Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department
Introduction: Delays in patient flow in the emergency department (ED) result in patients leaving without being seen (LWBS). This compromises patient experience and quality of care. Our primary goal was to develop a predictive model by evaluating associations between patients LWBS and ED process meas...
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doaj-2018f9b295f1495abfd5cf4024f976fe2020-11-25T02:51:20ZengeScholarship Publishing, University of CaliforniaWestern Journal of Emergency Medicine1936-90182020-08-0121510.5811/westjem.2020.6.47084wjem-21-1218Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency DepartmentNiels K. Rathlev0Paul Visintainer1Joseph Schmidt2Joeli Hettler3Vanna Albert4Haiping Li5University of Massachusetts Medical School – Baystate, Department of Emergency Medicine, Springfield, MassachusettsUniversity of Massachusetts Medical School – Baystate, Department of Epidemiology and Biostatistics Core, Springfield, MassachusettsUniversity of Massachusetts Medical School – Baystate, Department of Emergency Medicine, Springfield, MassachusettsUniversity of Massachusetts Medical School – Baystate, Department of Emergency Medicine, Springfield, MassachusettsUniversity of Massachusetts Medical School – Baystate, Department of Emergency Medicine, Springfield, MassachusettsUniversity of Massachusetts Medical School – Baystate, Department of Emergency Medicine, Springfield, MassachusettsIntroduction: Delays in patient flow in the emergency department (ED) result in patients leaving without being seen (LWBS). This compromises patient experience and quality of care. Our primary goal was to develop a predictive model by evaluating associations between patients LWBS and ED process measures and patient characteristics. Methods: This was a cross-sectional study in a 95,000 annual visit adult ED comparing patients LWBS, with controls. Data were drawn from four seasonally adjusted four-week periods (30,679 total visits). Process measures included 1) arrivals per hour; 2) “door-to-provider” time; and the numbers of 3) patients in the waiting room; 4) boarding ED patients waiting for an inpatient bed; 5) providers and nurses (RN); and 6) patients per RN. Patient characteristics collected included 1) age; 2) gender; 3) race/ethnicity; 4) arrival mode (walk-in or via emergency medical services [EMS]); and 5) acuity based on Emergency Severity Index (ESI). Univariable analyses included t-tests and Pearson’s chi-square tests. We split the data randomly into derivation and validation cohorts. We used backward selection to develop the final derivation model, and factors with a p-value ≤ 0.05 were retained. Estimates were applied to the validation cohort and measures of discrimination (receiver operating characteristic) and model fit were assessed. Results: In the final model, the odds of LWBS increased with the number of patients in the waiting room (odds ratio [OR] 1.05; 95% confidence interval [CI], 1.03 to 1.06); number of boarding patients (OR 1.02; 95% CI, 1.01 to 1.03); arrival rate (OR 1.04; 95% CI, 1.02 to 1.05) and longer “door-to-provider” times (test of linear trend in the adjusted OR was p = 0.002). Patient characteristics associated with LWBS included younger age (OR 0.98; 95% CI, 0.98 to 0.99), and lower acuity (higher ESI category) (OR 2.01; 95% CI, 1.84 to 2.20). Arrival by EMS was inversely associated with LWBS (OR 0.29; 0.23 to 0.36). The area under the curve for the final model in the validation cohort was 0.85 (95% CI, 0.84 to 0.86). There was good agreement between the observed and predicted risk. Conclusion: Arrival rate, “door-to-provider time,” and the numbers of patients in the waiting room and ED boarders are all associated with patients LWBS.https://escholarship.org/uc/item/0xr732bm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Niels K. Rathlev Paul Visintainer Joseph Schmidt Joeli Hettler Vanna Albert Haiping Li |
spellingShingle |
Niels K. Rathlev Paul Visintainer Joseph Schmidt Joeli Hettler Vanna Albert Haiping Li Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department Western Journal of Emergency Medicine |
author_facet |
Niels K. Rathlev Paul Visintainer Joseph Schmidt Joeli Hettler Vanna Albert Haiping Li |
author_sort |
Niels K. Rathlev |
title |
Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department |
title_short |
Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department |
title_full |
Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department |
title_fullStr |
Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department |
title_full_unstemmed |
Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department |
title_sort |
patient characteristics and clinical process predictors of patients leaving without being seen from the emergency department |
publisher |
eScholarship Publishing, University of California |
series |
Western Journal of Emergency Medicine |
issn |
1936-9018 |
publishDate |
2020-08-01 |
description |
Introduction: Delays in patient flow in the emergency department (ED) result in patients leaving without being seen (LWBS). This compromises patient experience and quality of care. Our primary goal was to develop a predictive model by evaluating associations between patients LWBS and ED process measures and patient characteristics. Methods: This was a cross-sectional study in a 95,000 annual visit adult ED comparing patients LWBS, with controls. Data were drawn from four seasonally adjusted four-week periods (30,679 total visits). Process measures included 1) arrivals per hour; 2) “door-to-provider” time; and the numbers of 3) patients in the waiting room; 4) boarding ED patients waiting for an inpatient bed; 5) providers and nurses (RN); and 6) patients per RN. Patient characteristics collected included 1) age; 2) gender; 3) race/ethnicity; 4) arrival mode (walk-in or via emergency medical services [EMS]); and 5) acuity based on Emergency Severity Index (ESI). Univariable analyses included t-tests and Pearson’s chi-square tests. We split the data randomly into derivation and validation cohorts. We used backward selection to develop the final derivation model, and factors with a p-value ≤ 0.05 were retained. Estimates were applied to the validation cohort and measures of discrimination (receiver operating characteristic) and model fit were assessed. Results: In the final model, the odds of LWBS increased with the number of patients in the waiting room (odds ratio [OR] 1.05; 95% confidence interval [CI], 1.03 to 1.06); number of boarding patients (OR 1.02; 95% CI, 1.01 to 1.03); arrival rate (OR 1.04; 95% CI, 1.02 to 1.05) and longer “door-to-provider” times (test of linear trend in the adjusted OR was p = 0.002). Patient characteristics associated with LWBS included younger age (OR 0.98; 95% CI, 0.98 to 0.99), and lower acuity (higher ESI category) (OR 2.01; 95% CI, 1.84 to 2.20). Arrival by EMS was inversely associated with LWBS (OR 0.29; 0.23 to 0.36). The area under the curve for the final model in the validation cohort was 0.85 (95% CI, 0.84 to 0.86). There was good agreement between the observed and predicted risk. Conclusion: Arrival rate, “door-to-provider time,” and the numbers of patients in the waiting room and ED boarders are all associated with patients LWBS. |
url |
https://escholarship.org/uc/item/0xr732bm |
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