Cost and Cost-Effectiveness of Digital Technologies for Support of Tuberculosis Treatment Adherence: A Systematic Review
Bibliographic record
Abstract
ABSTRACT Background Digital adherence technologies (DATs) may provide a patient-centered approach for supporting tuberculosis (TB) medication adherence and improving treatment outcomes. We synthesized evidence addressing costs and cost-effectiveness of DATs to support TB treatment. Methods A systematic review (PROSPERO-CRD42022313531) identified relevant literature from January 2000-April 2023 in MEDLINE, Embase, CENTRAL, CINAHL, Web of Science along with preprints from medRxiv, Europe PMC and clinicaltrials.gov. Studies with observational, experimental, or quasi-experimental designs (minimum 20 participants) and modelling studies reporting quantitative data on the cost or cost-effectiveness of DATs for TB infection or disease treatment were included. Study characteristics, cost and cost-effectiveness outcomes were extracted. Results Of 3,619 titles identified by our systematic search, 29 studies met inclusion criteria, of which 9 addressed cost-effectiveness. DATs included SMS reminders, phone-based technologies, digital pillboxes, ingestible sensors, and video observed treatment (VOT). VOT was the most extensively studied (16 studies) and was generally cost saving when compared to healthcare provider directly observed therapy (DOT), particularly when costs to patients were included--though findings were largely from high-income countries. Cost-effectiveness findings were highly variable, ranging from no clinical effect in one study (SMS), to greater effectiveness with concurrent cost savings (VOT) in others. Only 8 studies adequately reported at least 80% of the elements required by CHEERS, a standard reporting checklist for health economic evaluations. Conclusion DATs may be cost-saving or cost-effective compared to healthcare provider DOT, particularly in high-income settings. However, more data of higher quality are needed, notably in lower- and middle-income countries which have the greatest TB burden. KEY MESSAGES What is already known on this topic Digital adherence technologies (DATs) can provide a less intrusive, and potentially less resource-intensive way to monitor and support tuberculosis treatment adherence, as compared to traditional direct observation. To date, there is limited information about the cost and cost-effectiveness of these technologies in diverse care settings. What this study adds Our comprehensive review of available studies shows that some DATs like video-observed therapy can be cost-saving, particularly in higher-income countries, and especially when patient costs are considered. How this study might affect research, practice or policy While program savings related to some DATS will likely offset their initial costs in higher-income settings, more evidence is needed from lower-income settings where the TB burden is highest. Costing studies should also more rigorously account for all relevant costs, including those to patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".