Characteristics and resource utilization of high-cost users in the intensive care unit: a population-based cohort study - Claudia Dziegielewski; Robert Talarico; Haris Imsirovic; Danial Qureshi; Yasmeen Choudhri; Peter Tanuseputro; Laura H. Thompson; Kwadwo Kyeremanteng (BMC, 2021)
Abstract Background Healthcare expenditure within the intensive care unit (ICU) is costly. A cost reduction strategy may be to target patients accounting for a disproportionate amount of healthcare spending, or high-cost users. This study aims to describe high-cost users in the ICU, including health outcomes and cost patterns. Methods We conducted a population-based retrospective cohort study of patients with ICU admissions in Ontario from 2011 to 2018. Patients with total healthcare costs in the year following ICU admission (including the admission itself) in the upper 10th percentile were defined as high-cost users. We compared characteristics and outcomes including length of stay, mortality, disposition, and costs between groups. Results Among 370,061 patients included, 37,006 were high-cost users. High-cost users were 64.2 years old, 58.3% male, and had more comorbidities (41.2% had ≥3) when likened to non-high cost users (66.1 years old, 57.2% male, 27.9% had ≥3 comorbidities). ICU length of stay was four times greater for high-cost users compared to non-high cost users (22.4 days, 95% confidence interval [CI] 22.0-22.7 days vs. 5.56 days, 95% CI 5.54-5.57 days). High-cost users had lower in-hospital mortality (10.0% vs.14.2%), but increased dispositioning outside of home (77.4% vs. 42.2%) compared to non-high-cost users. Total healthcare costs were five-fold higher for high-cost users ($238,231, 95% CI $237,020-$239,442) compared to non-high-cost users ($45,155, 95% CI $45,046-$45,264). High-cost users accounted for 37.0% of total healthcare costs. Conclusion High-cost users have increased length of stay, lower in-hospital mortality, and higher total healthcare costs when compared to non-high-cost users. Further studies into cost patterns and predictors of high-cost users are necessary to identify methods of decreasing healthcare expenditure.