Assessment of implementation of the malaria test, treat and track cascade in eight health facilities in Gulu district
Abstract
Background: Every suspected malaria case should be tested for the presence of the malaria
parasite, every confirmed case should be treated with antimalarial medicine, and every confirmed
case should be tracked through timely and accurate surveillance systems. However, weekly
epidemiological reports from health facilities in Gulu district showed that not all suspected malaria
cases are tested and when tested, some with negative test results are treated with antimalarials. In
some cases, even those not tested receive antimalarials.
Objective: To assess the implementation of the malaria Test, Treat and Track policy of testing all
suspected malaria cases, treatment of only confirmed malaria cases and tracking malaria cases with
a surveillance system in the health facilities in Gulu district.
Methods: This was a retrospective analysis and employed a mix of both quantitative and
qualitative methods. Quantitative data was collected by retrospective review of OPD register,
laboratory register, and DHIS-2 from eight health facilities in Gulu district for a period of one year.
Data was summarised monthly for 12 months and was compared monthly, by level of health
facility, and by health facility ownership. Categorical data was summarised in frequencies and
percentages. Differences between levels of categorical variables were explored using a chi-square
test. A p-valve of less 0.05 was considered cut off for statistical significance. The Bland-Altman
correlation analysis quantified the numerical consistency between the aggregated malaria cases in
OPD registers, laboratory registers, and DHIS2. Factors associated with the proportion of
suspected malaria cases tested and confirmed malaria cases treated for each independent variable
were assessed using logistic regression models in STATA 14.0. Qualitative data was collected
through key informant interviews with the District Health Officer, the health educator, the malaria
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focal person, health workers, and health facility in-charges, and malaria focal persons from
development partners. Transcripts from the key informant audio files were subjected to schematic
analysis.
Results: The proportion of suspected malaria cases that were tested for malaria was 99.8% and
the proportion of confirmed malaria cases that were treated with antimalarials was 99.9%. The
Bland-Altman correlation analysis showed a poor concordance correlation coefficient of 0.558
(95% CI: 0.319- 0.797) when the number of malaria cases recorded in OPD register were compared
with the number of malaria cases reported in DHIS2. Logistic regression showed a significant
statistical difference in the proportion of suspected malaria cases tested in public and private health
facilities (p<0.0001). There was a significant statistical difference in the proportion of confirmed
malaria cases treated with antimalarials across different levels of health facilities (p<0.016) and
when health facilities were disaggregated by their location (p<0.004). Barriers to implementation
of the malaria T3 policy include patient perception, limited malaria support supervision, shortage
of health care staff dedicated to data management and declining motivation. Enablers to
implementation of T3 policy include availability of antimalarials and diagnostic facilities like RDT
and microscopy, and an established surveillance system.
Conclusion and Recommendation: Substantial implementation was observed in testing and
treatment of malaria cases. However, malaria data used to track malaria cases is of poor quality.
To sustain the gains attained in the implementation of T3 policy, the ministry of health and malaria
development partners should ensure consistent and sustainable supply and access to all malaria
commodities. Regular support supervision visits and data quality audits should be conducted to
improve the quality of data for tracking malaria cases.