Using quality improvement to improve the utilisation of GeneXpert testing at five lab hubs in Northern Uganda

Tuberculosis (TB) continues to be a major public health problem, with an estimated 10.4 million new (incident) TB cases worldwide each year. Case notification for TB in the 16 districts in Northern Uganda is 134 cases/100 000 population, well below the national target of 161/100 000.3 Improved TB diagnostics in this region is critical to attain timely case detection and management of TB, and reduce mortality, transmission and prevalence of the disease. In rural and low-resource health care settings like Northern Uganda, the GeneXpert machine is the preferred method of TB case diagnosis because it requires less expertise than X-ray diagnosis, is more sensitive than microscopy, and can detect multidrug-resistant TB.

With the aim of increasing the number of GeneXpert samples processed, ASSIST began working to improve GeneXpert services at five laboratory hubs in the Northern Uganda region in March 2016. All five GeneXpert machines were capable of running up to four samples every 2 hours, yet weekly data showed that about five samples were being run each day. In all, only 91 samples had been processed per month using GeneXpert machines instead of a maximum of about 1600 samples per month with eight working hours per day; hence, an underutilization of the machines.

Scaling up the use of GeneXpert in the region did not require increasing the number of machines procured and installed, but rather using the current machines to their optimal capacity; therefore, improvement teams at these facilities began working on this aim between March and August 2016. Following the implementation of changes to improve utilization of the machines, the teams achieved an increase in the number of samples processed from 91 to 448, and the number of identified TB-positives from 19 to 76 in the five sites.

Read the full article.

Report Author(s): 
Esther Karamagi, Joseph Nturo, Pamela Donggo, Isabel Kyobutungi, Judith Aloyo, Simon Sensalire, and Mirwais Rahimzai
USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project/URC
ASSIST publication: 
Facebook icon
Twitter icon
LinkedIn icon
e-mail icon