Simulating emergency patient flow during the COVID-19 pandemic

The accurate forecast of radiology emergency patient flow is of great importance to optimize appointment scheduling decisions. This study used a multi-model approach to forecast daily radiology emergency patient flow with consideration of different patient sources. We constructed six linear and nonlinear models by considering the lag effects and corresponding time factors. The autoregressive integrated moving average and least absolute shrinkage and selection operator (Lasso) were selected from the category of linear models, whereas linear-and-radial support vector regression models, random forests and adaptive boosting were chosen from the category of nonlinear models. The models were applied to 4-year daily emergency visits data in the radiology department of West China Hospital in Chengdu, China. The mean absolute percentage error of six models ranged from 8.56 to 9.36 percent for emergency department patients, whereas it varied from 10.90 to 14.39 percent for ward patients. The best-performing model for total radiology visits was Lasso, which yielded a mean absolute percentage error of 7.06 percent. The arrival patterns of emergency department and total radiology emergency patient flows could be modeled by linear processes. By contrast, the nonlinear model performed best for ward patient flow. These findings will benefit hospital managers in managing efficient patient flow, thus improving service quality and increasing patient satisfaction.

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71: The Race for Improved Emergency Patient Flow: A Pilot Project in a Large Canadian Community ED

Annals of Emergency Medicine ◽

10.1016/j.annemergmed.2008.01.038 ◽

2008 ◽

Vol 51 (4) ◽

pp. 492

Author(s):

A. Grunfeld ◽

P. McElheran ◽

M. Cloutier

Keyword(s):

Patient Flow ◽

Pilot Project ◽

Emergency Patient

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Dental Emergencies Management in COVID-19 Pandemic Peak: A Cohort Study

Journal of Dental Research ◽

10.1177/0022034521990314 ◽

2021 ◽

Vol 100 (4) ◽

pp. 352-360

Author(s):

J. Beauquis ◽

A.E. Petit ◽

V. Michaux ◽

V. Sagué ◽

S. Henrard ◽

...

Keyword(s):

Emergency Management ◽

Pain Control ◽

Management Strategy ◽

Patient Flow ◽

Symptom Relief ◽

Emergency Admission ◽

Patient Admission ◽

Emergency Patient ◽

Data Set

Due to the global coronavirus disease 2019 pandemic, the high risk of cross-contamination and the overload of hospital facilities have resulted in a real urgency for restricting dental emergency patient flow. In this context, the objectives of the current work were to 1) measure the ability of a triage-based management strategy to limit patient admission and 2) evaluate the success rate of both on-site and remote emergency management regarding symptom relief and pain control over a 1-mo period. We included all patients contacting the dental medicine department for an emergency consultation during the lockdown, between April 1 and April 30, 2020 ( N = 570). Following a telephone consultation and based on preestablished admission guidelines, a decision was made at baseline (T0) to either admit the patient for treatment or perform remote management by providing advice and/or drug prescription. Patients were then followed up systematically at 1 wk and 1 mo. Management failure was defined as the need for emergency admission for patients managed remotely since T0 and for new emergency admission for those admitted at T0. The global follow-up rate of patients with a complete data set was 91.4% ( N = 521). Of included patients, 49.3% could be managed without admission for emergency reasons for 1 mo. The proportion of successful management was 71.8% and 90.2% at 1 mo for remote and on-site management, respectively. To conclude, the proposed triage-based emergency management strategy with systematic follow-up was a good compromise between limiting patient admission and ensuring effective symptom relief and pain control. The strategy can be useful in situations where regulation of the emergency patient flow is required.

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A hybrid ARIMA-SVR approach for forecasting emergency patient flow

Journal of Ambient Intelligence and Humanized Computing ◽

10.1007/s12652-018-1059-x ◽

2018 ◽

Vol 10 (8) ◽

pp. 3315-3323 ◽

Cited By ~ 4

Author(s):

Yumeng Zhang ◽

Li Luo ◽

Jianchao Yang ◽

Dunhu Liu ◽

Ruixiao Kong ◽

...

Keyword(s):

Patient Flow ◽

Emergency Patient

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Redesigning emergency patient flow with timely quality care at the Alfred

Emergency Medicine Australasia ◽

10.1111/1742-6723.12338 ◽

2015 ◽

Vol 27 (1) ◽

pp. 35-41 ◽

Cited By ~ 12

Author(s):

Judy Lowthian ◽

Andrea Curtis ◽

Lahn Straney ◽

Amy McKimm ◽

Martin Keogh ◽

...

Keyword(s):

Patient Flow ◽

Quality Care ◽

Emergency Patient

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Patient Flow in an ICU

SSRN Electronic Journal ◽

10.2139/ssrn.1117672 ◽

2008 ◽

Cited By ~ 3

Author(s):

Gregory Dobson ◽

Hsiao-Hui Lee ◽

Edieal J. Pinker

Keyword(s):

Patient Flow

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A Simulation Model to Evaluate the Patient Flow in an Intensive Care Unit Under Different Levels of Specialization

SSRN Electronic Journal ◽

10.2139/ssrn.3740472 ◽

2020 ◽

Author(s):

Andres Alban ◽

Stephen E. Chick ◽

Oleksandra Lvova ◽

Danielle Sent

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Simulation Model ◽

Patient Flow ◽

Different Levels

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Introduction of Wireless Buzzer to Improve Efficiency in Gynecology Triage (Preprint)

10.2196/preprints.19287 ◽

2020 ◽

Author(s):

Nicholas Mark Stansbury ◽

Erin Nelson

Keyword(s):

Medical Students ◽

Nurse Practitioners ◽

Nursing Staff ◽

Internal Control ◽

Patient Flow ◽

Low Cost ◽

Work Flow ◽

Optimal Time ◽

Nursing Experience ◽

Asking Questions

BACKGROUND Current workflow in GYN triage has medical students interviewing patients after triage by nursing staff. The optimal time to initiate patient contact is unclear. This confusion has led to duplication of questions to patients, interruptions for nurses and fewer patient encounters for students. OBJECTIVE Determine if a restaurant-style buzzer can streamline workflow in gynecology (GYN) triage. METHODS A Plan-Do-Study-Act approach was used. Stakeholders were medical students, nurses, Nurse Practitioners and physicians. Factors contributing to workflow slowdown: students re-asking questions of patients, interruption of nursing staff, confusion about optimal patient flow. The net result was fewer interviews completed by students. The project was introduced during clerkship orientation. Buzzers were provided on weeks 1, 3, 5 of the rotation. Weeks 2, 4, 6 no buzzers were provided as an internal control. After each clerkship, students received a survey assessing key areas of waste and workflow disruption. A focus group with ten nurses was also conducted. RESULTS From February-July 2019, 30/45 surveys were completed (66%) 1. Very difficult/difficult to know when to begin the encounter: 90% without; 21.4% with buzzer p<.001 2. Students re-asking questions: very often/often 96.7% without; 14.8% with buzzer p<.001 3. Nursing staff interruptions: 76.7% very often/often without; 18.5% with buzzer p<.001 4. The odds of interviewing 5 or more patients per shift are ~10X greater using the buzzer χ²=14.2; p<.001 CONCLUSIONS The 10 nurses interviewed unanimously favored the use of the buzzer. Introduction of a simple, low-cost restaurant-style buzzer improved triage work-flow, student and nursing experience.

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