Association of Sociodemographic Factors With Overtriage, Undertriage, and Value of Care After Major Surgery

Author:

Loftus Tyler J.12,Ruppert Matthew M.13,Shickel Benjamin13,Ozrazgat-Baslanti Tezcan13,Balch Jeremy A.124,Abbott Kenneth L.2,Hu Die12,Javed Adnan5,Madbak Firas6,Guirgis Faheem7,Skarupa David6,Efron Philip A.2,Tighe Patrick J.8,Hogan William R.9,Rashidi Parisa14,Upchurch Gilbert R.2,Bihorac Azra123

Affiliation:

1. Intelligent Critical Care Center, University of Florida, Gainesville, FL

2. Department of Surgery, University of Florida Health, Gainesville, FL

3. Department of Medicine, University of Florida Health, Gainesville, FL

4. Departments of Biomedical Engineering, Computer and Information Science and Engineering, and Electrical and Computer Engineering, University of Florida, Gainesville, FL

5. Departments of Emergency Medicine & Critical Care Medicine, University of Florida College of Medicine, Jacksonville, FL

6. Department of Surgery, University of Florida College of Medicine, Jacksonville, FL

7. Department of Emergency Medicine, University of Florida College of Medicine, Jacksonville, FL

8. Departments of Anesthesiology, Orthopedics, and Information Systems/Operations Management, University of Florida Health, Gainesville, FL

9. Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL.

Abstract

Objective: To determine whether certain patients are vulnerable to errant triage decisions immediately after major surgery and whether there are unique sociodemographic phenotypes within overtriaged and undertriaged cohorts. Background: In a fair system, overtriage of low-acuity patients to intensive care units (ICUs) and undertriage of high-acuity patients to general wards would affect all sociodemographic subgroups equally. Methods: This multicenter, longitudinal cohort study of hospital admissions immediately after major surgery compared hospital mortality and value of care (risk-adjusted mortality/total costs) across 4 cohorts: overtriage (N = 660), risk-matched overtriage controls admitted to general wards (N = 3077), undertriage (N = 2335), and risk-matched undertriage controls admitted to ICUs (N = 4774). K-means clustering identified sociodemographic phenotypes within overtriage and undertriage cohorts. Results: Compared with controls, overtriaged admissions had a predominance of male patients (56.2% vs 43.1%, P < 0.001) and commercial insurance (6.4% vs 2.5%, P < 0.001); undertriaged admissions had a predominance of Black patients (28.4% vs 24.4%, P < 0.001) and greater socioeconomic deprivation. Overtriage was associated with increased total direct costs [$16.2K ($11.4K–$23.5K) vs $14.1K ($9.1K–$20.7K), P < 0.001] and low value of care; undertriage was associated with increased hospital mortality (1.5% vs 0.7%, P = 0.002) and hospice care (2.2% vs 0.6%, P < 0.001) and low value of care. Unique sociodemographic phenotypes within both overtriage and undertriage cohorts had similar outcomes and value of care, suggesting that triage decisions, rather than patient characteristics, drive outcomes and value of care. Conclusions: Postoperative triage decisions should ensure equality across sociodemographic groups by anchoring triage decisions to objective patient acuity assessments, circumventing cognitive shortcuts and mitigating bias.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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