ArticleStudies in health technology and informatics2017
A User-Centered Glucose-Insulin Data Display for the Inpatient Setting.
Article in Studies in health technology and informatics, 2017. 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, 5 citations in OpenAlex.
- Novel Automated Self-adjusting Subcutaneous Insulin Algorithm Improves Glycemic Control and Physician Efficiency in Hospitalized Patients.Journal of diabetes science and technology · 2024Article
- Electronic Health Record-Based Decision-Making Support in Inpatient Diabetes Management.Current diabetes reports · 2022Review
- Closing the Loop: Optimizing Diabetes Care in the Hospital by Addressing Dispersed Information in Electronic Health Records and Using Clinical Decision Support.Journal of diabetes science and technology · 2019Article
- How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.Journal of diabetes science and technology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Inpatient management of insulin-dependent diabetes (IDD) is a complex task that requires clinicians to cognitively process information across distinct domains in different locations of the electronic medical record (EMR). Current data displays are not optimized to support insulin management by end users. We sought to develop a set of user-centered displays of capillary glucose data and insulin dose to improve inpatient management of IDD. Our proposed conceptual data display prototype is designed to simplify the presentation and visualization of key information needed for treatment decisions. The goal is also to enhance clinician's ability to identify opportunities to optimize insulin dosing and decrease end users' cognitive load and error rates.
Indexed as
Identifiers
29295184PMC5935245W2786512572What 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.