A Joint Commission International consultant selection methodology for hospitals by the fuzzy analytic hierarchy process. (14th July 2009)

• Record Type: Journal Article
• Authors: Cebeci, Ufuk
• Is Part Of: International journal of nuclear knowledge management. Volume 3:Number 3(2009)
• Page Start: 236
• Page End: 249
• Publication Date: 2009-07-14
• Subjects: analytical hierarchy process -- fuzzy AHP -- fuzzy numbers -- Joint Commission International -- JCI -- hospitals -- quality consultancy -- healthcare quality -- consultant selection; Nuclear energy -- Periodicals; Nuclear energy -- Management -- Periodicals; Nuclear industry -- Periodicals; Nuclear industry -- Management -- Periodicals; 333.792405
• Languages: English
• ISSNs: 1479-540X

Abstract

The Joint Commission International (JCI) is dedicated to improving the quality and safety of healthcare services. Currently, the largest certification body of healthcare organisations in the USA, the JCI surveys nearly 20, 000 healthcare programmes through a voluntary accreditation process. The JCI is a nonprofit organisation that continually improves the safety and quality of care in the international community through the provision of education and international accreditation. The JCI standard contains different subjects such as Prevention of Infection, Patient and Family Rights, Leadership, Facility Management and Safety. Clients do not always appreciate the differences among JCI consultants. This paper aims to provide an analytical tool to select the best JCI consultant to provide the utmost customer satisfaction. The clients of three Turkish JCI consultancy firms were interviewed, and the most important criteria taken into account by the clients while they were selecting their consultancy firms were determined by a designed questionnaire. The fuzzy Analytic Hierarchy Process (AHP) was applied to compare these consultancy firms. The means of the triangular fuzzy numbers produced by the customers and experts for each comparison were successfully used in pairwise comparison matrices.