons' probability estimates of operative mortality compare with a decision analytic model?

The aim of this study is to compare surgeons' estimates of operative mortality of patients with an abdominal aneurysm (= dilation of the aorta) with the operative mortality derived from a decision analytic model and to determine how surgeons use clinical information. Four experienced surgeons are asked to estimate, among other things, the operative mortality of 137 patients. Results concerning the accuracy of surgeons' estimates show that surgeons' average operative mortality estimates are quite accurate as compared to the calculated mortalities. The standard deviations of surgeons' estimates are lower than the standard deviation of the model, however, indicating that the surgeons are not as good in distinguishing the high and low risk patients. Furthermore, surgeons show substantial inconsistencies in the weighing of the clinical information, and also differ from the model in how clinical information is weighed. Finally, when comparing the operative mortalities of the patients who died and those who did not, the model shows a modest, but higher discrimination than the surgeons. Physicians' performance seems to be influenced by the difficulty of the task (i.e. the unpredictability of the event and the multidimensionality of the task). In order to improve physicians' probability estimates, the calculations of the decision model can be used as learning tool.

Aortic Aneurysm, Abdominal↗
PubMedDate not supplied

The roles of experience and domain of expertise in using numerical and verbal probability terms in medical decisions.

Verbal probability terms are frequently used in medical practice. In the present experiment the use of verbal and numerical probability terms in medical decisions was investigated. Interns, residents in surgery and internal medicine, surgeons, and internists were asked to make treatment decisions for three different cases (acute appendicitis, angina pectoris, and an imaginary disease) and were also asked to give numerical interpretations of a series of verbal probability terms. In the second stage of the experiment the respondents received the same cases, but with numerical probability terms. The results showed no effect of context or of domain experience on the interpretation of verbal terms. Residents and experienced surgeons more often agreed on treatment decisions when chance information was presented in numerical terms as compared with verbal terms. Physicians were less confident when verbal terms were presented, but only for the less familiar decision problems. Finally, physicians turned out to be better in Bayesian reasoning when numerical terms were used. Experienced physicians were quite accurate in estimating the posterior probability in the appendicitis case, but not in the imaginary-disease case.

Acute Disease↗