Background: In China, an indigenously developed electronic medication monitor (EMM) was designed and used in 138 counties from three provinces. Previous studies showed positive results on accuracy, effectiveness, acceptability, and feasibility, but also found some ineffective implementations. In this paper, we assessed the effect of implementation of EMMs on treatment outcomes.
Methods: The longitudinal ecological method was used at the county level with aggregate secondary programmatic data. All the notified TB cases in 138 counties were involved in this study from April 2017 to June 2019, and rifampicin-resistant cases were excluded. We fitted a multilevel model to assess the relative change in the quarterly treatment success rate with increasing quarterly EMM coverage rate, in which a mixed effects maximum likelihood regression using random intercept model was applied, by adjusting for seasonal trends, population size, sociodemographic and clinical characteristics, and clustering within counties.
Results: Among all 69 678 notified TB cases, the treatment success rate was slightly increased from 93.5% [95% confidence interval (CI): 93.0-94.0] in second quarter of 2018 to 94.9% (95% CI: 94.4-95.4) in second quarter of 2019 after implementing EMMs. There was a statistically significant effect between quarterly EMM coverage and treatment success rate after adjusting for potential confounders (P = 0.0036), increasing 10% of EMM coverage rate will lead to 0.2% treatment success rate augment. Besides, an increase of 10% of elderly or bacteriologically confirmed TB will lead to a decrease of 0.4% and 0.9% of the treatment success rate.
Conclusions: Under programmatic settings, we found a statistically significant effect between increasing coverage of EMM and treatment success rate at the county level. More prospective studies are needed to confirm the effect of using EMM on TB treatment outcomes. We suggest performing operational research on EMMs that provides real-time data under programmatic conditions in the future.
Keywords: Digital technology; Longitudinal study; Medication monitoring; Treatment outcome; Tuberculosis.