Method for Selection of Laboratories in Need of Infrastructure Improvement to Meet HIV Viral Load and Early Infant Diagnosis Unmet Testing Needs in Kenya

Volume 11 - Issue 5

Leonard Kingwara*¹, Kipkerich Bera¹, Vincent Were², John Gituma³, Frank Onyambu⁵, Nancy Bowen¹, Emilia Fernandez⁴ and Dardane Arifaj Blumi⁴

Received: November 28, 2018;   Published: December 10, 2018

DOI: 10.26717/BJSTR.2018.11.002168

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Abstract

Introduction: Laboratory infrastructure remains an obstacle for meeting ISO 15189 requirements to assure functional quality management system essentials and competency to generate accurate results. With limited resources, it is challenging to select which facilities to upgrade from among many of similar needs. While common variables in laboratory systems are known, a model that uses these variables to identify priority laboratories for infrastructure upgrade in most resource limited setting is missing.

Methods: A quantitative and qualitative based questionnaire was used to collect specific indicators. Principal Component Analysis (PCA) type of factor analysis was then used to generate weights for each indicator. Composite indices were then obtained and used to group laboratories into four ranked clusters.

Results: Four clusters were generated in ranked order where the poorest performing facilities n=4, 21.1% were classified in cluster one. Of the 29 indicators the composite range score for the first five was 0.083-0.142. Absence of fire and smoke detectors had the least weight at -0.13. Among the 20 laboratories 9 had a negative factor weight.

Discussion: PCA method provides an opportunity to apply quantitative methods for generating weights that can be applied to select laboratories for infrastructure improvement.

Keywords :Principal Component Analysis; Malaria

Introduction| Methods| Data Analysis| Results| Discussion| Conclusion| References|