Characteristics, Outcomes, and Cost Patterns of High-cost Patients in the Intensive Care Unit
CCCF ePoster library. Kyeremanteng K. Oct 2, 2017; 198133
Kwadwo Kyeremanteng
Kwadwo Kyeremanteng
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Characteristics, Outcomes, and Cost Patterns of High-cost Patients in the Intensive Care Unit

Reardon, Peter 1; Thavorn, Kednapa 2,3,4;Van Katkwyk, Sasha 2; Kobewka, Daniel 2,5; Tanuseputro, Peter 2,6; Rosenberg, Erin 1,2; Wan, Cynthia 7; Vanderspank-Wright, Brandi 2,8; Kubelik, Dalibor 1,2; Devlin, Rose Anne 2; Kyeremanteng, Kwadwo 1,2;

Division of Critical Care Medicine, University of Ottawa, Ottawa, Ontario, Canada; 2 Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; 3 School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, Canada; 4 Institute for Clinical and Evaluative Sciences, University of Ottawa, Ottawa, Ontario, Canada; 5 Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada; 6 Department of Family Medicine, University of Ottawa, Ontario, Canada; 7 School of Psychology, University of Ottawa, Ottawa, Ontario, Canada; 8 School of Nursing, University of Ottawa, Ottawa, Ontario, Canada


Critical care medicine is expensive. It is estimated that almost 1% of the gross domestic product is spent on critical care alone.1 Additionally, intensive care unit (ICU) costs are expected to rise as usage escalates due to an aging population and the increasing severity of illness among hospitalized patients.2,3
It has been well described in the literature that a small proportion patients account for a disproportionate amount of health care spending.4-10 Longitudinal data has shown that only a minority of these patients remain in the high-cost group over time,15,22 rendering reactive strategies less useful. Identifying these patients up front may present an opportunity for focused intervention to reduce spending, albeit there is a paucity of literature describing these patients in the ICU setting. To date, we are only aware of a single retrospective study reported in the ICU literature.11 A better understanding of the cost pattern predictors may help anticipate resource demands and provide an opportunity to mitigate costs. 

To describe the characteristics, cost patterns, and outcomes for high-cost patients in the ICU. 

This was a retrospective observational cohort study conducted at two medical/surgical ICUs in a tertiary care academic centre. Included patients were critically ill admissions aged 18 years or older. This was a cost comparison study. Patients were divided into cost groups with the highest 10th percentile being compared to the 90th percentile regarding their characteristics, cost patterns and outcomes. 

A total of 7849 patients (8449 encounters) were included, with 7063 in the low-cost group and 786 patients in the high-cost group. The high-cost group had a mean age of 60.7 years. The high-cost group had a longer length of stay with a mean duration of 32.6 days in the ICU. The median direct cost per patient in the high-cost group was $148327 (IQR 114007 - 224610), and the top 10% of patients amounted to 49% of direct costs. Non-survivors were more likely to have a premorbid diagnosis of congestive heart failure, OR 1.84 (95% CI 1.27 - 2.68), chronic obstructive pulmonary disease, OR 2.32 (95% CI 1.64 - 3.28), or to be admitted after a procedural complication, OR 2.93 (95% CI 1.24 - 6.90).
Despite the difference in cost, the in-hospital mortality rate was 27.8% in the high-cost group, compared to 29.5% in the low-cost group (p = .341). Only 10.7% of the high-cost group were ultimately dispositioned home, compared to 29.4% in the low-cost group (p < .0001), and 33.6% of patients were transferred to long term care facilities.
In summary, in a population of high-cost ICU patients, we found that the top 10% of patients are responsible for half of the total cost. Among these, only a minimal proportion are sent home. Premorbid chronic obstructive pulmonary disease and patients admitted from procedure complications independently predicted high-cost status among non-survivors and may represent a population where cost strategies could be further explored.

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