ArticleAJPM focus2024
Evaluation of a Diabetes Screening Clinical Decision Support Tool.
Article in AJPM focus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
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
Abstract
Introduction: The authors evaluated whether an electronic health record clinical decision support system improves diabetes screening across a health system. Methods: Study population included adults without diabetes attending a visit at 27 primary care clinics. Outcomes included the monthly screening laboratory order rate and completion rate among eligible patient visits. The authors performed logistic regression using a generalized estimating equations model and interrupted time series analysis to evaluate the change in the outcome from baseline to implementation and postimplementation periods. Results: From the baseline to postimplementation period, screening laboratory order rates increased from 53% to 66%, and completion rates increased from 46% to 54%, respectively. The odds of laboratory order and completion increased significantly from the baseline to postimplementation period (test order: OR=3.7; 95% CI=3.4, 4.1, Conclusions: The authors developed and implemented a clinical decision support system alert that automatically identifies eligible patients and facilitates single-click ordering of a diabetes screening test. An easily implementable and scalable clinical decision support system alert can improve diabetes screening.
Indexed as
Identifiers
What OpenQuestion holds
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.