Inpatient disposition in overcrowded hospitals: is it safe and effective to use reverse triage and readmission screening tools for appropriate discharge? An observational prospective study of an Italian II level hospital

Abstract

Summary Background Reverse triage (RT) identifies patients eligible for discharge and have been proposed to cope with daily surge. Nevertheless, early discharge could increase the rate of readmission. Our aim is to test the effectiveness and safety of RT alone and with readmission screening tools (Identification Senior At Risk [ISAR], HOSPITAL, and Groeningen Frailty Index [GFI] scores) to predict appropriate discharge. Material and methods We prospectively assessed every 4 days (t0) inpatients of medical divisions (High Dependency Unit (HDU), Internal Medicine (IM), and Geriatrics (Ger)) of an Italian Hospital. RT score was calculated for each patient and an RT ≤3 identified those eligible for safe discharge. ISAR, HOSPITAL, and GFI were then applied. We assessed reinstituting of interventions and transferring to an increased level of care unit at 4 days as an ethical proxy of consequential medical events following hypothetical discharge. Date of effective discharge, death, and readmission were measured at 4, 7, 15, and 30 days after the first evaluation. Results Twenty‐five (9.6%) out of 260 patients in our sample had an RT ≤3. Twenty‐four (96%) of them compared with 205 (87%) of the RT >3 group (P = NS) were discharged. Patients with RT ≤3 were discharged significantly earlier (3.5 vs 8 days after t0 [P = 0.0002]). In the RT ≤3 group, all but one patient were alive and healthy at 7, 15, and 30 days. The HOSPITAL score seemed to have the best concordance with RT (84%), in comparison with the ISAR (52%) and the GFI (48%) scores. RT showed a low sensitivity (22%) and high specificity (95%), which was even higher when using RT associated with readmission screening tools. Conclusions Reverse triage proved to be a safe and conservative tool, with high specificity alone and with readmission screening tools. RT correctly identifies patients that will be discharged earlier.

Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions

“…Furthermore, the SERAP could also be adopted in the practice of reverse triage, a strategy coping with unusually high-demand situations by identifying patients who no longer need in-hospital resources and is safe for early discharge. 48 , 49 , 50 The integration of high-quality readmission risk evaluation models into the decision-making algorithm for reverse triage has been shown to further improve patient safety by Caramello et al. 50 Further research needs to be conducted to validate the effectiveness and physician-perceived acceptability after incorporating the SERAP into the transitional care model and reverse triage.…”

“…48 , 49 , 50 The integration of high-quality readmission risk evaluation models into the decision-making algorithm for reverse triage has been shown to further improve patient safety by Caramello et al. 50 Further research needs to be conducted to validate the effectiveness and physician-perceived acceptability after incorporating the SERAP into the transitional care model and reverse triage.…”

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“…A total of 434 or 6% of patients had LOS for two nights, 369 or 5% for three nights, 3% or 226 for 4 nights and only 1% or 87 patients who stayed in the hospital for a long time (more than 4 nights). Many researchers took the limit of more than 4 nights as an indicator of prolonged hospitalization (Brandi et al, 2020;Caramello et al, 2019;Neto et al, 2020;Rezaianzadeh et al, 2020).…”

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“…Consequently, the existing severity triage lacks usefulness and causes disputes between patients and medical staff [11]. In overcrowded hospitals, the development of a safe discharge system to prioritize hospitalization will improve patient safety and reduce repeat visits [12]. It has also been reported that clinical evaluation is superior to the use of various severity triage systems [13].…”