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. 2023 Sep 25:15:703-719.
doi: 10.2147/CEOR.S424759. eCollection 2023.

Patient Characteristics and Clinical and Economic Outcomes Associated with Unplanned Medical and Surgical Intensive Care Unit Admissions: A Retrospective Analysis

Affiliations

Patient Characteristics and Clinical and Economic Outcomes Associated with Unplanned Medical and Surgical Intensive Care Unit Admissions: A Retrospective Analysis

Ashish K Khanna et al. Clinicoecon Outcomes Res. .

Abstract

Purpose: To characterize medical and surgical patient characteristics, as well as clinical and economic outcomes, associated with unplanned intensive care unit (ICU) admissions.

Patients and methods: This was a retrospective matched cohort analysis that utilized the PINC AITM Healthcare Database, which collects deidentified data from 25% of United States (US) hospital admissions. Discharge records were assessed for medical and surgical admissions in 2021. An unplanned ICU admission was defined as direct transfer from a medical, surgical, or telemetry unit to the ICU. Patients with and without an unplanned ICU admission were 1:1 propensity score matched. Differences between patients with and without unplanned ICU admissions were assessed using two-sample t-tests for continuous measures and Chi-square tests for categorical measures.

Results: A total of 3,807,124 qualifying admissions were identified. Medical admissions with unplanned ICU transfers were more likely to be urgent/emergent (odds ratio [OR] 2.9, 95% confidence interval [CI 2.7-3.0], p<0.0001), with patient characteristics including male sex (1.4, [1.4-1.4], p<0.0001), obesity (1.7, [1.6-1.7], p<0.0001), and increased Charlson Comorbidity Index (CCI=1: 1.8, [1.8-1.9], p<0.0001; CCI≥5: 3.2, [3.1-3.3], p<0.0001). Surgical admissions with unplanned ICU transfers were more likely to be urgent/emergent (3.1, [2.9-3.2], p<0.0001) and with patients of higher CCI (2.5, [2.3-2.6], p<0.0001 to a CCI of≥5 (7.9, [7.4-8.4], p<0.0001). Between matched medical patients, mean differences in length of stay, cost, and mortality were 4.1 days (p<0.0001), $13,424 (p<0.0001), and 21% (p<0.0001), respectively. Between matched surgical patients, mean differences in these outcomes were 6.4 days (p<0.0001), $21,448 (p<0.0001), and 14% (p<0.0001), respectively.

Conclusion: Emergency care in patients with a higher co-morbid burden is more likely to lead to unplanned ICU admission, putting patients at a significantly increased chance of mortality, longer length of stay, and increased costs. Improving care and monitoring of patients outside the ICU may help detect early changes in pathophysiology and enable early intervention.

Keywords: comorbidity; healthcare costs; length of stay; mortality.

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Conflict of interest statement

Roop Kaw reports consulting fees from Medtronic. Marilyn A. Moucharite and Patrick Benefield report full time employment with Medtronic. Ashish K. Khanna reports consulting fees from Medtronic, Edwards Lifesciences, Philips Research North America, GE Healthcare, Caretaker Medical, Retia Medical, Baxter, Trevena Pharmaceuticals and support via an NIH/NCATS KL2 award for a trial of continuous portable monitoring on hospital general care floors. The Department of Anesthesiology at Wake Forest School of Medicine is funded by Edwards Lifesciences, Masimo, and Medtronic. The authors report no other conflicts of interest in this work.

Figures

Figure 1
Figure 1
Patient selection criteria for inclusion in the analysis cohort.
Figure 2
Figure 2
Patient demographic and clinical characteristics associated with unplanned ICU admissions, compared to admissions without unplanned ICU admissions, in (A) medical and (B) surgical patients. Points represent odds ratio and bars represent 95% confidence intervals.
Figure 3
Figure 3
Results of the post-match covariate balance validation for predictor variables, medical admissions. Points represent standardized mean differences before matching (white diamonds) and after matching (black circles).
Figure 4
Figure 4
Results of the post-match covariate balance validation for predictor variables, surgical admissions. Points represent standardized mean differences before matching (white diamonds) and after matching (black circles).

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