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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Main Authors: Niels K. Rathlev, Paul Visintainer, Joseph Schmidt, Joeli Hettler, Vanna Albert, Haiping Li
Format: Article
Language:English
Published: eScholarship Publishing, University of California 2020-08-01
Series:Western Journal of Emergency Medicine
Online Access:https://escholarship.org/uc/item/0xr732bm
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spelling 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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