ArticleJAMIA open2025
Implementing system-wide digital medical interpretation: a framework for healthcare organizations.
Article in JAMIA open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Communication Barriers in Patient-Provider Interactions in Health Care: Scoping Review.Journal of medical Internet research · 2026Article
- Language barriers, mobility, and health equity: clinical risks, economic burden, and policy options for universal language access.International journal for equity in health · 2026Review
- Article
- Increasing Interpreter Use for Pediatric Cardiology Units: A Quality Improvement Initiative.Pediatric quality & safetyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study evaluates and enhances language access services for Limited English Proficiency (LEP) patients in a large urban health system by integrating interpreter services into the Electronic Health Record (EHR), aiming to reduce care disparities and improve the digital experience for both patients and clinicians. Materials and Methods: Using a descriptive evaluation approach, the project assessed barriers to interpreter service usage and developed solutions informed by stakeholder engagement. Emphasis was placed on interfacing the EHR with the vendor platform, using existing devices, tracking utilization, ensuring cost-effectiveness, and implementing the solution across multiple hospitals and outpatient settings. Results Discussion and Conclusion: After implementation, audio and video interpreter service use rose significantly, with calls increasing from an average of 9700 calls per month in 2022 to over 68 176 calls per month by the end of 2024. Over 14 000 clinicians used the service for more than 121 077 unique patients. Average waiting times for the top ten languages fell below 30 seconds, and user satisfaction was high, with an average interpreter rating of 4.9. Conclusion: The EHR-integrated interpreter service has improved language service access, reduced waiting times and enhanced user satisfaction, marking noteworthy progress in overcoming language barriers and potentially decreasing healthcare disparities for LEP populations. We plan to assess the impact on patient outcomes.
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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.