Pharmacist Metrics in the Pediatric Intensive Care Unit: an Exploration of the Medication Regimen Complexity-Intensive Care Unit (MRC-ICU) Score

• Type of Material: Article
• Authors: Swaminathan Kandaswamy, Emory University; Thomas E. Dawson, Children's Healthcare of Atlanta; Whitney H. Moore, Wolfson Children's Hospital; Katherine Howell, Children's Healthcare of Atlanta; Jonathan Beus, Children's Healthcare of Atlanta; Olutola Adu, Children's Healthcare of Atlanta; Andrea Sikora, University of Georgia, Athens
• Language: English
• Date: 2023-12-12
• Publisher: Pediatric Pharmacy Association
• Publication Version: Final Published Version
• Copyright Statement: Pediatric Pharmacy Association. All rights reserved. For permissions, email: [e-mail]
• Final Published Version (URL): https://doi.org/10.5863/1551-6776-28.8.728
• Title of Journal or Parent Work: The Journal of Pediatric Pharmacology and Therapeutics
• Volume: 28
• Issue: 8
• Start Page: 728
• End Page: 734
• Grant/Funding Information: This study was funded by the Agency of Healthcare Research and Quality. Funding for Andrea Sikora and Swaminathan Kandaswamy was provided through R01HS029009 and through R21HS028485 for Andrea Sikora.
• Keywords: informatics; critical care; pharmacy; medication regimen complexity; pediatrics; pharmacists
• Research Categories: Health Sciences, Health Care Management; Health Sciences, Pharmacology

Abstract

INTRODUCTION The medication regimen complexity-intensive care unit (MRC-ICU) score has been developed and validated as an objective predictive metric for patient outcomes and pharmacist workload in the adult critically ill population. The purpose of this study was to explore the MRC-ICU and other workload metrics in the pediatric ICU (PICU). METHODS This study was a retrospective cohort of pediatric ICU patients admitted to a single institution ­between February 2, 2022 – August 2, 2022. Two scores were calculated, including the MRC-ICU and the pediatric Daily Monitoring System (pDMS). Data were extracted from the electronic health record. The primary outcome was the correlation of the MRC-ICU to mortality, as measured by Pearson ­correlation ­coefficient. Additionally, the correlation of MRC-ICU to number of orders was evaluated. Secondary ­analyses explored the correlation of the MRC-ICU with pDMS and with hospital and ICU length of stay. RESULTS A total of 2,232 patients were included comprising 2,405 encounters. The average age was 6.9 years (standard deviation [SD] 6.3 years). The average MRC-ICU score was 3.0 (SD 3.8). For the primary outcome, MRC-ICU was significantly positively correlated to mortality (0.22 95% confidence interval [CI 0.18 – 0.26]), p<0.05. Additionally, MRC-ICU was significantly positively correlated to ICU length of stay (0.38 [CI 0.34 – 0.41]), p<0.05. The correlation between the MRC-ICU and pDMS was (0.72 [CI 0.70 – 0.73]), p<0.05. CONCLUSION In this pilot study, MRC-ICU demonstrated an association with existing prioritization metrics and with mortality and length of ICU stay in PICU population. Further, larger scale studies are required.