Trial reportThe lancet. HIV2016
Effect of a clinical decision support system on early action on immunological treatment failure in patients with HIV in Kenya: a cluster randomised controlled trial.
Trial report in The lancet. HIV, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Evaluation of Use of Clinical Decision Support System for Early Detection of Immunological Treatment Failure Among HIV Patients in Resource Constrained Settings
Evaluation of the Clinical Impacts and Costs of eHealth in Rwanda Using Innovative Frameworks and Local Capacity Building
Who cites it
16 citing papers in PubMed.
- A clinical decision support system is associated with reduced loss to follow-up among patients receiving HIV treatment in Kenya: a cluster randomized trial.BMC medical informatics and decision making · 2021Trial
- Implementation and Evaluation of a Real-Time Prescription Alert System to Optimize Antiretroviral Therapy and Medication Adherence in People Living with HIV. SANPAT PROJECT.Patient preference and adherence · 2025Article
- "Following the data": perceptions of and willingness to use clinical decision support tools to inform HIV care among Haitian clinicians.Health policy and technology · 2024Article
- Electronic Medical Record Data Missingness and Interruption in Antiretroviral Therapy Among Adults and Children Living With HIV in Haiti: Retrospective Longitudinal Study.JMIR pediatrics and parenting · 2024Article
- Harnessing the power of clinical decision support systems: challenges and opportunities.Open heart · 2023Review
- The Roles of Electronic Health Records for Clinical Trials in Low- and Middle-Income Countries: Scoping Review.JMIR medical informatics · 2023Article
- The Global Health Informatics landscape and JAMIA.Journal of the American Medical Informatics Association : JAMIA · 2023Review
- Implementing Electronic Health Records in Primary Care Using the Theory of Change: Nigerian Case Study.JMIR medical informatics · 2022Article
- User Perceptions and Use of an Enhanced Electronic Health Record in Rwanda With and Without Clinical Alerts: Cross-sectional Survey.JMIR medical informatics · 2022Article
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- Cluster-Randomized Test-Negative Design Trials: A Novel and Efficient Method to Assess the Efficacy of Community-Level Dengue Interventions.American journal of epidemiology · 2018Article
- Implementing an Open Source Electronic Health Record System in Kenyan Health Care Facilities: Case Study.JMIR medical informatics · 2018Article
- Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset.Journal of healthcare engineering · 2018Article
- The Internet of Things to come: digital technologies and the End TB Strategy.BMJ global health · 2016Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundA clinical decision support system (CDSS) is a computer program that applies a set of rules to data stored in electronic health records to offer actionable recommendations. We aimed to establish whether a CDSS that supports detection of immunological treatment failure among patients with HIV taking antiretroviral therapy (ART) would improve appropriate and timely action.
methodsWe did this prospective, cluster randomised controlled trial in adults and children (aged ≥18 months) who were eligible for, and receiving, ART at HIV clinics in Siaya County, western Kenya. Health facilities were randomly assigned (1:1), via block randomisation (block size of two) with a computer-generated random number sequence, to use electronic health records either alone (control) or with CDSS (intervention). Facilities were matched by type and by number of patients enrolled in HIV care. The primary outcome measure was the difference between groups in the proportion of patients who experienced immunological treatment failure and had a documented clinical action. We used generalised linear mixed models with random effects to analyse clustered data. This trial is registered with ClinicalTrials.gov, number NCT01634802.
findingsBetween Sept 1, 2012, and Jan 31, 2014, 13 clinics, comprising 41,062 patients, were randomly assigned to the control group (n=6) or the intervention group (n=7). Data collection at each site took 12 months. Among patients eligible for ART, 10,358 (99%) of 10,478 patients were receiving ART at control sites and 10,991 (99%) of 11,028 patients were receiving ART at intervention sites. Of these patients, 1125 (11%) in the control group and 1342 (12%) in the intervention group had immunological treatment failure, of whom 332 (30%) and 727 (54%), respectively, received appropriate action. The likelihood of clinicians taking appropriate action on treatment failure was higher with CDSS alerts than with no decision support system (adjusted odds ratio 3·18, 95% CI 1·02-9·87).
interpretationCDSS significantly improved the likelihood of appropriate and timely action on immunological treatment failure. We expect our findings will be generalisable to virological monitoring of patients with HIV receiving ART once countries implement the 2015 WHO recommendation to scale up viral load monitoring.
fundingUS President's Emergency Plan for AIDS Relief (PEPFAR), through the US Centers for Disease Control and Prevention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.