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Research on Teleconsultation service quality based on multi-granularity linguistic information: the perspective of regional doctors.

Authors :
Lu W
Wang XP
Zhao J
Zhai YK
Source :
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2020 Jun 18; Vol. 20 (1), pp. 113. Date of Electronic Publication: 2020 Jun 18.
Publication Year :
2020

Abstract

Background: Due to the increasing complexity in socioeconomic environments and the ambiguity in human cognition, decision makers prefer to give linguistic cognitive information with different granularities according to their own preferences. Consequently, to consider the uncertainty and preferences in the evaluation process, a method based on Multi-Granularity Linguistic Information (MGLI) for evaluating teleconsultation service quality is proposed, which provides a new research direction for scientific evaluation and improvement of teleconsultation service quality.<br />Methods: Firstly, this paper explored a service quality evaluation system from the perspective of regional doctors. And then considering the uncertainty and preferences of decision makers, MGLI was used to optimize the index system according to the similarity degree between the linguistic evaluation information and a given linguistic term set. Finally, the empirical research was conducted using Henan Province Telemedicine Center of China (HTCC) as an example to identify the direction for improving the service quality in teleconsultation.<br />Results: This study found that the number of consulting rooms, attitude of operators, consultation duration, charges, and attitude of experts are the key factors affecting the quality of teleconsultation service.<br />Conclusions: Suggestions for improving the quality of teleconsultation service are put forward in terms of optimizing the allocation of consulting rooms, improving regional doctors' experience and standardizing charging standards, which provides a new direction for improving the quality of teleconsultation service.

Details

Language :
English
ISSN :
1472-6947
Volume :
20
Issue :
1
Database :
MEDLINE
Journal :
BMC medical informatics and decision making
Publication Type :
Academic Journal
Accession number :
32552734
Full Text :
https://doi.org/10.1186/s12911-020-01155-5