Cost-effectiveness of artificial intelligence monitoring for active tuberculosis treatment: A modeling study
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Background: Tuberculosis (TB) incidence in Los Angeles County, California, USA (5.7 per 100,000) is significantly higher than the U.S. national average (2.9 per 100,000). Directly observed therapy (DOT) is the preferred strategy for active TB treatment but requires substantial resources. We partnered with the Los Angeles County Department of Public Health (LACDPH) to evaluate the cost-effectiveness of AiCure, an artificial intelligence (AI) platform that allows for automated treatment monitoring. Methods: We used a Markov model to compare DOT versus AiCure for active TB treatment in LA County. Each cohort transitioned between health states at rates estimated using data from a pilot study for AiCure (N = 43) and comparable historical controls for DOT (N = 71). We estimated total costs (2017, USD) and quality-adjusted life years (QALYs) over a 16-month horizon to calculate the incremental cost-effectiveness ratio (ICER) and net monetary benefits (NMB) of AiCure. To assess robustness, we conducted deterministic (DSA) and probabilistic sensitivity analyses (PSA). Results: For the average patient, AiCure was dominant over DOT. DOT treatment cost $4,894 and generated 1.03 QALYs over 16-months. AiCure treatment cost $2,668 for 1.05 QALYs. At willingness-to-pay threshold of $150K/QALY, incremental NMB per-patient under AiCure was $4,973. In univariate DSA, NMB were most sensitive to monthly doses and vocational nurse wage; however, AiCure remained dominant. In PSA, AiCure was dominant in 93.5% of 10,000 simulations (cost-effective in 96.4%). Conclusions: AiCure for treatment of active TB is cost-effective for patients in LA County, California. Increased use of AI platforms in other jurisdictions could facilitate the CDC’s vision of TB elimination.
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Salcedo et al. found that AiCure was cost-saving in 96.4% of simulations at a $150,000/QALY threshold.
“Salcedo et al.30 found that AiCure was cost-saving in 96.4% of simulations at a $150,000/QALY threshold.”
From Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare (2025) · cites this paper as Salcedo et al.30
The Results report that AiCure was cost-effective in 96.4% of simulations at a $150,000/QALY threshold. They separately report that it produced more QALYs at a lower cost than DOT in 93.5% of simulations. The claim conflates cost-effectiveness with cost savings. (LLM, conf=0.94)
Experimental — accuracy not yet measuredSalcedo et al. demonstrated AI dominance in TB monitoring, with cost savings of $2226 per patient and slightly higher QALYs (1.05 vs. 1.03).
“Salcedo et al.30 demonstrated AI dominance in TB monitoring, with cost savings of $2226 per patient and slightly higher QALYs (1.05 vs. 1.03).”
From Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare (2025) · cites this paper as Salcedo et al.30
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Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare
El Arab, R. A., & Al Moosa, O. A. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01722-y · Cited by 149 · see citing works
- Authors
- Salcedo, J., Rosales, M., Kim, J. S., Nuno, D., Suen, S.-C., & Chang, A. H.
- Affiliations
- University of Southern California (US)
- Los Angeles County Department of Public Health (US)
- Corresponding author
- Suen, Sze-chuan
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2021-07-21
- Volume
- 16
- Issue
- 7
- Pages
- e0254950
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC8294556
- OpenAlex
- W3184936058
- Cited by
- 41
- References
- 2
- Citations by year
- 2026: 8 · 2025: 12 · 2024: 11 · 2023: 8 · 2022: 2
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- creativecommons.org/publicdomain/zero/1.0/ (vor)
- Locations
- PLoS ONE (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- los angeles county quality and productivity commission
- Topics
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- active tuberculosis, AI monitoring, directly observed therapy, cost-effectiveness, quality-adjusted life years, tuberculosis elimination, Los Angeles County, public health resource allocation
- MeSH terms
- Adult, Aged, Artificial Intelligence, California, Cost-Benefit Analysis, Female, Humans, Male, Middle Aged, Monitoring, Physiologic, Pilot Projects, Tuberculosis
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