Development and Validation of a Customer Satisfaction Measuring Instrument with Laboratory Services at the University Hospital of Kinshasa, Democratic Republic of the Congo (DRC)

Chabo Byaene Alain,Muwonga Masidi Jérémie,Mabela Makengo Matendo Rostin,Muhindo Mavoko Hypolite,Kayembe Nzongola-Nkasu Donatien,Konde Nkiama Numbi Joël,Tanon Aristophane Koffi,Situakibanza Nani-Tuma Hippolyte

doi:10.4236/ajibm.2021.115030

Abstract

In clinical laboratory, monitoring customers’ satisfaction is required by laboratory quality standards, such as ISO15189:2012 and ISO17025:2017. However, there is no reliable and valid scale to measure clinical laboratory customers’ satisfaction in DRC. This study aims to develop a theoretical and operational instrument for measuring customer satisfaction with clinical laboratory services. In order to develop a reliable and valid measurement tool, the general methodological approach recommended by Churchill was followed. The developed questionnaire was checked for reliability and validity using exploratory and confirmatory factor analyses. Structural Equation Modeling (SEM) was used to determine whether the hypothesis of the conceptual framework is acceptable in measuring customer satisfaction. The Principal Component Analysis (PCA) results showed a three-dimensionality of Customer Satisfaction. Cronbachs alpha coefficients (0.983, 0.981 and 0.981), Joreskog Rho (0.973, 0.970 and 0.967) and composite reliability values (0.95, 0.92 and 0.93) of the latent variables were greater than 0.9, which confirms the very high reliability of the model. Indicator loadings were all greater than the threshold of 0.7 or higher. Also, all the latent variables have average variance extracted (AVE) greater than 0.5, therefore, convergent validity has been achieved. Both the Maximum Shared Variance (0.195, 0.297 and 0.234) and the Average Shared Variance (0.805, 0.703 and 0.766) were lower than the AVE (0.897, 0.839 and 0.875) for all the constructs in the scale. Therefore, Discriminant validity has been achieved. Fit indices used to assess CFA and structural equation model were found to be at an acceptable level for the two- factor model where chi-square/df was 1.6, p = 0.476, GFI = 0.99, AGFI = 0.99, SRMR = 0.069, RMSEA < 0.001, CFI = 1, NFI = 0.98, RFI = 0.98, IFI = 0.98, TLI = 0.98. The instrument demonstrated acceptable psychometric properties and thus it fits for measuring customers’ satisfaction with laboratory services.

Highlights

In today’s competitive and technology driven world, organizations are starting to go back to the basics-single-minded focus on customers and service experience
Three factors in the initial solution have eigenvalues greater than 1. They account for almost 93.481% of the variability in the original variables or manifest variables. This suggests that three latent variables are associated with customer satisfaction
The third section of this table shows the variance explained by the extracted factors before rotation

Summary

Introduction

In today’s competitive and technology driven world, organizations are starting to go back to the basics-single-minded focus on customers and service experience. A high quality organization meets customer’s needs. Philip Crosby, one of the founding fathers of the quality movement, defined service quality as meeting the customer’s requirements (Crosby, 1989). The hospital market, which is a service industry, has today changed from a sellers’ market to a buyers’ market, where the customer is all important. Customer satisfaction is considered as one of the desired outcomes of health care and it is directly related to the utilization of health services (Bekele et al, 2008). A study done in South Africa concluded that customer satisfaction is a fundamental indicator of equitable quality of care (Myburgh et al, 2005)

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Discussion

Conclusion