Evaluating the Medication Regimen Complexity Score as a Predictor of Clinical Outcomes in the Critically Ill

Abstract

Background: Medication Regimen Complexity (MRC) refers to the combination of medication classes, dosages, and frequencies. The objective of this study was to examine the relationship between the scores of different MRC tools and the clinical outcomes. Methods: We conducted a retrospective cohort study at Roger William Medical Center, Providence, Rhode Island, which included 317 adult patients admitted to the intensive care unit (ICU) between 1 February 2020 and 30 August 2020. MRC was assessed using the MRC Index (MRCI) and MRC for the Intensive Care Unit (MRC-ICU). A multivariable logistic regression model was used to identify associations among MRC scores, clinical outcomes, and a logistic classifier to predict clinical outcomes. Results: Higher MRC scores were associated with increased mortality, a longer ICU length of stay (LOS), and the need for mechanical ventilation (MV). MRC-ICU scores at 24 h were significantly (p < 0.001) associated with increased ICU mortality, LOS, and MV, with ORs of 1.12 (95% CI: 1.06–1.19), 1.17 (1.1–1.24), and 1.21 (1.14–1.29), respectively. Mortality prediction was similar using both scoring tools (AUC: 0.88 [0.75–0.97] vs. 0.88 [0.76–0.97]. The model with 15 medication classes outperformed others in predicting the ICU LOS and the need for MV with AUCs of 0.82 (0.71–0.93) and 0.87 (0.77–0.96), respectively. Conclusion: Our results demonstrated that both MRC scores were associated with poorer clinical outcomes. The incorporation of MRC scores in real-time therapeutic decision making can aid clinicians to prescribe safer alternatives.