Reducing Delays in STAT Antibiotics Administration: Evaluation of Automated STAT-Order Alert System (ASOS)

Year Submitted: 2025
Published Date: 11 February 2026

Tags: Care Process ＆ Redesign, Technology, Workflow Redesign, Time Saving, Quality Improvement, Turnaround Time, Automation, Productivity

About this Content

Aims

1. To reduce mean time from STAT antibiotics order to administration time from 75 minutes to 60 minutes within 6 months. 2. To increase the percentage of STAT antibiotics order administration within 60 minutes to at least 50% within 6 months.

Background

Timely administration of STAT antibiotics is essential in reducing infection-related mortality, especially in sepsis cases. The Surviving Sepsis Campaign (2021) recommends antibiotic administration within one hour of sepsis recognition. At a tertiary acute hospital in Singapore, baseline data from July to September 2023 showed a mean STAT antibiotic administration time of 75.1 minutes, with 50% delivered within 60 minutes. Root cause analysis revealed a key issue where nurses were often unaware of STAT orders unless informed verbally or after checking the electronic Medication Administration Record (eMAR), leading to missed or delayed administration.

Methods

Using a quasi-experimental pre-post design, 4,003 STAT ward stock antibiotic orders were analysed: 2,145 pre-ASOS (July 2023) and 2,270 post-ASOS (July 2024). Ward stock antibiotics were specifically selected to eliminate confounding variables such as delays from pharmacy dispensing or porter delivery. These medications are stored directly in the ward and readily accessible to nurses, allowing the study to isolate the impact of the ASOS intervention on nursing response time alone. Due to the non-normal distribution of administration time, Mann-Whitney U test was used to compare the median time from order placement to administration. Run charts tracked monthly trends in average administration time and the percentage of antibiotics administered within 60 minutes. Additionally, administration times were categorized into three intervals: less than 60 minutes, 61-120 minutes, and more than 120 minutes, with distribution changes evaluated using the chi-square test.

Results

The average time from order to administration demonstrated a downward trend post-implementation, indicating greater consistency and timeliness in medication delivery. The mean administration time decreased from 75.1 minutes (SD 53.3) in the control group to 67.6 minutes (SD 44.5) in the intervention group. This difference was statistically significant (p=0.005), suggesting that ASOS contributed to the improvement. The percentage of STAT ward stock antibiotics administered within 60 minutes increased from 50.0% in the control group to 53.4% in the intervention group following the implementation of ASOS. Concurrently, administrations delayed beyond 120 minutes declined significantly from 20.7% to 14.7%, indicating reduced extreme delays. The proportion of administrations within 61-120 minutes also increased slightly from 29.2% to 31.9%. The chi-square test (x Squared=25.387, p=0.000) confirms a statistically significant shift in distribution across the time intervals, reflecting overall improvement in timeliness and responsiveness of antibiotic administration.

Conclusion

The implementation of the Automated Stat-Order Alert System (ASOS) significantly improved the timeliness of STAT antibiotic administration. While the one-hour benchmark remains a challenge, ASOS demonstrates a scalable and effective strategy to enhance communication, streamline urgent medication workflows, and support safer patient care.

Lessons Learnt

The implementation of ASOS significantly improved the timeliness of STAT antibiotic administration. While the one-hour benchmark remains a challenge, ASOS demonstrates a scalable and effective strategy to enhance communication, streamline urgent medication workflows, and support safer patient care.

Keywords

STAT antibiotics, ASOS, sepsis, administration time, alerts

Innovators' Details

Connect with this contributor!

Loh Huey Peng - singaporehealthcaremanagement@singhealth.com.sg

Project Attachment

1107_SGH_SHM_2025_Reducing_Delays_in_STAT_Antibiotic_Administration_A_Quasi_Experimental_Evaluation_of_Automated_Stat_Order_Alert_System_ASOS.pdf