| dc.description.abstract | Background: Surveillance data are essential for malaria control, but quality is often poor. The aim of the study was
to evaluate the efectiveness of the novel combination of training plus an innovative quality improvement method—
collaborative improvement (CI)—on the quality of malaria surveillance data in Uganda.
Methods: The intervention (training plus CI, or TCI), including brief in-service training and CI, was delivered in 5
health facilities (HFs) in Kayunga District from November 2015 to August 2016. HF teams monitored data quality, con‑
ducted plan-do-study-act cycles to test changes, attended periodic learning sessions, and received CI coaching. An
independent evaluation was conducted to assess data completeness, accuracy, and timeliness. Using an interrupted
time series design without a separate control group, data were abstracted from 156,707 outpatient department (OPD)
records, laboratory registers, and aggregated monthly reports (MR) for 4 time periods: baseline—12 months, TCI scaleup—5 months; CI implementation—9 months; post-intervention—4 months. Monthly OPD register completeness
was measured as the proportion of patient records with a malaria diagnosis with: (1) all data felds completed, and (2)
all clinically-relevant felds completed. Accuracy was the relative diference between: (1) number of monthly malaria
patients reported in OPD register versus MR, and (2) proportion of positive malaria tests reported in the laboratory
register versus MR. Data were analysed with segmented linear regression modelling.
Results: Data completeness increased substantially following TCI. Compared to baseline, all-feld completeness
increased by 60.1%-points (95% confdence interval [CI]: 46.9–73.2%) at mid-point, and clinically-relevant complete‑
ness increased by 61.6%-points (95% CI: 56.6–66.7%). A relative − 57.4%-point (95% confdence interval: − 105.5,
− 9.3%) change, indicating an improvement in accuracy of malaria test positivity reporting, but no efect on data accuracy for monthly malaria patients, were observed. Cost per additional malaria patient, for whom complete
clinically-relevant data were recorded in the OPD register, was $3.53 (95% confdence interval: $3.03, $4.15).
Conclusions: TCI improved malaria surveillance completeness considerably, with limited impact on accuracy.
Although these results are promising, the intervention’s efectiveness should be evaluated in more HFs, with longer
follow-up, ideally in a randomized trial, before recommending CI for wide-scale use.
Keywords: Collaborative improvement, Quality improvement, Malaria, Surveillance, Uganda, Data quality | en_US |
