Analysis of Rothman Index Data to Predict Postdischarge Adverse Events in a Medical Intensive Care Unit

Nursing care complexity as a predictor of adverse events in patients transferred from ICU to hospital ward after general surgery

OBJECTIVES

Predicting the likelihood of adverse events following discharge from the intensive care unit (ICU) can contribute to improving the quality of surgical care. This study aimed to evaluate the impact of nursing care complexity as a predictor of adverse event development in general surgery patients transferred from the ICU to the hospital ward.

METHODS

A prospective observational study was conducted with 100 patients in the ICU and general surgical inpatient unit of a training and research hospital in Istanbul, Turkey. The Nursing Care Complexity tool was used by ICU and hospital ward nurses to measure nursing complexity.

RESULTS

A total of 65 adverse events developed in 51 patients during hospital ward hospitalization after discharge from the ICU. Nursing care complexity evaluations by the ICU nurses predicted overall and some specific adverse events, while hospital ward nurses' evaluations predicted ICU readmission and some follow-up abnormalities such as patients' blood pressure, pulse rate, and laboratory results.

CONCLUSION

The results of the current study validate that nursing care complexity can serve as a valuable tool for predicting the risk of adverse events and ICU readmission following discharge from the ICU.

IMPLICATIONS FOR CLINICAL PRACTICE

The use of the Nursing Care complexity tool by the ICU and even hospital ward nurses after ICU discharge may have a significant impact on patient outcomes and contribute to the recognition of nursing efforts.

The Rothman Index predicts unplanned readmissions to intensive care associated with increased mortality and hospital length of stay: a propensity-matched cohort study

BACKGROUND

Patients with unplanned readmissions to the intensive care unit (ICU) are at high risk of preventable adverse events. The Rothman Index represents an objective real-time grading system of a patient's clinical condition and a predictive tool of clinical deterioration over time. This study was designed to test the hypothesis that the Rothman Index represents a sensitive predictor of unanticipated ICU readmissions.

METHODS

A retrospective propensity-matched cohort study was performed at a tertiary referral academic medical center in the United States from January 1, 2022, to December 31, 2022. Inclusion criteria were adult patients admitted to an ICU and readmitted within seven days of transfer to a lower level of care. The control group consisted of patients who were downgraded from ICU without a subsequent readmission. The primary outcome measure was in-hospital mortality or discharge to hospice for end-of-life care. Secondary outcome measures were overall hospital length of stay, ICU length of stay, and 30-day readmission rates. Propensity matching was used to control for differences between the study cohorts. Regression analyses were performed to determine independent risk factors of an unplanned readmission to ICU.

RESULTS

A total of 5,261 ICU patients met the inclusion criteria, of which 212 patients (4%) had an unanticipated readmission to the ICU within 7 days. The study cohort and control group were stratified by propensity matching into equal group sizes of n = 181. Lower Rothman Index scores (reflecting higher physiologic acuity) at the time of downgrade from the ICU were significantly associated with an unplanned readmission to the ICU (p < 0.0001). Patients readmitted to ICU had a lower mean Rothman Index score (p < 0.0001) and significantly increased rates of mortality (19.3% vs. 2.2%, p < 0.0001) and discharge to hospice (14.4% vs. 6.1%, p = 0.0073) compared to the control group of patients without ICU readmission. The overall length of ICU stay (mean 8.0 vs. 2.2 days, p < 0.0001) and total length of hospital stay (mean 15.8 vs. 7.3 days, p < 0.0001) were significantly increased in patients readmitted to ICU, compared to the control group.

CONCLUSION

The Rothman Index represents a sensitive predictor of unanticipated readmissions to ICU, associated with a significantly increased mortality and overall ICU and hospital length of stay. The Rothman Index should be considered as a real-time objective measure for prediction of a safe downgrade from ICU to a lower level of care.

Factors Associated With Inpatient Hospice Utilization Among Hospitalized Decedents With Comfort Measures Only Status

Background: Patients with serious illness may elect to transition their care to comfort measures only (CMO) while in the hospital. Although studies have shown that routine hospice care is underutilized, the rate of general inpatient hospice (GIP) use among CMO patients during their terminal admission remains unclear. Objectives: We sought to (1) examine the rate of GIP utilization and (2) identify factors associated with its use among hospitalized CMO decedents. Methods: CMO decedents in two academic, tertiary care hospitals in the United States who died between October 1, 2020 and October 31, 2021, were subgrouped based on their primary medical service (GIP vs. non-GIP) at the time of inpatient death. Data abstracted from the electronic health record included demographics, primary diagnosis codes, Rothman Index (RI), time of CMO order, ordering clinician type, time of death, and length of stay (LOS). Multivariable logistic regression analysis was performed, adjusting for relevant covariates. Results: Of 1475 CMO decedents, only 321 (n = 22%) patients received GIP. On multivariable analysis, CMO patients who died in an ICU were five times less likely (odds ratio [OR] = 0.18, confidence interval [95% CI] 0.11-0.29) to receive GIP. Every 10-point increase in RI raised the likelihood of receiving GIP by 59% (OR = 1.59, 95% CI 1.39-1.80). Conclusions: Most CMO decedents died in the hospital without GIP. Compared with GIP decedents, non-GIP decedents were less acutely ill. There was no difference in total LOS between the two groups. CMO decedents were much less likely to receive GIP in an ICU. The RI may help clinicians identify CMO patients who would benefit from GIP earlier in their terminal admission.

Development of a Discharge Criteria Checklist for COVID-19 Patients From the Intensive Care Unit

This study aims to develop and validate a checklist of discharge readiness criteria for COVID-19 patients from the intensive care unit (ICU). We conducted a Delphi design study. The degree of agreement among 7 experts had been evaluated using the content validity index (CVI) through a 4-point Likert scale. The instrument was validated with 17 items. All the experts rated all items as very relevant which scored the item-CVI 1, which validates all checklist items. Using the mean of all items, the scale-CVI was calculated, and it was 1. This meant validation of the checklist as a whole. With regard to the overall checklist evaluation, the mean expert proportion of the instrument was 1, and the S-CVI/UA was 1. This discharge criteria checklist improves transition of care for COVID-19 patients and can help nurses, doctors, and academics to discharge COVID-19 patients from the ICU safely.

Deterioration Index in Critically Injured Patients: A Feasibility Analysis

INTRODUCTION

Continuous prediction surveillance modeling is an emerging tool giving dynamic insight into conditions with potential mitigation of adverse events (AEs) and failure to rescue. The Epic electronic medical record contains a Deterioration Index (DI) algorithm that generates a prediction score every 15 min using objective data. Previous validation studies show rapid increases in DI score (≥14) predict a worse prognosis. The aim of this study was to demonstrate the utility of DI scores in the trauma intensive care unit (ICU) population.

METHODS

A prospective, single-center study of trauma ICU patients in a Level 1 trauma center was conducted during a 3-mo period. Charts were reviewed every 24 h for minimum and maximum DI score, largest score change (Δ), and AE. Patients were grouped as low risk (ΔDI <14) or high risk (ΔDI ≥14).

RESULTS

A total of 224 patients were evaluated. High-risk patients were more likely to experience AEs (69.0% versus 47.6%, P = 0.002). No patients with DI scores <30 were readmitted to the ICU after being stepped down to the floor. Patients that were readmitted and subsequently died all had DI scores of ≥60 when first stepped down from the ICU.

CONCLUSIONS

This study demonstrates DI scores predict decompensation risk in the surgical ICU population, which may otherwise go unnoticed in real time. This can identify patients at risk of AE when transferred to the floor. Using the DI model could alert providers to increase surveillance in high-risk patients to mitigate unplanned returns to the ICU and failure to rescue.

Evaluation of Clinical Predictors for Major Outcomes in Patients Hospitalized With COVID-19: The Potential Role of the Rothman Index

Introduction

The Rothman Index (RI, PeraHealth, Inc. Charlotte, NC, USA) is a predictive model intended to provide continuous monitoring of a patient's clinical status. There is limited data to support its use in the risk stratification of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We hypothesized that low admission RI scores would correlate with higher rates of adverse outcomes in patients hospitalized for coronavirus disease 2019 (COVID-19).

Methods

Medical records of adult patients admitted to a single 1,200-bed tertiary academic center were retrospectively reviewed for demographic data, baseline characteristics, RI scores, admission to intensive care unit (ICU), need for mechanical ventilation, and inpatient mortality. Statistical analyses were performed using STATA statistical software, version 17 (Stata Corp LLC, College Station, TX, USA). Continuous variables were analyzed using the Mann-Whitney test, and categorical variables were analyzed using Fisher’s exact test. Both univariate and multivariate analyses were performed. A p-value <0.05 was considered statistically significant.

Results

Median admission RI score for the entire cohort was 63.0 (IQR 45.0 - 77.1). The cohort was divided by admission RI into a low-risk group (RI ≥70; n=70) and a high-risk group (RI <70; n=107). Compared to patients with low-risk RI, patients with high-risk RI had higher mortality (95.2%, 95% CI: 85.8 - 105 vs 4.8%, 95% CI: -5 - 14.2, p < 0.01), were more likely to require ICU admission (90.2%, 95% CI: 81.9 - 98.5 vs 9.8%, 95% CI: 1.5 - 18.1, p < 0.01) and mechanical ventilation (89.7%, 95% CI: 78.3 - 101 vs 10.3%, 95% CI: -1 - 21.7, p < 0.01), and had a longer median hospital length of stay (12 days, 95% CI: 9 - 14 vs 5 days, 95% CI: 4 - 7, p < 0.01).

Conclusions

High-risk RI was associated with increased admission to the ICU, mechanical ventilation, and mortality. These results suggest that it may be used as a tool to aid provider judgment in the setting of COVID-19.

Do In-Hospital Rothman Index Scores Predict Postdischarge Adverse Events and Discharge Location After Total Knee Arthroplasty?

BACKGROUND

There have been efforts to reduce adverse events and unplanned readmissions after total joint arthroplasty. The Rothman Index (RI) is a real-time, composite measure of medical acuity for hospitalized patients. We aimed to examine the association among in-hospital RI scores and complications, readmissions, and discharge location after total knee arthroplasty (TKA). We hypothesized that RI scores could be used to predict the outcomes of interest.

METHODS

This is a retrospective study of an institutional database of elective, primary TKA from July 2018 until December 2019. Complications and readmissions were defined per Centers for Medicare and Medicaid Services. Analysis included multivariate regression, computation of the area under the curve (AUC), and the Youden Index to set RI thresholds.

RESULTS

The study cohort's (n = 957) complications (2.4%), readmissions (3.6%), and nonhome discharge (13.7%) were reported. All RI metrics (minimum, maximum, last, mean, range, 25th%, and 75th%) were significantly associated with increased odds of readmission and home discharge (all P < .05). RI scores were not significantly associated with complications. The optimal RI thresholds for increased risk of readmission were last ≤ 71 (AUC = 0.65), mean ≤ 67 (AUC = 0.66), or maximum ≤ 80 (AUC = 0.63). The optimal RI thresholds for increased risk of home discharge were minimum ≥ 53 (AUC = 0.65), mean ≥ 69 (AUC = 0.65), or maximum ≥ 81 (AUC = 0.60).

CONCLUSION

RI values may be used to predict readmission or home discharge after TKA.

Transition of care at discharge from the Intensive Care Unit: a scoping review

OBJECTIVE

to map the available evidence on the components of the transition of care, practices, strategies, and tools used in the discharge from the Intensive Care Unit (ICU) to the Inpatient Unit (IU) and its impact on the outcomes of adult patients.

METHOD

a scoping review using search strategies in six relevant health databases.

RESULTS

37 articles were included, in which 30 practices, strategies or tools were identified for organizing and executing the transfer process, with positive or negative impacts, related to factors intrinsic to the Intensive Care Unit and the Inpatient Unit and cross-sectional factors regarding the staff. The analysis of hospital readmission and mortality outcomes was prevalent in the included studies, in which trends and potential protective actions for a successful care transition are found; however, they still lack more robust evidence and consensus in the literature.

CONCLUSION

transition of care components and practices were identified, in addition to factors intrinsic to the patient, associated with worse outcomes after discharge from the Intensive Care Unit. Discharges at night or on weekends were associated with increased rates of readmission and mortality; however, the association of other practices with the patient's outcome is still inconclusive.