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METHOD FOR SELECTING EXPERT GROUPS AND DETERMINING THE IMPORTANCE OF EXPERTS’ JUDGMENTS FOR THE PURPOSE OF MANAGERIAL DECISION-MAKING TASKS IN HEALTH SYSTEM
Business Administration and Management
METHOD FOR SELECTING EXPERT GROUPS AND DETERMINING THE IMPORTANCE OF EXPERTS’ JUDGMENTS FOR THE PURPOSE OF MANAGERIAL DECISION-MAKING TASKS IN HEALTH SYSTEM
Name and surname of author:
Ilya Ivlev, Peter Kneppo, Miroslav Barták
Year:
2015
Volume:
18
Issue:
2
Keywords:
Group decision making; expert; expert selection criteria; medical equipment; selfassessment; weighting factor
JEL clasification:
DOI (& full text):
Anotation:
This work aims to develop a methodology for determining the qualitative composition of an expert
group and the weighting factor regarding the importance of expert’s judgments for the purpose of
participating in decision-making. It is based on the expert’s overall work experience, experience
in solving tasks, level of education and scientific record, interest in solving the particular task, current position and awareness of how to solve the task. This study also considered the relevance of the expert’s knowledge and the overall self-evaluation concerning their total competence in solving the task. For the purpose of validating the methodology, 96 potential experts (physicians, biomedical engineers, radiological assistants, medical physicists, etc.) from 72 health facilities in the Czech Republic were interviewed through a web-based questionnaire. The calculation model that was selected was able to eliminate errors in estimating the proportionality of extreme values and reduces the impact of uncertainty in the experts’ overall self-evaluations concerning their total competence. A statistically significant correlation was found between the complex weighting factor and the following characteristics: the expert’s experience in dealing with similar tasks (r = 0.512, p < 0.001), the expert’s theoretical background (awareness) and the relevance of the expert’s knowledge (r = 0.440, p < 0.001), the expert’s current position (r = 0.319, p = 0.002) and the level of his or her education and scientific record (r = 0.280, p = 0.007). The developed methodology may be especially useful in scientific and technological forecasting, medical and managerial decisionmaking, quality assessment and operational research.
This work aims to develop a methodology for determining the qualitative composition of an expert
group and the weighting factor regarding the importance of expert’s judgments for the purpose of
participating in decision-making. It is based on the expert’s overall work experience, experience
in solving tasks, level of education and scientific record, interest in solving the particular task, current position and awareness of how to solve the task. This study also considered the relevance of the expert’s knowledge and the overall self-evaluation concerning their total competence in solving the task. For the purpose of validating the methodology, 96 potential experts (physicians, biomedical engineers, radiological assistants, medical physicists, etc.) from 72 health facilities in the Czech Republic were interviewed through a web-based questionnaire. The calculation model that was selected was able to eliminate errors in estimating the proportionality of extreme values and reduces the impact of uncertainty in the experts’ overall self-evaluations concerning their total competence. A statistically significant correlation was found between the complex weighting factor and the following characteristics: the expert’s experience in dealing with similar tasks (r = 0.512, p < 0.001), the expert’s theoretical background (awareness) and the relevance of the expert’s knowledge (r = 0.440, p < 0.001), the expert’s current position (r = 0.319, p = 0.002) and the level of his or her education and scientific record (r = 0.280, p = 0.007). The developed methodology may be especially useful in scientific and technological forecasting, medical and managerial decisionmaking, quality assessment and operational research.
group and the weighting factor regarding the importance of expert’s judgments for the purpose of
participating in decision-making. It is based on the expert’s overall work experience, experience
in solving tasks, level of education and scientific record, interest in solving the particular task, current position and awareness of how to solve the task. This study also considered the relevance of the expert’s knowledge and the overall self-evaluation concerning their total competence in solving the task. For the purpose of validating the methodology, 96 potential experts (physicians, biomedical engineers, radiological assistants, medical physicists, etc.) from 72 health facilities in the Czech Republic were interviewed through a web-based questionnaire. The calculation model that was selected was able to eliminate errors in estimating the proportionality of extreme values and reduces the impact of uncertainty in the experts’ overall self-evaluations concerning their total competence. A statistically significant correlation was found between the complex weighting factor and the following characteristics: the expert’s experience in dealing with similar tasks (r = 0.512, p < 0.001), the expert’s theoretical background (awareness) and the relevance of the expert’s knowledge (r = 0.440, p < 0.001), the expert’s current position (r = 0.319, p = 0.002) and the level of his or her education and scientific record (r = 0.280, p = 0.007). The developed methodology may be especially useful in scientific and technological forecasting, medical and managerial decisionmaking, quality assessment and operational research.
Section:
Business Administration and Management
Economics and Management
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