Five-Year Mortality and Hospital Costs Associated with Surviving Intensive Care

Abstract

Rationale: Survivors of critical illness experience significant morbidity, but the impact of surviving the intensive care unit (ICU) has not been quantified comprehensively at a population level.

Objectives: To identify factors associated with increased hospital resource use and to ascertain whether ICU admission was associated with increased mortality and resource use.

Methods: Matched cohort study and pre/post-analysis using national linked data registries with complete population coverage. The population consisted of patients admitted to all adult general ICUs during 2005 and surviving to hospital discharge, identified from the Scottish Intensive Care Society Audit Group registry, matched (1:1) with similar hospital control subjects. Five-year outcomes included mortality and hospital resource use. Confounder adjustment was based on multivariable regression and pre/post within-individual analyses.

Measurements and main results: Of 7,656 ICU patients, 5,259 survived to hospital discharge (5,215 [99.2%] matched to hospital control subjects). Factors present before ICU admission (comorbidities/pre-ICU hospitalizations) were stronger predictors of hospital resource use than acute illness factors. In the 5 years after the initial hospital discharge, compared with hospital control subjects, the ICU cohort had higher mortality (32.3% vs. 22.7%; hazard ratio, 1.33; 95% confidence interval, 1.22-1.46; P < 0.001), used more hospital resources (mean hospital admission rate, 4.8 vs. 3.3/person/5 yr), and had 51% higher mean 5-year hospital costs ($25,608 vs. $16,913/patient). Increased resource use persisted after confounder adjustment (P < 0.001) and using pre/post-analyses (P < 0.001). Excess resource use and mortality were greatest for younger patients without significant comorbidity.

Conclusions: This complete, national study demonstrates that ICU survivorship is associated with higher 5-year mortality and hospital resource use than hospital control subjects, representing a substantial burden on individuals, caregivers, and society.

Keywords: hospital costs; hospital readmission; intensive care; mortality; registries.

Figure 1.

Kaplan-Meier plot of 5-year survival after hospital discharge for the intensive care unit (ICU) survivor cohort, hospital cohort, and general population of Scotland. General population mortality rates were derived using age–sex indirect standardization. Gen = general; Popul = general population at risk of event; Hosp = hospital control cohort at risk of event; ICU = ICU cohort at risk of event.

Figure 2.

Hospital costs for all admission types and emergency admissions before and after index hospital admission for the intensive care unit survivor cohort (n = 5,259). Each point represents the mean cost in 2014 US$ for each quarter (reported as cost per year) for each patient alive at the start of each quarter.

Figure 3.

Mean hospital costs in the 5-year period after discharge from index hospitalization in intensive care unit (ICU) survivors compared with hospital control subjects (A) for all patients, (B and C) for patients stratified by age (B, age < 70 yr; C, age ≥ 70 yr), and (D and E) in the presence of Charlson comorbidity (D, no comorbidity; E, one or more comorbidities). Each point represents the mean cost for each quarter (reported as cost per year) for each patient alive at the start of each quarter. Modeling number of admissions rather than costs, age was an effect modifier for the admission rate ratio (ARR) of ICU survivors compared with hospital controls (age < 70 yr: ARR, 1.28; 95% confidence interval [CI], 1.18–1.38; P < 0.001; age ≥ 70 yr: ARR, 1.09; 95% CI, 1.00–1.19; P = 0.05; interaction term, P < 0.001). Similarly, comorbidity is an effect modifier (no comorbidity: ARR, 1.25; 95% CI, 1.17–1.34; P < 0.001; one or more comorbidities: ARR, 1.02; 95% CI, 0.91–1.14; P = 0.72; interaction term, P = 0.02).

Figure 4.

Difference in mean annual hospital costs from baseline cost in pre/post within-individual analyses in the 5-year period after discharge from index hospitalization: sensitivity analysis in varying baseline hospital cost and effect of aging on hospital costs. (A) Baseline hospital cost was varied from the mean annual hospital cost in the 1 year before index hospital admission (solid lines) and the mean annual hospital cost in the 5 years before index hospital admission (dashed lines). Lighter lines represent 95% confidence intervals. (B) In addition to varying baseline costs, the effect of aging on hospital costs was modeled, using the gradient of increasing costs during the preindex hospitalization period. The gradient was assumed to vary under three scenarios: no effect of aging on costs (X); the assumption that the cost gradient during Years –5, –4, and –3 pre–index hospitalization continued during Years 0 to 5 years posthospitalization (Y); and finally, the assumption that the cost gradient from –5 years to 0 years pre–index hospitalization continued during Years 0 to 5 years posthospitalization (Z).