Improving service quality by understanding emergency department flow: a White Paper and position statement prepared for the American Academy of Emergency Medicine

Patient flow problems affecting in-patient spinal cord injury rehabilitation in the Netherlands

STUDY DESIGN

Prospective cohort study.

OBJECTIVES

To describe barriers to admission to and discharge from an inpatient rehabilitation unit for patients with newly acquired spinal cord injury or disease (SCI/D) and to identify modifiable factors whereby patient flow can be optimized.

SETTING

Netherlands.

METHODS

In-patients with newly acquired SCI/D referred to a rehabilitation centre in the Netherlands between December 2018 and December 2019 were included. Demographic, clinical characteristics and information about waiting days and causes of delay were recorded. Descriptive analysis was used.

RESULTS

In total, 105 patients were included; 33 patients (31%) were female, mean age was 59 years, 60% had a non-traumatic SCI/D, 42% of the SCI/D were tetraplegia and 62% were AIS D at referral. No significant differences in demographic or clinical characteristics were found between patients with and without a barrier to admission. Most common admission barriers were bed availability and capacity of nursing and other health staff. The most frequent discharge barriers were delay in care approval, lack of availability of nursing home places and waiting for home modifications.

CONCLUSION

Most frequent admission barriers were availability of beds and staffing capacity; most discharge barriers were problems with home modifications, waiting for care approval or a nursing home place. Recommendations for reducing these barriers are recognizing a potential problem at an early stage, timely communication with patient and/or family about options for discharge, while simultaneously initiating a home modification plan and exploring temporary accommodation options.

Probabilistic prediction of arrivals and hospitalizations in emergency departments in Île-de-France

BACKGROUND

Forecasts of future demand is foundational for effective resource allocation in emergency departments (EDs). As ED demand is inherently variable, it is important for forecasts to characterize the range of possible future demand. However, extant research focuses primarily on producing point forecasts using a wide variety of prediction algorithms. In this study, our objective is to generate point and interval predictions that accurately characterize the variability in ED demand using ensemble methods that combine predictions from multiple base algorithms based on their empirical performance.

METHODS

Data consisted in daily arrivals and subsequent hospitalizations at 72 emergency departments in Île-de-France from 2014-2018. Additional explanatory variables were collected including public and school holidays, meteorological variables, and public health trends. One-day ahead point and 80% interval predictions of arrivals and hospitalizations were produced by predicting the 10%, 50%, and 90% quantiles of the forecast distribution. Quantile prediction algorithms included methods such as ARIMAX, variations of random forests, and generalized additive models. Ensemble predictions were then formed using Exponentially Weighted Averaging, Bernstein Online Aggregation, and Super Learning. Prediction intervals were post-processed using Adaptive Conformal Inference techniques. Point predictions were evaluated by their Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE), and 80% interval predictions by their empirical coverage and mean interval width.

RESULTS

For point forecasts, ensemble methods achieved lower average MAE and MAPE than any of the base algorithms. All of the base algorithms and ensemble methods yielded prediction intervals with near optimal empirical coverage after conformalization. For hospitalizations, the shortest mean interval widths were achieved by the ensemble methods.

CONCLUSIONS

Ensemble methods yield joint point and prediction intervals that adapt to individual EDs and achieve better performance than individual algorithms. Conformal inference techniques improve the performance of the prediction intervals.

Comprehensive Risk Analysis of Emergency Medical Response Systems in Serbian Healthcare: Assessing Systemic Vulnerabilities in Disaster Preparedness and Response

BACKGROUND/OBJECTIVES

Emergency Medical Response Systems (EMRSs) play a vital role in delivering medical aid during natural and man-made disasters. This quantitative research delves into the analysis of risk and effectiveness within Serbia's Emergency Medical Services (EMS), with a special emphasis on how work organization, resource distribution, and preparedness for mass casualty events contribute to overall disaster preparedness.

METHODS

The study was conducted using a questionnaire consisting of 7 sections and a total of 88 variables, distributed to and collected from 172 healthcare institutions (Public Health Centers and Hospitals). Statistical methods, including Pearson's correlation, multivariate regression analysis, and chi-square tests, were rigorously applied to analyze and interpret the data.

RESULTS

The results from the multivariate regression analysis revealed that the organization of working hours (β = 0.035) and shift work (β = 0.042) were significant predictors of EMS organization, explaining 1.9% of the variance (R2 = 0.019). Furthermore, shift work (β = -0.045) and working hours (β = -0.037) accounted for 2.0% of the variance in the number of EMS points performed (R2 = 0.020). Also, the availability of ambulance vehicles (β = 0.075) and financial resources (β = 0.033) explained 4.1% of the variance in mass casualty preparedness (R2 = 0.041). When it comes to service area coverage, the regression results suggest that none of the predictors were statistically significant. Based on Pearson's correlation results, there is a statistically significant correlation between the EMS organization and several key variables such as the number of EMS doctors (p = 0.000), emergency medicine specialists (p = 0.000), etc. Moreover, the Chi-square test results reveal statistically significant correlations between EMS organization and how EMS activities are conducted (p = 0.001), the number of activity locations (p = 0.005), and the structure of working hours (p = 0.001).

CONCLUSIONS

Additionally, the results underscore the necessity for increased financial support, standardized protocols, and enhanced intersectoral collaboration to strengthen Serbia's EMRS and improve overall disaster response effectiveness. Based on these findings, a clear roadmap is provided for policymakers, healthcare administrators, and EMS personnel to prioritize strategic interventions and build a robust emergency medical response system.

Mapping the processes and information flows of a prehospital emergency care system in Rwanda: a process mapping exercise

OBJECTIVE

A vital component of a prehospital emergency care system is getting an injured patient to the right hospital at the right time. Process and information flow mapping are recognised methods to show where efficiencies can be made. We aimed to understand the process and information flows used by the prehospital emergency service in transporting community emergencies in Rwanda in order to identify areas for improvement.

DESIGN

Two facilitated process/information mapping workshops were conducted. Process maps were produced in real time during discussions and shared with participants for their agreement. They were further validated by field observations.

SETTING

The study took place in two prehospital care settings serving predominantly rural and predominantly urban patients.

PARTICIPANTS

24 healthcare professionals from various cadres. Field observations were done on 49 emergencies across both sites.

RESULTS

Two maps were produced, and four main process stages were described: (1) call triage by the dispatch/call centre team, (2) scene triage by the ambulance team, (3) patient monitoring by the ambulance team on the way to the health facility and (4) handover process at the health facility. The first key finding was that the rural site had multiple points of entry into the system for emergency patients, whereas the urban system had one point of entry (the national emergency number); processes were otherwise similar between sites. The second was that although large amounts of information were collected to inform decision-making about which health facility to transfer patients to, participants found it challenging to articulate the intellectual process by which they used this to make decisions; guidelines were not used for decision-making.

DISCUSSION

We have identified several areas of the prehospital care processes where there can be efficiencies. To make efficiencies in the decision-making process and produce a standard approach for all patients will require protocolising care pathways.

Low Back Pain: Utilization of Urgent Cares Relative to Emergency Departments

STUDY DESIGN/SETTING

Retrospective study.

OBJECTIVE

To understand why patients utilize emergency departments (EDs) versus urgent care centers for low back pain (LBP).

SUMMARY OF BACKGROUND DATA

LBP is a common reason for ED visits. In the setting of trauma or recent surgery, the resources of EDs may be needed. However, urgent care centers may be appropriate for other cases.

MATERIALS AND METHODS

Adult patients below 65 years of age presenting to the ED or urgent care on the day of diagnosis of LBP were identified from the 2019 PearlDiver M151 administrative database. Exclusion criteria included history of radiculopathy or sciatica, spinal surgery, spinal cord injury, other traumatic, neoplastic, or infectious diagnoses in the 90 days prior, or Medicare insurance. Patient age, sex, Elixhauser comorbidity index, geographic region, insurance, and management strategies were extracted. Factors associated with urgent care relative to ED utilization were assessed using multivariable analysis.

RESULTS

Of 356,284 LBP patients, ED visits were identified for 345,390 (96.9%) and urgent care visits for 10,894 (3.1%). Factors associated with urgent care use relative to the ED were: geographic region [relative to Midwest; Northeast odds ratio (OR): 5.49, South OR: 1.54, West OR: 1.32], insurance (relative to Medicaid; commercial OR: 4.06), lower Elixhauser comorbidity index (OR: 1.28 per two-point decrease), and higher age (OR: 1.10 per decade), female sex (OR: 1.09), and use of advanced imaging (OR: 0.08) within 1 week ( P <0.001 for all).

CONCLUSIONS

Most patients presenting for a first diagnosis of isolated LBP went to the ED relative to urgent care. The greatest drivers of urgent care versus ED utilization for LBP were insurance type and geographic region. Utilization of advanced imaging was higher among ED patients, but rates of surgical intervention were similar between those seen in the ED and urgent care.

Transport Rates and Prehospital Intervals for an EMS Telemedicine Intervention

INTRODUCTION

Emergency medical services (EMS) facilitated telemedicine encounters have been proposed as a strategy to reduce transports to hospitals for patients who access the 9-1-1 system. It is unclear which patient impressions are most likely able to be treated in place. It is also unknown if the increased time spent facilitating the telemedicine encounter is offset by the time saved from reducing the need for transport. The objective of this study was to determine the association between the impressions of EMS clinicians of the patients' primary problems and transport avoidance, and to describe the effects of telemedicine encounters on prehospital intervals.

METHODS

This was a retrospective review of EMS records from two commercial EMS agencies in New York and Tennessee. For each EMS call where a telemedicine encounter occurred, a matched pair was identified. Clinicians' impressions were mapped to the corresponding category in the International Classification of Primary Care, 2nd edition (ICPC-2). Incidence and rates of transport avoidance for each category were determined. Prehospital interval was calculated as the difference between the time of ambulance dispatch and back-in-service time.

RESULTS

Of the 463 prehospital telemedicine evaluations performed from March 2021 to April 2022, 312 (67%) avoided transports to the hospital. Respiratory calls were most likely to result in transport avoidance (p = 0.018); no other categories had statistically significant transport rates. Four hundred sixty-one (99.6%) had matched pairs identified and were included in the analysis. When compared to the matched pair, telemedicine without transport was associated with a prehospital interval reduction in 68% of the cases with a median reduction of 16 min; this is significantly higher than telemedicine with transport when compared to the matched pair with a median interval increase in 27 min. Regardless of transport status, the prehospital interval was a median of 4 min shorter for telemedicine encounters than non-telemedicine encounters (p = 0.08).

CONCLUSION

In this study, most telemedicine evaluations resulted in ED transport avoidance, particularly for respiratory issues. Telemedicine interventions were associated with a median four-minute decrease in prehospital interval per call. Future research should investigate the long-term effects of telemedicine on patient outcomes.

What Factors Increase Odds of Long-Stay Delayed Discharge in Alternate Level of Care Patients?

OBJECTIVE

The objective of this study was to determine the factors that increase the odds of long-stay delayed discharge in alternate level of care (ALC) patients using data collected from the Ontario Wait Time Information System (WTIS) database.

DESIGN

Retrospective cohort study utilizing data from Niagara Health's WTIS database. WTIS includes individuals admitted to any of the Niagara Health sites that have been designated as ALC.

SETTING AND PARTICIPANTS

Sample consisted of 16,429 ALC patients who received care in Niagara Health hospitals from September 2014 to September 2019 and were recorded in the WTIS database.

METHODS

ALC designation of 30 or more days was used as the threshold for a long-stay delayed discharge. This study used binary logistic regression modeling to analyze sex, age, admission source, and discharge destination as well needs/barriers requirements to assess the likelihood of a long-stay delayed discharge among acute care (AC) and post-acute care (PAC) patients given the presence of each variable. Sample sizes calculations and receiver operating characteristic curves were used to verify the validity of the regression model.

RESULTS

Overall, 10.2% of the sample were considered long-stay ALC patients. Both AC and PAC long-stay ALC patients were more likely to be male [OR = 1.23, (1.06-1.43); OR = 1.28, (1.03-1.60)] and have a discharge destination of a long-term care bed [OR = 28.68, (22.83-36.04); OR = 6.22, (4.75-8.15)]. AC patients had bariatric [OR = 7.16, (3.45-14.83)], behavioral [OR = 1.89, (1.22-2.91)], infection (isolation) [OR = 2.31, (1.63-3.28)], and feeding [OR = 6.38, (1.82-22.30)] barriers hindering discharge. PAC patients had no significant barriers hindering patient discharge.

CONCLUSIONS AND IMPLICATIONS

Shifting the focus from ALC patient designation to short- vs long-stay ALC patients allowed this study to focus on the subset of patients that are disproportionately affecting delayed discharges. Understanding the importance of specialized patient requirements in addition to clinical factors can help hospitals become more prepared in preventing delayed discharges.

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study

BACKGROUND

Large language model (LLM)-based artificial intelligence chatbots direct the power of large training data sets toward successive, related tasks as opposed to single-ask tasks, for which artificial intelligence already achieves impressive performance. The capacity of LLMs to assist in the full scope of iterative clinical reasoning via successive prompting, in effect acting as artificial physicians, has not yet been evaluated.

OBJECTIVE

This study aimed to evaluate ChatGPT's capacity for ongoing clinical decision support via its performance on standardized clinical vignettes.

METHODS

We inputted all 36 published clinical vignettes from the Merck Sharpe & Dohme (MSD) Clinical Manual into ChatGPT and compared its accuracy on differential diagnoses, diagnostic testing, final diagnosis, and management based on patient age, gender, and case acuity. Accuracy was measured by the proportion of correct responses to the questions posed within the clinical vignettes tested, as calculated by human scorers. We further conducted linear regression to assess the contributing factors toward ChatGPT's performance on clinical tasks.

RESULTS

ChatGPT achieved an overall accuracy of 71.7% (95% CI 69.3%-74.1%) across all 36 clinical vignettes. The LLM demonstrated the highest performance in making a final diagnosis with an accuracy of 76.9% (95% CI 67.8%-86.1%) and the lowest performance in generating an initial differential diagnosis with an accuracy of 60.3% (95% CI 54.2%-66.6%). Compared to answering questions about general medical knowledge, ChatGPT demonstrated inferior performance on differential diagnosis (β=-15.8%; P<.001) and clinical management (β=-7.4%; P=.02) question types.

CONCLUSIONS

ChatGPT achieves impressive accuracy in clinical decision-making, with increasing strength as it gains more clinical information at its disposal. In particular, ChatGPT demonstrates the greatest accuracy in tasks of final diagnosis as compared to initial diagnosis. Limitations include possible model hallucinations and the unclear composition of ChatGPT's training data set.

Development of a machine learning-based clinical decision support system to predict clinical deterioration in patients visiting the emergency department

This study aimed to develop a machine learning-based clinical decision support system for emergency departments based on the decision-making framework of physicians. We extracted 27 fixed and 93 observation features using data on vital signs, mental status, laboratory results, and electrocardiograms during emergency department stay. Outcomes included intubation, admission to the intensive care unit, inotrope or vasopressor administration, and in-hospital cardiac arrest. eXtreme gradient boosting algorithm was used to learn and predict each outcome. Specificity, sensitivity, precision, F1 score, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve were assessed. We analyzed 303,345 patients with 4,787,121 input data, resampled into 24,148,958 1 h-units. The models displayed a discriminative ability to predict outcomes (AUROC > 0.9), and the model with lagging 6 and leading 0 displayed the highest value. The AUROC curve of in-hospital cardiac arrest had the smallest change, with increased lagging for all outcomes. With inotropic use, intubation, and intensive care unit admission, the range of AUROC curve change with the leading 6 was the highest according to different amounts of previous information (lagging). In this study, a human-centered approach to emulate the clinical decision-making process of emergency physicians has been adopted to enhance the use of the system. Machine learning-based clinical decision support systems customized according to clinical situations can help improve the quality of care.

Increased Prehospital Emergency Medical Service Time Interval and Nontransport Rate of Patients With Fever Using Emergency Medical Services Before and After COVID-19 in Busan, Korea

BACKGROUND

In Korea, patients with fever have been preemptively isolated to isolation beds in the emergency department (ED) since the coronavirus disease 2019 (COVID-19) pandemic began. However, isolation beds were not always available, and transport delays or failure (nontransport), especially for infants, were reported in the media. Few studies have focused on delays and failure in transporting fever patients to the ED. Therefore, this study aimed to examine and compare the emergency medical service (EMS) time interval and nontransport rate of patients with fever using EMSs before and after COVID-19.

METHODS

This retrospective observational study analyzed the prehospital EMS time interval and nontransport rate of fever patients who contacted EMSs in Busan, South Korea, from March 1, 2019 to February 28, 2022, using emergency dispatch reports. All fever patients (≥ 37.5°C) who contacted EMSs during this study were included. The EMS time interval was defined as the time between the patient's EMS call and ED arrival time. Nontransport was defined as a case recorded as not being transported in the emergency dispatch reports. The study population of 2019 was compared to the population of 2020 and 2021 with the independent t-test, Mann-Whitney U test, and χ² test. As a subgroup, the EMS time intervals and nontransport rates of infants with fever were compared before and after COVID-19.

RESULTS

A total of 554,186 patients accessed the EMS during the study period, and 46,253 patients with fever were included. The EMS time interval (mean ± standard deviation, minutes) of fever patients was 30.9 ± 29.9 in 2019, 46.8 ± 127.8 in 2020 (P < 0.001) and 45.9 ± 34.0 in 2021 (P < 0.001). The nontransport rate (%) was 4.4 in 2019, 20.6 in 2020 (P < 0.001), and 19.5 in 2021 (P < 0.001). For infants with fever, the EMS time interval was 27.6 ± 10.8 in 2019, 35.1 ± 15.4 in 2020 (P < 0.001), and 42.3 ± 20.5 in 2021 (P < 0.001), and the nontransport rate (%) was 2.6 in 2019, 25.0 in 2020, and 19.7 in 2021.

CONCLUSION

After the emergence of COVID-19, in Busan, the EMS time interval of fever patients was delayed, and approximately 20% of fever patients were not transported. However, infants with fever had shorter EMS time intervals and higher nontransport rates than the overall study population. A comprehensive approach, including prehospital and hospital ED flow improvements, is required beyond increasing the number of isolation beds.

Agreement and prognostic accuracy of three ED vulnerability screeners: findings from a prospective multi-site cohort study

OBJECTIVES

To evaluate the agreement between three emergency department (ED) vulnerability screeners, including the InterRAI ED Screener, ER2, and PRISMA-7. Our secondary objective was to evaluate the discriminative accuracy of screeners in predicting discharge home and extended ED lengths-of-stay (> 24 h).

METHODS

We conducted a nested sub-group study using data from a prospective multi-site cohort study evaluating frailty in older ED patients presenting to four Quebec hospitals. Research nurses assessed patients consecutively with the three screeners. We employed Cohen's Kappa to determine agreement, with high-risk cut-offs of three and four for the PRISMA-7, six for the ER2, and five for the interRAI ED Screener. We used logistic regression to evaluate the discriminative accuracy of instruments, testing them in their dichotomous, full, and adjusted forms (adjusting for age, sex, and hospital academic status).

RESULTS

We evaluated 1855 older ED patients across the four hospital sites. The mean age of our sample was 84 years. Agreement between the interRAI ED Screener and the ER2 was fair (K = 0.37; 95% CI 0.33-0.40); agreement between the PRISMA-7 and ER2 was also fair (K = 0.39; 95% CI = 0.36-0.43). Agreement between interRAI ED Screener and PRISMA-7 was poor (K = 0.19; 95% CI 0.16-0.22). Using a cut-off of four for PRISMA-7 improved agreement with the ER2 (K = 0.55; 95% CI 0.51-0.59) and the ED Screener (K = 0.32; 95% CI 0.2-0.36). When predicting discharge home, the concordance statistics among models were similar in their dichotomous (c = 0.57-0.61), full (c = 0.61-0.64), and adjusted forms (c = 0.63-0.65), and poor for all models when predicting extended length-of-stay.

CONCLUSION

ED vulnerability scores from the three instruments had a fair agreement and were associated with important patient outcomes. The interRAI ED Screener best identifies older ED patients at greatest risk, while the PRISMA-7 and ER2 are more sensitive instruments.

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow

IMPORTANCE

Large language model (LLM) artificial intelligence (AI) chatbots direct the power of large training datasets towards successive, related tasks, as opposed to single-ask tasks, for which AI already achieves impressive performance. The capacity of LLMs to assist in the full scope of iterative clinical reasoning via successive prompting, in effect acting as virtual physicians, has not yet been evaluated.

OBJECTIVE

To evaluate ChatGPT's capacity for ongoing clinical decision support via its performance on standardized clinical vignettes.

DESIGN

We inputted all 36 published clinical vignettes from the Merck Sharpe & Dohme (MSD) Clinical Manual into ChatGPT and compared accuracy on differential diagnoses, diagnostic testing, final diagnosis, and management based on patient age, gender, and case acuity.

SETTING

ChatGPT, a publicly available LLM.

PARTICIPANTS

Clinical vignettes featured hypothetical patients with a variety of age and gender identities, and a range of Emergency Severity Indices (ESIs) based on initial clinical presentation.

EXPOSURES

MSD Clinical Manual vignettes.

MAIN OUTCOMES AND MEASURES

We measured the proportion of correct responses to the questions posed within the clinical vignettes tested.

RESULTS

ChatGPT achieved 71.7% (95% CI, 69.3% to 74.1%) accuracy overall across all 36 clinical vignettes. The LLM demonstrated the highest performance in making a final diagnosis with an accuracy of 76.9% (95% CI, 67.8% to 86.1%), and the lowest performance in generating an initial differential diagnosis with an accuracy of 60.3% (95% CI, 54.2% to 66.6%). Compared to answering questions about general medical knowledge, ChatGPT demonstrated inferior performance on differential diagnosis (β=-15.8%, p<0.001) and clinical management (β=-7.4%, p=0.02) type questions.

CONCLUSIONS AND RELEVANCE

ChatGPT achieves impressive accuracy in clinical decision making, with particular strengths emerging as it has more clinical information at its disposal.

The effects of an emergency department length-of-stay management system on severely ill patients' treatment outcomes

PURPOSE

This study aimed to compare the length of stay (LOS) and treatment outcomes based on the application and achievement of a newly developed emergency department (ED) LOS management system for severely ill patients.

METHODS

Data were retrospectively collected from electronic medical records (EMRs) for the system evaluation and research purpose. The study subjects are severely ill patients whose diagnosis codes are designated by the Ministry of Health and Welfare and who visited the ED of a tertiary hospital from January to December 2019. The control group (Group 1) refers to those who have neither applied nor achieved the goal (5 hours or less) of the ED LOS management system even after it was applied, and the experimental group (Group 2) refers to those who have achieved the 5-hour goal after applying the system.

RESULTS

A total of 2034 severely ill patients applied the ED LOS management system. Group 1 included 837 patients and Group 2 included 1197 patients. Thirty days in-hospital mortality corresponded to 10.6% in Group 1 and 6.6% in Group 2 (χ2 = 10.58, p = .001). The total duration of hospitalization was 14.66 ± 18.26 days in Group 1 and 10.19 ± 16.00 days in Group 2 (t = 9.03, p < .001). Six hundred forty-two patients (76.6%) in Group 1 were discharged to their home (normal discharge) and 979 patients (81.7%) were discharged to their home in Group 2, but the discharge-as-death rate was 14.1% in Group 1 and 7.5% in Group 2 (χ2 = 29.80, p < .001).

CONCLUSION

With the application and attainment of the ED LOS management system for severely ill patients, we have concluded the new system produced a lower LOS in the ED, 30 days in-hospital mortality, length of the hospitalization, mortality rate, and a higher rate of normal discharge.

Understanding the impacts of health information systems on patient flow management: A systematic review across several decades of research

Background

Patient flow describes the progression of patients along a pathway of care such as the journey from hospital inpatient admission to discharge. Poor patient flow has detrimental effects on health outcomes, patient satisfaction and hospital revenue. There has been an increasing adoption of health information systems (HISs) in various healthcare settings to address patient flow issues, yet there remains limited evidence of their overall impacts.

Objective

To systematically review evidence on the impacts of HISs on patient flow management including what HISs have been used, their application scope, features, and what aspects of patient flow are affected by the HIS adoption.

Methods

A systematic search for English-language, peer-review literature indexed in MEDLINE and EMBASE, CINAHL, INSPEC, and ACM Digital Library from the earliest date available to February 2022 was conducted. Two authors independently scanned the search results for eligible publications, and reporting followed the PRISMA guidelines. Eligibility criteria included studies that reported impacts of HIS on patient flow outcomes. Information on the study design, type of HIS, key features and impacts was extracted and analysed using an analytical framework which was based on domain-expert opinions and literature review.

Results

Overall, 5996 titles were identified, with 44 eligible studies, across 17 types of HIS. 22 studies (50%) focused on patient flow in the department level such as emergency department while 18 studies (41%) focused on hospital-wide level and four studies (9%) investigated network-wide HIS. Process outcomes with time-related measures such as ‘length of stay’ and ‘waiting time’ were investigated in most of the studies. In addition, HISs were found to address flow problems by identifying blockages, streamlining care processes and improving care coordination.

Conclusion

HIS affected various aspects of patient flow at different levels of care; however, how and why they delivered the impacts require further research.

Quality Improvement: Implementing Nurse Standard Work in Emergency Department Fast-Track Area to Reduce Patient Length of Stay

Introduction

The average length of stay of a fast-track area of a large urban hospital was excessively long, which affected the patient experience and the rate at which patients left without being seen. One approach to reducing average length of stay is to create nurse standard work. Nurse standard work was a defined set of process and procedures that reduce variability within a nurse’s workflow.

Methods

Nurse standard work was created by a team of nurses assisted by management engineering using lean methodology and A3 problem solving. Data were gathered about average length of stay and left without being seen for patients in the emergency department fast-track area of an urban emergency department from October 2018 to June 2020. This period includes 5 months before the intervention start, 4 months during nurse standard work implementation, 9 months using nurse standard work before the unit was repurposed during COVID-19, and 3 months during COVID-19.

Results

Nurse standard work helped reduce average length of stay in the emergency department fast-track area from 205 minutes before project initiation to 150.4 minutes in the 7 months after implementing nurse standard work. The time spent walking for supplies was reduced from 422 and 272 seconds before nurse standard work to 25 and 30 seconds for the nurse technician and nurse, respectively, after nurse standard work. Left without being seen was decreased from 4.7% in October of 2018 to 0.7% by March of 2020.

Discussion

Nurse standard work reduced the amount of time that nurses spent performing support tasks and reduced delays in providing patient care, which then allowed more time for nurses to interact directly with patients. Nurse standard work provides a clear task sequence that eliminates delays in treating patients, but it also allows for fast identification of delays that do occur and simplifies problem solving to eliminate reoccurrence of delays. Therefore, nurse standard work is an essential component of efforts to reduce patient average length of stay in health care processes and reduce left without being seen to the national standard of less than 2%.

A Qualitative Study of Factors Influencing Unsafe Work Behaviors Among Environmental Service Workers: Perspectives of Workers, and Safety Managers: The Case of Government Hospitals in Addis Ababa, Ethiopia

BACKGROUND

Environmental Service (EVS) is a term that refers to cleaning in healthcare facilities. EVS personnel are exposed to a variety of hazards, including physical, chemical, ergonomic, cognitive, and biological hazards that contribute to the development of diseases and disabilities. Recognizing the conditions that promote unsafe behavior is the first step in reducing such hazards. The purpose of this study was to (a) investigate the attitudes and perceptions of safety among employees and safety managers in Addis Ababa hospitals, and (b) figure out what factors inhibit healthy work behaviors.

METHODS

The data for this study was gathered using 2 qualitative data gathering methods: key informant interviews and individual in-depth interviews. About 25 personnel from 3 Coronavirus treatment hospitals were interviewed to understand more about the factors that make safe behavior challenging. The interviews were recorded, transcribed, and then translated into English. Open Code 4.02 was used for thematic analysis.

RESULTS

Poor safety management and supervision, a hazardous working environment, and employee perceptions, skills, and training levels were all identified as key factors in the preponderance of unsafe work behaviors among environmental service workers.

CONCLUSIONS

Different types of personal and environmental factors were reported to affect safe work behavior among environmental service personnel. Individual responsibility is vital in reducing or eliminating these risk factors for unsafe behaviors, but management's involvement in providing resources for safe work behavior is critical.

Queueing Problems in Emergency Departments: A Review of Practical Approaches and Research Methodologies

Problems related to patient scheduling and queueing in emergency departments are gaining increasing attention in theory, in the fields of operations research and emergency and healthcare services, and in practice. This paper aims to provide an extensive review of studies addressing queueing-related problems explicitly related to emergency departments. We have reviewed 229 articles and books spanning seven decades and have sought to organize the information they contain in a manner that is accessible and useful to researchers seeking to gain knowledge on specific aspects of such problems. We begin by presenting a historical overview of applications of queueing theory to healthcare-related problems. We subsequently elaborate on managerial approaches used to enhance efficiency in emergency departments. These approaches include bed management, fast-track, dynamic resource allocation, grouping/prioritization of patients, and triage approaches. Finally, we discuss scientific methodologies used to analyze and optimize these approaches: algorithms, priority models, queueing models, simulation, and statistical approaches.

The Association Between Abnormal Vital Signs and Mortality in the Emergency Department

Background

The emergency department (ED) receives patients from all over the world every day. Hence, using various triage scales to detect sick patients and the need for early admission are essential. Triage is a process used in the ED to prioritize patients requiring the most urgent care over those with minor injuries based on medical urgency and medical needs. These decisions may be based on patients’ chief complaints at the time of their ED visit and their vital signs. Vital signs, including blood pressure (BP), respiratory rate (RR), heart rate (HR), and body temperature, are necessary tools that are traditionally used in the ED during procedures such as triage and recognizing high-risk hospital inpatients. This study aimed to determine the relationship between abnormal vital signs and mortality in the ED.

Method and Material

This retrospective record review study was performed at the ED of King Abdulaziz University Hospital (KAUH). Altogether, 641 patients fulfilled our inclusion criteria. Data including patients’ demographics, vital signs, in-hospital mortality, triage level, and precipitating factors were collected.

Results

The mean age of the patients was 45.66 ± 18.43 years (69.3% females), and the majority of them had Canadian Triage and Acuity Scale (CTAS) level 3 (71.1%). The total number of in-hospital mortalities was 32 (5%). Lower systolic blood pressure (SBP) and diastolic blood pressure (DBP), high respiratory rates, and low oxygen saturation (O₂SAT) were significantly associated with high mortality rates.

Conclusion

Abnormal vital signs play a major role in determining patient prognosis and outcomes. Triage score systems should be adjusted and carefully studied in each center according to its population.

The Prioritization of Lean Techniques in Emergency Departments Using VIKOR and SAW Approaches

Background

Considering various researches were carried out to implement Lean techniques in healthcare centers, this study has tried to investigate how lean principles could be prioritized in the Emergency Department (ED) by comparing physicians and nurses viewpoints.

Methodology

In the first stage, relevant Lean techniques and several criteria to evaluate the ED performance were selected by reviewing the literature. Then, weight factors for each criterion were calculated using the Entropy method, and Lean techniques were compared and ranked via a questionnaire by which the physicians' and nurses' opinions were obtained separately. In the last stage, the final ranking of Lean techniques was done using VIKOR and SAW methods as two powerful means of Multi-Criteria Decision-Making (MCDM).

Results

Theory of Constraints (TOC) was selected as the most appropriate principle from the physicians' viewpoints by both decision-making methods. However, according to the nurses' opinions, Jiduka was the best approach by the VIKOR method, while with the SAW method, 5S was chosen as the most practical Lean technique.

Conclusion

This study has illustrated that although all Lean techniques are useable for ED, these techniques' prioritization has a key role in choosing the more suitable Lean approach. Moreover, it provides a chance for the emergency wards to keep down different costs and improve staff and patient satisfaction and the quality of treatment simultaneously.

Triage physicians in an academic emergency department: Impact on resident education

BACKGROUND

Overcrowding in emergency departments (EDs) in the United States has been linked to worse patient outcomes. Implementation of countermeasures such as a physician-in-triage (PIT) system have improved patient care and decreased wait times. The purpose of this study was to evaluate how a PIT system affects medical resident education in an academic ED.

METHODS

This was a retrospective observational comparison of resident metrics at a single-site, urban, academic ED before and after implementing a PIT system. Resident metrics of average emergency severity index (ESI), patients-per-hour, and in-training-examination scores were measured before and six months after the implementation of the PIT system.

RESULTS

In total, 18,231 patients were evaluated by all residents in the study period before PIT implementation compared to 17,008 in the study period following PIT implementation. The average ESI among patients evaluated by residents decreased from 3.00 to 2.68 (p < 0.01, 95% confidence interval [CI] = 0.31 to 0.33), while average resident patient-per-hour rate decreased from 1.41 to 1.32 (p < 0.01, 95% CI = 0.05 to 0.13] and ITE scores saw no statistically significant change of 76.11 to 78.26 (p = 0.26, 95% CI = -5.75 to 1.45). While these differences are statistically significant, they are likely not clinically significant.

CONCLUSIONS

Our implementation of PIT system at one academic medical center minimally increased the acuity and minimally decreased the number of patients that residents see. This suggested that in our center, a PIT program did not detract from ED resident clinical education. However, further research with alternative markers in multiple centers is needed.

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units

STUDY OBJECTIVE

This study aimed to develop and validate 2 machine learning models that use historical and current-visit patient data from electronic health records to predict the probability of patient admission to either an inpatient unit or ICU at each hour (up to 24 hours) of an emergency department (ED) encounter. The secondary goal was to provide a framework for the operational implementation of these machine learning models.

METHODS

Data were curated from 468,167 adult patient encounters in 3 EDs (1 academic and 2 community-based EDs) of a large academic health system from August 1, 2015, to October 31, 2018. The models were validated using encounter data from January 1, 2019, to December 31, 2019. An operational user dashboard was developed, and the models were run on real-time encounter data.

RESULTS

For the intermediate admission model, the area under the receiver operating characteristic curve was 0.873 and the area under the precision-recall curve was 0.636. For the ICU admission model, the area under the receiver operating characteristic curve was 0.951 and the area under the precision-recall curve was 0.461. The models had similar performance in both the academic- and community-based settings as well as across the 2019 and real-time encounter data.

CONCLUSION

Machine learning models were developed to accurately make predictions regarding the probability of inpatient or ICU admission throughout the entire duration of a patient's encounter in ED and not just at the time of triage. These models remained accurate for a patient cohort beyond the time period of the initial training data and were integrated to run on live electronic health record data, with similar performance.

Quantifying the impact of patient boarding on emergency department length of stay: All admitted patients are negatively affected by boarding

BACKGROUND

Patients boarding in the emergency department (ED) as a result of delays in bed placement are associated with increased morbidity and mortality. Prior literature on ED boarding does not explore the impact of boarding on patients admitted to the hospital from the ED. The objective of this study was to evaluate the impact of patient boarding on ED length of stay for all patients admitted to the hospital.

METHODS

This was an institutional review board-approved, retrospective review of all patients from January 1, 2015, through June 30, 2019, presenting to 2 large EDs in a single health system in Pennsylvania. Quantile regression models were created to estimate the impact of patients boarding in the ED on length of stay for all ED patients admitted to the hospital.

RESULTS

A total number of 466,449 ED encounters were analyzed across two EDs. At one ED, for every patient boarded, the median ED length of stay for all admitted patients increased by 14.0 minutes (P < 0.001). At the second ED, for every patient boarded in the ED, the median ED length of stay increased by 12.4 minutes (P < 0.001).

CONCLUSION

ED boarding impacts length of stay for all patients admitted through the ED and not just those admitted patients who are boarded. This study provides an estimate for the increased ED length of stay experienced by all patients admitted to the hospital as a function of patient boarding.

Emergency Department Overcrowding: A Retrospective Spatial Analysis and the Geocoding of Accesses. A Pilot Study in Rome

The overcrowding of first aid facilities creates considerable hardship and problems which have repercussions on patients’ wellbeing, the time needed for a diagnosis, and on the quality of the assistance. The basic objective of this contribution, based on the data collected by the Hospital Policlinico Umberto I in Rome (Lazio region, Italy), is to carry out a territorial screening of the municipality using GIS applications and spatial analyses aimed at reducing—in terms of triage—code white (inappropriate) attendances, after having identified the areas of greatest provenance of improperly used emergency room access. Working in a GIS environment and using functions for geocoding, we have tested an experimental model aimed at giving a close-up geographical-sanitary look at the situation: recognizing the territorial sectors in Rome which contribute to amplifying the Policlinico Umberto I emergency room overcrowding; leading up to an improvement of the situation; promoting greater awareness and knowledge of the services available on the territory, a closer relationship between patient and regular doctor (general practitioner, GP) or Local Healthcare Unit and a more efficient functioning of the emergency room. In particular, we have elaborated a “source” map from which derive all the others and it is a dot map on which all the codes white have been geolocalized on a satellite image through geocoding. We have produced three sets made up of three digital cartographic elaborations each, constructed on the census sections, the census areas and the sub-municipal areas, according to data aggregation, for absolute and relative values, and using different templates. Finally, following the same methodology and steps, we elaborated another dot map about all the codes red to provide another kind of information and input for social utility. In the near future, this system could be tested on a platform that spatially analyzes the emergency department (ED) accesses in near-real-time in order to facilitate the identification of critical territorial issues and intervene in a shorter time to regulate the influx of patients to the ED.

Maximum emergency department overcrowding is correlated with occurrence of unexpected cardiac arrest

Background

Emergency department overcrowding negatively impacts critically ill patients and could lead to the occurrence of cardiac arrest. However, the association between emergency department crowding and the occurrence of in-hospital cardiac arrest has not been thoroughly investigated. This study aimed to evaluate the correlation between emergency department occupancy rates and the incidence of in-hospital cardiac arrest.

Methods

A single-center, observational, registry-based cohort study was performed including all consecutive adult, non-traumatic in-hospital cardiac arrest patients between January 2014 and June 2017. We used emergency department occupancy rates as a crowding index at the time of presentation of cardiac arrest and at the time of maximum crowding, and the average crowding rate for the duration of emergency department stay for each patient. To calculate incidence rate, we divided the number of arrest cases for each emergency department occupancy period by accumulated time. The primary outcome is the association between the incidence of in-hospital cardiac arrest and emergency department occupancy rates.

Results

During the study period, 629 adult, non-traumatic cardiac arrest patients were enrolled in our registry. Among these, 187 patients experienced in-hospital cardiac arrest. Overall survival discharge rate was 24.6%, and 20.3% of patients showed favorable neurologic outcomes at discharge. Emergency department occupancy rates were positively correlated with in-hospital cardiac arrest occurrence. Moreover, maximum emergency department occupancy in the critical zone had the strongest positive correlation with in-hospital cardiac arrest occurrence (Spearman rank correlation ρ = 1.0, P < .01). Meanwhile, occupancy rates were not associated with the ED mortality.

Conclusion

Maximum emergency department occupancy was strongly associated with in-hospital cardiac arrest occurrence. Adequate monitoring and managing the maximum occupancy rate would be important to reduce unexpected cardiac arrest.

Improving the Efficiency of an Emergency Department Based on Activity-Relationship Diagram and Radio Frequency Identification Technology

Emergency department crowding has been one of the main issues in the health system in Taiwan. Previous studies have usually targeted the process improvement of patient treatment flow due to the difficulty of collecting Emergency Department (ED) staff data. In this study, we have proposed a hybrid model with Discrete Event Simulation, radio frequency identification applications, and activity-relationship diagrams to simulate the nurse movement flows and identify the relationship between different treatment sections. We used the results to formulate four facility layouts. Through comparing four scenarios, the simulation results indicated that 2.2 km of traveling distance or 140 min of traveling time reduction per nurse could be achieved from the best scenario.

An innovative medical consultation model in mainland China

PURPOSE

The purposes of this paper are two-fold: first, to introduce a new concept of primary care consultation system at a mainland Chinese hospital in response to healthcare reform; and second, to explore the factors associated with change resistance and acceptance from both patients' and medical staff's perspectives.

DESIGN/METHODOLOGY/APPROACH

A survey design study, with two questionnaires developed and distributed to patients and medical staff. Convenience and stratified random sampling methods were applied to patient and medical staff samples.

FINDINGS

A 5-dimension, 21-item patient questionnaire and a 4-dimension, 16-item staff questionnaire were identified and confirmed, with 1020 patients (91.07 percent) and 202 staff (90.18 percent) as effective survey participants. The results revealed that patient resistance mainly stems from a lack of personal experiences with visiting general practice (GP) and being educated or having lived overseas; while staff resistance came from occupation, education, GP training certificate, and knowledge and experience with specialists. Living in overseas and knowledge of GP concepts, gender and education are associated with resistance of accepting the new practice model for both patients and staff.

ORIGINALITY/VALUE

There are few Chinese studies on process reengineering in the medical sector; this is the first study to adopt this medical consultation model and change in patients' consultation culture in Mainland China. Applying organizational change and process reengineering theories to medical and healthcare services not only extends and expands hospital management theory but also allows investigation of modern hospital management practice. The experience from this study can serve as a reference to promote this new consultation model in Chinese healthcare reform.

Patients' time perception in the waiting room of an ambulatory emergency unit: a cross-sectional study

Background

Patient satisfaction has become an increasingly important element in a service-oriented healthcare market. Although satisfaction is influenced by many factors, the waiting time to be seen by medical staff has been shown to be one of the key criteria. However, waiting is not an objective experience and several factors can influence its perception.

Methods

We conducted a questionnaire-based, cross-sectional study among patients attending the emergency unit of a Swiss university hospital in order to explore the key factors influencing wait perception.

Results

A total of 509 patients participated in the study. Appropriate assessment of emergency level by caregivers, the feeling of being forgotten, respect of privacy, and lack of information on the exact waiting time were identified as significant variables for wait perception.

Conclusions

Our study confirmed the existence of a ‘golden hour’ when the patient is willing to wait until the medical encounter. In case the wait cannot be limited, an appropriate assessment of the emergency level by caregivers and avoiding the patients of feeling being forgotten are very important factors to avoid a negative perception of the waiting time before seeing a doctor.

Trial registration

(ID REQ-2016-00555).

A Mobile-Based Patient-Centric Passive System for Guiding Patients Through the Hospital Workflow: Design and Development

Background

A hospital is an unfamiliar place to patients because of its style, atmosphere, and procedures. These hospital characteristics cause patients to become confused about responding to protocols, which slows down the procedural flows. Some additional information technology infrastructure facilities and human resources may be needed to solve these problems. However, this solution needs high investment and cannot guarantee an accuracy of information sent to patients. To handle this limitation, EasyHos has been developed to help patients recognize their status (for example, “waiting for an appointment at 11am“) during their stay in a hospital using all existing infrastructure and hospital data and without changing existing hospital's process.

Objective

The objective of this study was to provide a design of the EasyHos system and the case study in hospitals in Thailand. The design is usable and repeatable for small- and medium-sized hospitals where internet infrastructure is in place.

Methods

The EasyHos system has been designed based on existing infrastructure, hospital data and hospital processes. The main components include mobile devices, existing hospital data, wireless communication network. The EasyHos was deployed at 2 hospitals in Thailand, one small and the other with a medium size. The experimental process was focused on solving the problem of unfamiliarity in the hospital. The criteria and pretest conditions regarding the unexpected problem have been defined before the experiment.

Results

The results are presented in terms of criteria, pretest conditions, posttest conditions in the hospitals. The posttest conditions show the experimental results and impact of the system on users such as hospital nurses/staff and patients. For example, the questions from patients were reduced by 83.3% after using EasyHos system while nurses/hospital staff had 5 min more to do their routine work each day. In addition, another impact is that hospitals can create new information values from existing data, which now can be visible and valuable to patients.

Conclusions

Hospitals' unexpected problems have been reduced by the EasyHos system. The EasyHos system has been developed with self-service and patient-centered concepts to assist patients with necessary information. The system makes interaction easier for nurses/hospital staff members and patients working or waiting in the hospital. The nurses/hospital staff members would have more time to do their routine works. Hospitals can easily set up the EasyHos system, which will have a low or nearly zero implementation cost.

Using Lean Six Sigma to Improve Delayed Intracranial Hemorrhage Screening in a Geriatric Trauma Population

PURPOSE

Geriatric trauma patients taking preinjury anticoagulant or antiplatelet (ACAP) medications are at greater risk for delayed intracranial hemorrhage (DICH), a rare but potentially life-threatening condition. Routine repeat head computed tomography (RRHCT) scans can identify DICH. Our objective was to decrease the rate of missed RRHCT in a level 1 Midwest trauma center geriatric minor trauma population on preinjury ACAP medications.

OBJECTIVE

The objective of the quality improvement project was to identify the root cause of the missed RRHCTs and to implement a comprehensive solution to reduce rates of missed RRHCTs.

METHODS

Medical records from before and after the intervention were evaluated. Frequencies and percentages were calculated. In addition, χ and logistic regression were utilized. The Lean Six Sigma (LSS) DMAIC (Define, Measure, Analyze, Improve, and Control) process was used to drive process improvement.

RESULTS

At baseline, 15% (41 of 267) of RRHCTs were missed. After solution implementation, missed RRHCTs dropped to 4% (2 of 50). Of the 2 that were missed, zero were clinically inappropriate misses, making the postimplementation rate effectively 0%.

CONCLUSION

The LSS DMAIC process helped health care professional to facilitate improved adherence to the department's practice guideline with respect to RRHCT. Adherence with this guideline can help providers identify patients with DICH, a potentially life-threatening condition.

SurgeCon: Priming a Community Emergency Department for Patient Flow Management

Introduction

Canadian emergency departments (ED) are struggling to provide timely emergency care. Very few studies have assessed attempts to improve ED patient flow in the rural context. We assessed the impact of SurgeCon, an ED patient-management protocol, on total patient visits, patients who left without being seen (LWBS), length of stay for departed patients (LOSDep), and physician initial assessment time (PIA) in a rural community hospital ED.

Methods

We implemented a set of commonly used methods for increasing ED efficiency with an innovative approach over 45 months. Our intervention involved seven parts comprised of an external review, Lean training, fast track implementation, patient-centeredness approach, door-to-doctor approach, performance reporting, and an action-based surge capacity protocol. We measured key performance indicators including total patient visits (count), PIA (minutes), LWBS (percentage), and LOSDep (minutes) before and after the SurgeCon intervention. We also performed an interrupted time series (ITS) analysis.

Results

During the study period, 80,709 people visited the ED. PIA decreased from 104.3 (±9.9) minutes to 42.2 (±8.1) minutes, LOSDep decreased from 199.4 (±16.8) minutes to 134.4(±14.5) minutes, and LWBS decreased from 12.1% (±2.2) to 4.6% (±1.7) despite a 25.7% increase in patient volume between pre-intervention and post-intervention stages. The ITS analysis revealed a significant level change in PIA - 19.8 minutes (p<0.01), and LWBS - 3.8% (0.02), respectively. The change over time decreased by 2.7 minutes/month (p< 0.001), 3.0 minutes/month (p<0.001) and 0.4%/month (p<0.001) for PIA, LOSDep, and LWBS, after the intervention.

Conclusion

SurgeCon improved the key wait-time metrics in a rural ED in a country where average wait times continue to rise. The SurgeCon platform has the potential to improve ED efficiency in community hospitals with limited resources.

An Edge Computing Based Smart Healthcare Framework for Resource Management

The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time.

An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments

Emergency departments (EDs) provide medical treatment for a broad spectrum of illnesses and injuries to patients who arrive at all hours of the day. The quality and efficient delivery of health care in EDs are associated with a number of factors, such as patient overall length of stay (LOS) and admission, prompt ambulance diversion, quick and accurate triage, nurse and physician assessment, diagnostic and laboratory services, consultations and treatment. One of the most important ways to plan the healthcare delivery efficiently is to make forecasts of ED processes. The aim this study is thus to provide an exhaustive review for ED stakeholders interested in applying forecasting methods to their ED processes. A categorisation, analysis and interpretation of 102 papers is performed for review. This exhaustive review provides an insight for researchers and practitioners about forecasting in EDs in terms of showing current state and potential areas for future attempts.

Complex Febrile Seizures, Lumbar Puncture, and Central Nervous System Infections: A National Perspective

OBJECTIVES

The objective was to determine the national lumbar puncture (LP) practice patterns relative to the incidence of central nervous system (CNS) infections among children presenting to the emergency department (ED) with complex febrile seizures (CFS).

METHODS

This was a retrospective study of ED visits for CFS from 2007 to 2014 in patients aged 0 to 5 years using a national sample. Primary outcomes include the frequency of LP, incidence of CNS infections, and ED disposition.

RESULTS

Of 28,810 ED visits for CFS (44.4% female; mean age = 1.39 years), LP was performed in 7,445 (25.8%, 95% confidence interval [CI] 23.5%-28.2%). There was no significant difference in the proportion due to hospital teaching status or geographical region. The proportion decreased from 31.4% to 17.8% over the study period (Rao-Scott statistic = 5.85, p < 0.001). CNS infection was diagnosed in 80 (0.3%) encounters (95% CI = 41-112). The most commonly associated infections were otitis media (16.8%), upper respiratory infections (15.8%), and other viral infections (14.6%). A total of 14,696 encounters (51.0%, 95% CI = 47.9%-54.1%) resulted in a hospital admission.

CONCLUSIONS

Although rates have been declining, LP was performed in one-fourth of ED encounters for CFS over the 8-year study period. The incidence of CNS infections was very low, however, suggesting that this procedure could be avoided in many patients.

Predictive performance of the SOFA and mSOFA scoring systems for predicting in-hospital mortality in the emergency department

BACKGROUND

The Sequential Organ Failure Assessment (SOFA) and modified SOFA (mSOFA) are risk stratification systems which incorporate respiratory, coagulatory, liver, cardiovascular, renal, and neurologic systems to quantify the overall severity of acute disorder in the intensive care unit.

OBJECTIVE

To evaluate the prognostic performance of the SOFA and mSOFA scores at arrival for predicting in-hospital mortality in the emergency department (ED).

METHODS

All adult patients with an Emergency Severity Index (ESI) of 1-3 in the ED of Imam Reza Hospital, northeast of Iran were included from March 2016 to March 2017. The predictive performance of the SOFA or mSOFA scores were expressed in terms of accuracy (Brier Score, BS and Brier Skill Score, BSS), discrimination (Area Under the Receiver Operating Characteristic Curve, AUC), and calibration.

RESULTS

A total of 2205 patients (mean age 61.8 ± 18.5 years, 53% male) were included. The overall in-hospital mortality was 19%. For SOFA and mSOFA the BS was 0.209 and 0.192 and the BSS was 0.11 and 0.09, respectively. The estimated AUCs of SOFA and mSOFA models were 0.751 and 0.739, respectively. No significant difference was observed between the AUCs (P = 0.186). The Hosmer-Lemeshow test did not show that the predictions deviated from the true probabilities. Also, the calibration plots revealed good agreement between the actual and predicted probabilities.

CONCLUSION

The SOFA and mSOFA scores demonstrated fair discrimination and good calibration in predicting in-hospital mortality when applied to ED. However, further external validation studies are needed before their use in routine clinical care.

Evidence that patient-centered medical homes are effective in reducing emergency department admissions for patients with depression

The patient-centered medical home (PCMH) has increasingly been touted as one means of integrating behavioral health and primary care and more holistically caring for patients with chronic disease. With its whole person orientation, the PCMH presents an opportunity to reduce emergency department visits for patients with depression by focusing on the patient and his/her health care needs, facilitating communication among providers and patients, and improving patients' access to care providers across settings. This study examines the relationship between PCMH capacity - defined as the ability to offer a service identified as a component part of the PCMH - and the number of emergency department visits for patients with depression. Health plan claims data, self-report data from physician practices on their PCMH characteristics, and the Area Resource File were analyzed. Results show that overall PCMH capacity is associated with fewer emergency department visits for patients with depression, and interpersonal aspects of the PCMH in particular, were associated with fewer emergency department visits while technical capabilities were not. Interpersonal activities that facilitate care coordination, patient engagement, and connect patients with community resources might be more effective in keeping patients out of the emergency department for unnecessary reasons as compared to technical activities focused on reporting and information management.

Inpatient flow management: a systematic review

Purpose

In hospitals, several patient flows compete for access to shared resources. Failure to manage these flows result in one or more disruptions within a hospital system. To ensure continuous care delivery, solving flow problems must not be limited to one unit, but should be extended to other departments – a prerequisite for solving flow problems in the entire hospital. Since most current studies focus solely on overcrowding in emergency units, additional insights are needed on system-wide patient flow management. The purpose of this paper is to look at the information available in system-wide patient flow management studies, which were also systematically evaluated to demonstrate which interventions improve inpatient flow.

Design/methodology/approach

The authors searched PubMed and Web of Science (Core Collection) literature databases and collected full-text articles using two selection and classification stages. Stage 1 was used to screen articles relating to patient flow management for inpatient settings with typical characteristics. Stage 2 was used to classify the articles selected in Stage 1 according to the interventions and their impact on patient flow within a hospital system.

Findings

In Stage 1, 107 studies were selected. Although a growing trend was observed, there were fewer studies on patient flow management in inpatient than studies in emergency settings. In Stage 2, 61 intervention studies were classified. The authors found that most interventions were about creating and adding supply resources. Since many hospital managers these days cannot easily add capacity owing to cost and resource constraints, using existing capacity efficiently is important – unfortunately not addressed in many studies. Furthermore, arrival variability was the factor most frequently mentioned as affecting flow. Of all interventions addressed in this review, the most prominent for advancing patient access to inpatient units was employing a specialized individual or team to maintain patient flow and bed placement across hospital units.

Originality/value

This study provides the first patient flow management systematic overview within an inpatient setting context.

Key High-efficiency Practices of Emergency Department Providers: A Mixed-methods Study

OBJECTIVE

The objective of this study was to determine specific provider practices associated with high provider efficiency in community emergency departments (EDs).

METHODS

A mixed-methods study design was utilized to identify key behaviors associated with efficiency. Stage 1 was a convenience sample of 16 participants (ED medical directors, nurses, advanced practice providers, and physicians) identified provider efficiency behaviors during semistructured interviews. Ninety-nine behaviors were identified and distilled by a group of three ED clinicians into 18 themes. Stage 2 was an observational study of 35 providers was performed in four (30,000- to 55,000-visit) community EDs during two 4-hour periods and recorded in minute-by-minute observation logs. In Stage 3, each behavior or practice from Stage 1 was assigned a score within each observation period. Behaviors were tested for association with provider efficiency (relative value units/hour) using linear univariate generalized estimating equations with an identity link, clustered on ED site.

RESULTS

Five ED provider practices were found to be positively associated with efficiency: average patient load, using name of team member, conversations with health care team, visits to patient rooms, and running the board. Two behaviors, "inefficiency practices," demonstrated significant negative correlations: non-work-related tasks and documentation on patients no longer in the ED.

CONCLUSIONS

Average patient load, running the board, conversations with team member, and using names of team members are associated with enhanced provider productivity. Identification of behaviors associated with efficiency can be utilized by medical directors, clinicians, and trainees to improve personal efficiency or counsel team members.

Grow the Pie: Interdepartmental Cooperation as a Method for Achieving Operational Efficiency in an Emergency Department

BACKGROUND

Despite sufficient literature analyzing macroscopic and microscopic methods of addressing emergency department (ED) operations, there is a paucity of studies that analyze methods between these extremes.

OBJECTIVE

We conducted a quasi-experimental study incorporating a pre/post-intervention comparison to determine whether interdepartmental cooperation is effective at improving ED operations by combining microscopic and macroscopic concepts.

METHODS

We performed an analysis of operational and financial data from a cooperative investment in imaging transport personnel between the emergency and radiology departments. Our primary outcome, order to table time (OTT), measured imaging times by modality (computed tomography [CT], ultrasound [US], magnetic resonance imaging [MRI]). These were compared for statistically significant change before and after the intervention. Our secondary outcome, gross profit, was calculated using the revenue generated from gained outpatient studies minus the associated direct personnel costs.

RESULTS

Transporters improved OTTs by decreasing median imaging times from 132 min to 116 min (p < 0.0005). Efficiency improved for CT scans with median time decreasing from 142 min to 114 min (p < 0.0005). Transport hires had adverse effects on US, with an increase in median OTT from 91 min to 99 min (p < 0.018). MRI experienced a similar trend in OTT, as median times worsened from 215 min to 235 min (p < 0.225). The investment in transporters generated a gross profit of $1.03 million for the radiology department over 9 months.

CONCLUSIONS

Interdepartmental cooperation is a broadly applicable macroscopic method that is effective at achieving microscopic, site-specific gains in ED efficiency. Transporters provided operational gains for the ED and financial gains for the radiology department.

Improving patient flow through applying lean concepts to emergency department

Purpose This paper aims to propose lean-based interventions that address the main causes of emergency department overcrowding. Emergency department overcrowding (EDOC) and increased length of stay (LOS) have been key global issues for more than 20 years, as they have serious repercussions. No measurements have been done to assess the situation nationally. Expanding emergency departments (EDs) and adding more beds have never succeeded in eliminating wastes and targeting the root causes of the problem. Design/methodology/approach This paper is a quantitative analytical applied research. The paper used direct observation for seven days to collect patient flow data on ED patients at a secondary care hospital in Kuwait. It calculated wait times and services to identify the major causes of EDOC and increased LOS. Findings Around one-third of the ED design capacity was used by 12 per cent of the patients who stayed >6 h each. The wasted waiting time represents 56.2 per cent of the aggregated LOS, which puts lean management (LM) on the top of the process reengineering approaches suitable for improving overcrowding by reducing waste. Guided by the LM concepts, the paper proposes solutions that fall into three themes. The selected solutions address the vital few causes of the EDOC and prolonged EDLOS. Originality/value This paper is the first study of its kind in Kuwait, and one of the most outstanding studies in the Gulf region, in terms of the number of the daily ED visits and the comprehensive multi-level proposed interventions.

Standardized Reporting System Use During Handoffs Reduces Patient Length of Stay in the Emergency Department

Background

Emergency department (ED) shift handoffs are potential sources of delay in care. We aimed to determine the impact that using standardized reporting tool and process may have on throughput metrics for patients undergoing a transition of care at shift change.

Methods

We performed a prospective, pre- and post-intervention quality improvement study from September 1 to November 30, 2015. A handoff procedure intervention, including a mandatory workshop and personnel training on a standard reporting system template, was implemented. The primary endpoint was patient length of stay (LOS). A comparative analysis of differences between patient LOS and various handoff communication methods were assessed pre- and post-intervention. Communication methods were entered a multivariable logistic regression model independently as risk factors for patient LOS.

Results

The final analysis included 1,006 patients, with 327 comprising the pre-intervention and 679 comprising the post-intervention populations. Bedside rounding occurred 45% of the time without a standard reporting during pre-intervention and increased to 85% of the time with the use of a standard reporting system in the post-intervention period (P < 0.001). Provider time (provider-initiated care to patient care completed) in the pre-intervention period averaged 297 min, but decreased to 265 min in the post-intervention period (P < 0.001). After adjusting for other communication methods, the use of a standard reporting system during handoff was associated with shortened ED LOS (OR = 0.60, 95% CI 0.40 - 0.90, P < 0.05).

Conclusions

Standard reporting system use during emergency physician handoffs at shift change improves ED throughput efficiency and is associated with shorter ED LOS.

Prudent healthcare in emergency departments: a case study in Wales

To deliver a patient-centred service, emergency departments (EDs) must be efficient, effective and meet the needs of the local population. This article describes a service redesign of unscheduled care in a hospital in Wales, which followed the principles of prudent healthcare to improve patient experiences. Extending the roles of nurse specialist practitioners was a major component of the redesign. Six working groups were established to guide the process, one of which was responsible for working cooperatively with the local community, which was concerned about perceived 'downgrading' of the ED. The service redesign was completed in 2016 and evaluation shows the target for patients being seen in under four hours improved from 88% to 96%, significantly more acute medical admission patients were discharged in less than 24 hours, and patient satisfaction increased overall.

Lessons Learned From the Development and Parameterization of a Computer Simulation Model to Evaluate Task Modification for Health Care Providers

Computer simulation is a highly advantageous method for understanding and improving health care operations with a wide variety of possible applications. Most computer simulation studies in emergency medicine have sought to improve allocation of resources to meet demand or to assess the impact of hospital and other system policies on emergency department (ED) throughput. These models have enabled essential discoveries that can be used to improve the general structure and functioning of EDs. Theoretically, computer simulation could also be used to examine the impact of adding or modifying specific provider tasks. Doing so involves a number of unique considerations, particularly in the complex environment of acute care settings. In this paper, we describe conceptual advances and lessons learned during the design, parameterization, and validation of a computer simulation model constructed to evaluate changes in ED provider activity. We illustrate these concepts using examples from a study focused on the operational effects of HIV screening implementation in the ED. Presentation of our experience should emphasize the potential for application of computer simulation to study changes in health care provider activity and facilitate the progress of future investigators in this field.

Understanding Emergency Care Delivery Through Computer Simulation Modeling

In 2017, Academic Emergency Medicine convened a consensus conference entitled, "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes." This article, a product of the breakout session on "understanding complex interactions through systems modeling," explores the role that computer simulation modeling can and should play in research and development of emergency care delivery systems. This article discusses areas central to the use of computer simulation modeling in emergency care research. The four central approaches to computer simulation modeling are described (Monte Carlo simulation, system dynamics modeling, discrete-event simulation, and agent-based simulation), along with problems amenable to their use and relevant examples to emergency care. Also discussed is an introduction to available software modeling platforms and how to explore their use for research, along with a research agenda for computer simulation modeling. Through this article, our goal is to enhance adoption of computer simulation, a set of methods that hold great promise in addressing emergency care organization and design challenges.

The Effect of Implementation of the Standard Clinical Practice Guideline (CPG) for Management of Multiple Trauma Patients Admitted to an Emergency Department

INTRODUCTION

The purpose of triage in the standard Clinical Practice Guide (CPG) for multiple trauma patients is to perform the primary and secondary evaluations in the quickest and shortest possible time with minimal errors and the best quality in the emergency department (ED).

OBJECTIVE

In this study, a practical program for a coordinated management of multiple trauma patients in the ED has been provided by using the CPG guide. The impact of its implementation on the multiple trauma patients' management was evaluated.

METHODS

This is a cross-sectional study conducted in 2014 and 2015 in Isfahan's Al-Zahra hospital ED. Administration and management of multiple trauma patients had been prepared before the implementation of the plan based on standard clinical methods of implementation in a way that used a 12-step protocol for the practical guide. This protocol was designed as a flowchart and the results before and after its implementation were evaluated.

RESULTS

In this study, 100 multiple trauma patients before and after the implementation of the protocol were studied. The mean age of the patients and other baseline characteristics of studied patients in the two periods before and after implantation of the CPG were not significantly different (p > 0.05). The frequency of intubation (p = 0.016) and sent to the operating room (p < 0.001) were different in the two study periods. However, hospitalization in the ICU (p = 0.35) and death (p = 0.73) before and after implementation of the protocol were not statistically different. The time before examination by the EM physicians was significantly lower in all triage levels after CPG implementation. Meanwhile, no change in time elapsed occurred for the surgeons except for the patients in level 2 of triage.

CONCLUSION

Implementation of the strategic plan of CPG lead to a significant reduction in waiting time for visits by emergency medicine services and other specialized services, increased the deployment of patients needing surgery, and reducing the time spent in the ED.