Analyze the healthcare service requirement using fuzzy QFD
•A fuzzy QFD methodology to analyze healthcare service requirement is proposed.•A methodology helps understand customer's requirements for service improvement.•The methodology was trial implemented into the healthcare services in Singapore.•39 fuzzy rules and new insights in healthcare service...
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Published in: | Computers in industry Vol. 74; pp. 1 - 15 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Amsterdam
Elsevier B.V
01-12-2015
Elsevier Sequoia S.A |
Subjects: | |
Online Access: | Get full text |
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Summary: | •A fuzzy QFD methodology to analyze healthcare service requirement is proposed.•A methodology helps understand customer's requirements for service improvement.•The methodology was trial implemented into the healthcare services in Singapore.•39 fuzzy rules and new insights in healthcare service improvement are provided.
Research on the adoption of fuzzy logic in healthcare diagnostic system to oversee the process performance and recognize certain predefined patterns has been conducted for associating the well-known problems using the rule-based approach technique. Even though a couple of medical applications such as those described above had shown generally proven results, the literature regarding applying fuzzy logic in healthcare delivery remains modest and the application of fuzzy logic to healthcare services had been rare. Applying fuzzy logic in healthcare services is still a mostly untapped region, especially collecting the voice of customer. Coupled fuzzy logic with QFD in healthcare services enables medical practitioners to understand customer requirements and include them for continuous improvement during the health service delivery. A fuzzy QFD approach for analyzing healthcare service requirement is proposed and realized through a case study. It is realized that the proposed approach can adjust service quality toward customer requirements. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0166-3615 1872-6194 |
DOI: | 10.1016/j.compind.2015.08.005 |