Comparing glucose monitoring methods: efficiency insights in a simulated hospital setting

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.

Keywords: FreeStyle Libre; capillary blood glucose monitoring; continuous glucose monitoring; diabetes; finger-prick test; flash glucose monitoring-dynamic interstitial glucose monitoring; staff perception.

Figure 1

Flow diagram illustrating participant recruitment and inclusion in the simulation-based study.

Figure 2

Demographic characteristics of study participants, including professional roles, age distribution, and experience with glucose monitoring.

Figure 3

Comparison of participant characteristics (nurses vs. AHCPs), including years of experience and familiarity with glucose monitoring methods.

Figure 4

Aggregated responses to Likert-scale survey items assessing healthcare staff perceptions of DIGM versus traditional finger-prick testing.

Figure 5

Projected total time required for 20 glucose measurements per patient using either DIGM or finger-prick testing, highlighting time savings with DIGM.

Figure 6

Monte Carlo simulation results demonstrating average staff time saved per patient when using DIGM compared to finger-prick testing.

Figure 7

Correlation between professional experience and task efficiency for DIGM and finger-prick glucose monitoring methods.