The impact of emergency department crowding on admission decisions and patient outcomes.

OBJECTIVES: The objective of this study is to evaluate the impact of emergency department (ED) crowding levels on patient admission decisions and outcomes. METHODS: A retrospective study was performed based on 2-year electronic health record data from a tertiary care hospital ED in Alberta, Canada. Using modified Poisson regression models, we studied the association of patient admission decisions and 7-day revisit probability with ED crowding levels measured by: 1) the total number of patients waiting and in treatment (ED census), 2) the number of boarding patients (boarder census), and 3) the average physician workload, calculated by the total number of ED patients divided by the number of physicians on duty (physician workload census). The control variables included age, gender, treatment area, triage level, and chief complaint. A subgroup analysis was performed to evaluate the heterogeneous effects among patients of different acuity levels. RESULTS: Our dataset included 141,035 patient visit records after cleaning from August 2013 to July 2015. The patient admission probability was positively correlated with ED census (relative risk [RR] = 1.006, 95% confidence interval [CI] = 1.005 to 1.007) and physician workload census (RR = 1.029, 95% CI = 1.027 to 1.032), but inversely correlated with boarder census (RR = 0.991, 95% CI = 0.989 to 0.993). We further found that the 7-day revisit probability of discharged patients was positively associated with boarder census (RR = 1.009, 95% CI = 1.004 to 1.014). CONCLUSIONS: Patient admission probability was found to be directly associated with ED census and physician workload census, but inversely associated with the boarder census. The effects of boarder census and physician workload census were stronger for patients of triage levels 3-5. Our results suggested that (i) insufficient physician staffing may lead to unnecessary patient admissions; (ii) too many boarding patients in ED leads to an increase in unsafe discharges, and as a result, an increase in 7-day revisit probability.

The effects of emergency department crowding on triage and hospital admission decisions.

BACKGROUND: Emergency department (ED) crowding is a recognized issue and it has been suggested that it can affect clinician decision-making. OBJECTIVES: Our objective was to determine whether ED census was associated with changes in triage or disposition decisions made by ED nurses and physicians. METHODS: We performed a retrospective study using one year of data obtained from a US academic center ED (65,065 patient encounters after cleaning). Using a cumulative logit model, we investigated the association between a patient's acuity group (low, medium, and high) and ED census at triage time. We also used multivariate logistic regression to investigate the association between the disposition decision for a patient (admit or discharge) and the ED census at the disposition decision time. In both studies, control variables included census, age, gender, race, place of treatment, chief complaint, and certain interaction terms. RESULTS: We found statistically significant correlation between ED census and triage/disposition decisions. For each additional patient in the ED, the odds of being assigned a high acuity versus medium or low acuity at triage is 1.011 times higher (95% confidence interval [CI] for Odds Ratio [OR] = [1.009,1.012]), and the odds of being assigned medium or high acuity versus low acuity at triage is 1.009 times higher (95% CI for OR = [1.008,1.010]). Similarly, the odds of being admitted versus discharged increases by 1.007 times (95% CI for OR = [1.006,1.008]) per additional patient in the ED at the time of disposition decision. CONCLUSION: Increased ED occupancy was found to be associated with more patients being classified as higher acuity as well as higher hospital admission rates. As an example, for a commonly observed patient category, our model predicts that as the ED occupancy increases from 25 to 75 patients, the probability of a patient being triaged as high acuity increases by about 50% and the probability of a patient being categorized as admit increases by around 25%.

Factors Influencing Hospital Admission of Non-critically Ill Patients Presenting to the Emergency Department: a Cross-sectional Study.

BACKGROUND: Little is known about the factors that influence physicians' admission decisions, especially among lower acuity patients. For the purpose of our study, non-medical refers to all of the factors-other than the patient's clinical condition-that could potentially influence admission decisions. OBJECTIVE: To describe the influence of non-medical factors on physicians' decisions to admit non-critically ill patients presenting to the ED. DESIGN: Cross-sectional study of hospital admissions at a single academic medical center. PARTICIPANTS: Non-critically ill adult patients admitted to the hospital (n = 297) and the admitting emergency medicine physicians (n = 34). MAIN MEASURES: A patient survey assessed non-medical factors, including primary care access and utilization. A physician survey assessed clinical and non-medical factors influencing the decision to admit. Based on physician responses, admissions were characterized as "strongly acuity-driven," "moderately acuity-driven," or "weakly acuity-driven." Among these admission types, we compared length of stay, cost, and readmission within 30 days to the hospital or ED. KEY RESULTS: Based on the admitting physician's assessment, we categorized the motivation for admission as strongly acuity-driven in 185 (62 %) admissions, moderately acuity-driven in 92 (31 %), and weakly acuity-driven in 20 (7 %). Per the physician surveys, 51 % of hospitalizations were strongly or moderately influenced by one or more non-medical factors, including lack of information about baseline conditions (23 %); inadequate access to outpatient specialty care (14 %); need for a diagnostic testing or procedure (12 %); a recent ED visit (11 %); and inadequate access to primary care (10 %). Compared with strongly-acuity driven admissions, admissions that were moderately or weakly acuity-driven were shorter and less costly but were associated with similar rates of ED (35 %) and hospital (27 %) readmission. CONCLUSIONS: Non-medical factors are influential in the admission decisions for many patients presenting to the emergency department. Moderately and weakly acuity-driven admissions may represent a feasible target for alternative care pathways.

Lung Ultrasound to Assist ICU Admission Decision-Making Process of COVID-19 Patients With Acute Respiratory Failure.

There is only low-certainty evidence on the use of predictive models to assist COVID-19 patient's ICU admission decision-making process. Accumulative evidence suggests that lung ultrasound (LUS) assessment of COVID-19 patients allows accurate bedside evaluation of lung integrity, with the added advantage of repeatability, absence of radiation exposure, reduced risk of virus dissemination, and low cost. Our goal is to assess the performance of a quantified indicator resulting from LUS data compared with standard clinical practice model to predict critical respiratory illness in the 24 hours following hospital admission. DESIGN: Prospective cohort study. SETTING: Critical Care Unit from University Hospital Purpan (Toulouse, France) between July 2020 and March 2021. PATIENTS: Adult patients for COVID-19 who were in acute respiratory failure (ARF), defined as blood oxygen saturation as measured by pulse oximetry less than 90% while breathing room air or respiratory rate greater than or equal to 30 breaths/min at hospital admission. Linear multivariate models were used to identify factors associated with critical respiratory illness, defined as death or mild/severe acute respiratory distress syndrome (Pao2/Fio2 < 200) in the 24 hours after patient's hospital admission. INTERVENTION: LUS assessment. MEASUREMENTS AND MAIN RESULTS: One hundred and forty COVID-19 patients with ARF were studied. This cohort was split into two independent groups: learning sample (first 70 patients) and validation sample (last 70 patients). Interstitial lung water, thickening of the pleural line, and alveolar consolidation detection were strongly associated with patient's outcome. The LUS model predicted more accurately patient's outcomes than the standard clinical practice model (DeLong test: Testing: z score = 2.50, p value = 0.01; Validation: z score = 2.11, p value = 0.03). CONCLUSIONS: LUS assessment of COVID-19 patients with ARF at hospital admission allows a more accurate prediction of the risk of critical respiratory illness than standard clinical practice. These results hold the promise of improving ICU resource allocation process, particularly in the case of massive influx of patients or limited resources, both now and in future anticipated pandemics.

Evaluation of angiogenic factors in the decision to admit women with suspected preeclampsia.

OBJECTIVE: To compare outcomes, specifically development of preeclampsia with severe features (sPE), between angiogenic biomarker-based admission and admission based on routine clinical care. STUDY DESIGN: This secondary analysis of a prospective study evaluated soluble fms-like tyrosine kinase-1 (sFlt1)/placental growth factor (PlGF) ratio in women presenting to triage for preeclampsia evaluation. Biomarkers levels were measured in samples collected from triage and analyzed retrospectively after outcomes were achieved. For this analysis patients would be hypothetically assigned to 'discharged' with a sFlt1/PlGF ratio ≤ 38 and 'admitted' with a sFlt1/PlGF ratio > 85. Development of sPE and other outcomes were then compared using the biomarker and clinical criteria for admission. RESULTS: 459 patients were included in this analysis. Using biomarker criteria, a larger proportion of patients were hypothetically discharged (67.8% vs 51.0%, p < 0.0001). A larger proportion of patients 'admitted' with a high biomarker level developed sPE (69.5% vs 40.9%, p < 0.0001). A sFlt1/PlGF ratio ≤ 38 had a negative predictive value of 96.8% for development of sPE within two weeks. CONCLUSION: Assessment of angiogenic biomarkes that 'discharges' patients with a low sFlt1/PlGF ratio and 'admits' patients with high ratio could result in reduced admissions and increased admission of patients at risk for developing sPE. Randomized trials are needed to determine the effectiveness of angiogenic biomarker use in decision making in a triage setting among women with suspected preeclampsia.

The Impact of Step-Down Unit Care on Patient Outcomes After ICU Discharge.

OBJECTIVES: To examine whether and how step-down unit admission after ICU discharge affects patient outcomes. DESIGN: Retrospective study using an instrumental variable approach to remove potential biases from unobserved differences in illness severity for patients admitted to the step-down unit after ICU discharge. SETTING: Ten hospitals in an integrated healthcare delivery system in Northern California. PATIENTS: Eleven-thousand fifty-eight episodes involving patients who were admitted via emergency departments to a medical service from July 2010 to June 2011, were admitted to the ICU at least once during their hospitalization, and were discharged from the ICU to the step-down unit or the ward. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using congestion in the step-down unit as an instrumental variable, we quantified the impact of step-down unit care in terms of clinical and operational outcomes. On average, for ICU patients with lower illness severity, we found that availability of step-down unit care was associated with an absolute decrease in the likelihood of hospital readmission within 30 days of 3.9% (95% CI, 3.6-4.1%). We did not find statistically significant effects on other outcomes. For ICU patients with higher illness severity, we found that availability of step-down unit care was associated with an absolute decrease in in-hospital mortality of 2.5% (95% CI, 2.3-2.6%), a decrease in remaining hospital length-of-stay of 1.1 days (95% CI, 1.0-1.2 d), and a decrease in the likelihood of ICU readmission within 5 days of 3.6% (95% CI, 3.3-3.8%). CONCLUSIONS: This study shows that there exists a subset of patients discharged from the ICU who may benefit from care in an step-down unit relative to that in the ward. We found that step-down unit care was associated with statistically significant improvements in patient outcomes especially for high-risk patients. Our results suggest that step-down units can provide effective transitional care for ICU patients.