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Published on: September 28, 2021
Serious Fungal Diseases: Assessing the Impact of Training Clinicians and Laboratory Scientists in Nigeria
Rita Oladele1, Damilola Akinlawon2, Alexander Jordan3
1Department of Medical Microbiology and Parasitology, College of Medicine, University of Lagos, Lagos, Nigeria.
Background:
Surveillance for serious fungal diseases (SFDs) relies on the capacity to recognize them and request and accurately perform diagnostic investigations. However, knowledge in resource-limited settings is suboptimal. This study evaluated the impact of a training intervention on the diagnosis and management of SFDs among clinicians and laboratory scientists in Nigerian tertiary hospitals.
Methods:
Clinicians in 6 hospitals were purposively selected and trained in 6 SFDs using standardized modules developed by international medical mycology experts. A quasi-experimental design assessed performance using a pretest and posttest. Designated laboratory scientists received hands-on training with pretraining and posttraining assessments. Paired t tests were used to assess differences in mean scores. An impact assessment of the laboratory mycology records was performed 1 year after intervention using analysis of variance.
Results:
A total of 149 clinicians and 8 laboratory scientists participated. Mean performance scores of participants improved significantly after training, with the following percentage increases: invasive aspergillosis (25.4%), chronic pulmonary aspergillosis (13.0%), invasive candidiasis (23.8%), Pneumocystis pneumonia (22.6%), mucormycosis (29.5%), and histoplasmosis (20.6%) (all P < .001). There was also a significant improvement in the laboratory scientists' posttraining performance (59.1%; P < .001). The laboratory mycology records reviewed 1 year later indicated a significant increase in the number of samples sent to the laboratory for mycological testing (P < .001) and the number and distribution of fungal isolates identified (P < .001).
Conclusions:
Training significantly improved SFD diagnosis and enhanced surveillance and patient care. Expanding this model across other low-resource settings is recommended.
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