# Review of Adult Critical Care Calls to the Out-of-Hours Resident Pharmacist Service: A Retrospective Single-Center Observation Study

## TL;DR

This study examines out-of-hours pharmacy calls from adult critical care units to understand their patterns and characteristics.

## Contribution

The study provides a detailed analysis of OOH pharmacy calls in critical care, highlighting trends in medication requests and call timing.

## Key findings

- Most OOH calls were for medication supply, with anti-infectives being the most requested drug category.
- Nighttime calls showed a higher proportion for all drug classes and routes of administration compared to evening calls.
- Thursday was the busiest day for calls, and ICU1 had the highest number of calls.

## Abstract

Background

There is good evidence describing on-call pharmacy services internationally; however, there is limited evidence evaluating out-of-hours (OOH) calls from adult critical care units. Our primary objective is to describe the characteristics of OOH calls from adult critical care units to resident pharmacists, to inform service provision to this high-risk specialty. Our secondary objective is to compare the characteristics of calls during evening and nighttime hours.

Methods

This is a retrospective observational review of adult critical care OOH calls received by resident pharmacists from August 2023 to July 2024 at a large tertiary center. OOH calls were defined as calls received from 5 pm to 9 am Monday to Sunday, and we further differentiated the calls into evening calls (5 pm to 9 pm) and nighttime calls (9 pm to 9 am). We collected the characteristics of OOH calls, i.e., patient age and sex, ward location, type of query (medicines information/advice or supply), drug requested, category of drug, route of administration, day of the week, date and time of call received, and duration to resolution of call. We compared the characteristics of OOH calls during the evening (5 pm to 9 pm) vs. nighttime (9 pm to 9 am) using an independent samples t-test for continuous data and Pearson's χ2 test for categorical data.

Results

We identified 5085 OOH calls from adult critical care units, which represented 15.3% of all calls received by the resident pharmacist during the study period. Of these, 2080 calls were received between the hours of 5 pm and 9 pm, and 3004 calls were received between the hours of 9 pm and 9 am. Most calls related to male patients (n=2364; 46.5%), with a mean (SD) of 56.6 (17.5) years. The highest number of calls was received from ICU1 (n=1183; 23.3%), followed by ICU2 (n=923; 18.2%) and ICU6 (n=787; 15.5%). The greatest proportion of calls was received on a Thursday (n=806; 15.9%), and January 2024 was the busiest month for calls (n=528; 17.6%). Most calls were for medication supply (n=4885; 96.1%), and most calls took 50 minutes and over to complete (n=4724; 92.9%). We compared the general characteristics of calls between 5 pm and 9 pm with calls between 9 pm and 9 am and found no significant difference in the proportion of calls to individual critical care units (p=0.050), the day of the week (p=0.513), or the category of the call (p=0.074). We found no significant difference in patient characteristics when comparing OOH calls received during the evening and nighttime periods: male sex 48.4% vs. 45.2% (p=0.563) and age 56.3 (17.6) vs. 56.9 (17.5) years (p=0.250). There were 5915 medication requests for supply or advice during the study period. Total parenteral nutrition was the most requested item (n=255; 4.3%), and the most requested category of medicine was anti-infectives (n=921; 18.1%). We compared the characteristics of medicines between evening and nighttime and found a higher proportion of calls during nighttime for all classes of drugs (p<0.001) and most routes of administration (p<0.001).

Conclusions

OOH pharmacy services to adult critical care provide timely supply and advice of critical medicines; however, no conclusions of impact on patient outcomes can be inferred. Further work should explore the impact of calls on avoidable patient harm, the economic analysis of the resident pharmacist on-call service, and whether the integration of artificial intelligence decision support could lower call volume.