The performance of digital technologies for measuring tuberculosis medication adherence: a systematic review

Digital adherence technologies (DATs), such as phone-based technologies and digital pillboxes, can provide more person-centric approaches to support tuberculosis (TB) treatment. However, there are varying estimates of their performance for measuring medication adherence.

We conducted a systematic review (PROSPERO-CRD42022313526), which identified relevant published literature and preprints from January 2000 to April 2023 in five databases. Studies reporting quantitative data on the performance of DATs for measuring TB medication adherence against a reference standard, with at least 20 participants, were included. Study characteristics and performance outcomes (eg, sensitivity, specificity and predictive values) were extracted. Sensitivity was the proportion correctly classified as adherent by the DAT, among persons deemed adherent by a reference standard. Specificity was the proportion correctly classified as non-adherent by the DAT, among those deemed non-adherent by a reference standard.

Of 5692 studies identified by our systematic search, 13 met inclusion criteria. These studies investigated medication sleeves with phone calls (branded as '99DOTS'; N=4), digital pillboxes N=5), ingestible sensors (N=2), artificial intelligence-based video-observed therapy (N=1) and multifunctional mobile applications (N=1). All but one involved persons with TB disease. For medication sleeves with phone calls, compared with urine testing, reported sensitivity and specificity were 70%-94% and 0%-61%, respectively. For digital pillboxes, compared with pill counts, reported sensitivity and specificity were 25%-99% and 69%-100%, respectively. For ingestible sensors, the sensitivity of dose detection was ≥95% compared with direct observation. Participant selection was the most frequent potential source of bias.

The limited number of studies available suggests suboptimal and variable performance of DATs for dose monitoring, with significant evidence gaps, notably in real-world programmatic settings. Future research should aim to improve understanding of the relationships of specific technologies, settings and user engagement with DAT performance and should measure and report performance in a more standardised manner.