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A Decision Making Model for Performance Evaluation and Profit Sharing in a Diagnostic Laboratory Network
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  • Niloufar Ghafari Someh,
  • Mir Saman Pishvaee,
  • Seyed Jafar Sadjadi,
  • Roya Soltani
Niloufar Ghafari Someh
Islamic Azad University Science and Research Branch
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Mir Saman Pishvaee
Iran University of Science and Technology
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Seyed Jafar Sadjadi
Iran University of Science and Technology
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Roya Soltani
KHATAM University
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Peer review status:ACCEPTED

25 Nov 2019Submitted to Journal of Evaluation in Clinical Practice
29 Nov 2019Assigned to Editor
29 Nov 2019Submission Checks Completed
29 Nov 2019Editorial Decision: Accept

Abstract

Rationale, aims and objectives Creating networked business models is one of the innovative approaches that have the ability and potential for meeting market needs. The purpose of this study is to provide a decision making model for a fair profit sharing among the members of a diagnostic laboratory network while providing a distinctive value for the patients. Methods To identify the members of the network of laboratories, a suitable approach to calculate members’ efficiency scores is proposed. Then, the network members are classified into three groups based on their performance scores. The three groups help administrators identify eligible members, members who need to improve their performance in order to meet the minimum requirements, and members who do not qualify for admission to the network. Since the performance of the members should play a significant role in the fair profit sharing mechanism, the fair allocation of profits among network members is done by the use of Shapely’s value based on the efficiency scores of members. Results The results show that for such a fair mechanism, the efficiency and sample size (the number of samples (blood, urine) taken from the patients by the laboratories), as the two effective factors, have a decisive role in the share of profit of laboratory units of the network. In the Laboratory Services Network, members receive a number of samples according to their performance. As a result, the sample size received has a direct impact on the net income of each member. Conclusion In conclusion, it is evident that the use of Shapely value may help managers in the process of sharing profits among network members in a fair way, thereby improving network performance. In this way, incentive strategies may be created for the members of the network and long-term survival of the network may be achieved.