ArticleFrontiers in clinical diabetes and healthcare2025
Comparing glucose monitoring methods: efficiency insights in a simulated hospital setting.
Article in Frontiers in clinical diabetes and healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
While the advantages of flash glucose monitoring, also known as dynamic interstitial glucose monitoring (DIGM), are established in outpatient diabetes care, evidence of its impact within hospital settings remains limited. This study compared the efficiency of use and healthcare staff perception of DIGM monitoring versus traditional finger-prick testing in a simulated hospital environment. Twenty-five healthcare professionals (52% nurses, 48% allied healthcare professionals [AHCPs]) participated in simulated clinical scenarios involving glucose monitoring tasks using a high-fidelity mannequin. Participants performed three tasks: (A) applying a flash sensor, (B) scanning the sensor to obtain a glucose reading, and (C) performing a finger-prick test. Task durations and staff perceptions were assessed, with statistical analyses conducted using Python (version 3). DIGM was significantly faster than finger-prick testing. Sensor application took 75.4 ± 22.4 seconds, flash scanning took 26.4 ± 11.5 seconds, and finger-prick testing required 132.8 ± 37 seconds (p < 0.05 for all comparisons). DIGM saved approximately 106 seconds per glucose check based on these timings. Furthermore, a scenario of 20 readings per hospitalized patient translates to an average of 34.2 minutes saved per patient. While staff with greater experience performed tasks slightly faster, the overall time-saving benefit of DIGM remained substantial across all levels of experience. In addition, survey responses revealed a strong staff preference for DIGM, highlighting perceived benefits in workflow efficiency, patient comfort, and infection control. In conclusion, DIGM was significantly more efficient than finger-prick testing and strongly preferred by clinical staff. These technologies offer time-saving benefits that could improve patient experience, streamline clinical workflows, and potentially enhance diabetes management outcomes.
Indexed as
Identifiers
What Socratic 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 Socratic graph.