Models for improving patient throughput and waiting at hospital emergency departments

Prolonged length of stay and associated factors among emergency department patients in Ethiopia: systematic review and meta-analysis

BACKGROUND

The duration between a patient's arrival at the Emergency Department (ED) and their actual departure, known as the Emergency Department Length of Stay (EDLOS), can have significant implications for a patient's health. In Ethiopia, various studies have investigated EDLOS, but a comprehensive nationwide pooled prevalence of prolonged EDLOS, which varies across different locations, is currently lacking. Therefore, the objective of this systematic review and meta-analysis is to provide nationally representative pooled prevalence of prolonged EDLOS and identify associated factors.

METHODS

In this study, we conducted a comprehensive systematic review and meta-analysis using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist. We conducted a thorough search of numerous international databases, including PubMed/Medline, SCOPUS, Web of Science, and Google Scholar. The primary outcome was the prevalence of prolonged EDLOS. The secondary outcome was factors affecting the EDLOS. Random-effects model was used to since there was high heterogeneity. We also conducted subgroup analysis and meta-regression to investigate heterogeneity within the included studies. To assess publication bias, we used Egger's regression test and funnel plots. All statistical analyses were performed using STATA version 17.0 software to ensure accurate and reliable findings.

RESULT

We have identified eight articles that met our inclusion criteria with a total sample size of 8,612 participants. The findings of this systematic review and meta-analysis indicate that the pooled estimate for the prevalence of prolonged EDLOS is 63.67% (95% CI = 45.18, 82.16, I2 = 99.56%, P = 0.0001). The study identified several significant factors associated with prolonged EDLOS, including patients admitted to overcrowded emergency departments (OR = 5.25, 95% CI = 1.77, 15.58), delays in receiving laboratory findings (OR = 3.12, 95% CI = 2.16, 4.49), and delays in receiving radiological results (OR = 3.00, 95% CI = 2.16, 4.16).

CONCLUSION

In this review, the EDLOS was found to be very high. Overcrowding, delays in laboratory test findings, and delays in radiology test results make up the factors that have a statistically significant association with prolonged EDLOS. Given the high prevalence of prolonged EDLOS in this review, stakeholders should work to increase the timeliness of ED services in Ethiopia by proper disposition of non-emergency palliative patients to the appropriate destination, and implementing point-of-care testing and imaging.

What Is It That You Want Me To Do? Guidance for Ethics Consultants in Complex Discharge Cases

Some of the most difficult consultations for an ethics consultant to resolve are those in which the patient is ready to leave the acute-care setting, but the patient or family refuses the plan, or the plan is impeded by deficiencies in the healthcare system. Either way, the patient is "stuck" in the hospital and the ethics consultant is called to help get the patient "unstuck." These encounters, which we call "complex discharges," are beset with tensions between the interests of the institution and the interests of the patient as well as tensions within the ethics consultant whose commitments are shaped both by the values of the organization and the values of their own profession. The clinical ethics literature on this topic is limited and provides little guidance. What is needed is guidance for consultants operating at the bedside and for those participating at a higher organizational level. To fill this gap, we offer guidance for facilitating a fair process designed to resolve the conflict without resorting to coercive legal measures. We reflect on three cases to argue that the approach of the consultant is generally one of mediation in these types of disputes. For patients who lack decision making capacity and lack a surrogate decision maker, we recommend the creation of a complex discharge committee within the organization so that ethics consultants can properly discharge their duties to assist patients who are unable to advocate for themselves through a fair and transparent process.

A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak

The use of emergency departments (EDs) has increased during the COVID-19 outbreak, thereby evidencing the key role of these units in the overall response of healthcare systems to the current pandemic scenario. Nevertheless, several disruptions have emerged in the practical scenario including low throughput, overcrowding, and extended waiting times. Therefore, there is a need to develop strategies for upgrading the response of these units against the current pandemic. Given the above, this paper presents a hybrid fuzzy multicriteria decision-making model (MCDM) to evaluate the performance of EDs and create focused improvement interventions. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique is used to estimate the relative priorities of criteria and sub-criteria considering uncertainty. Then, the intuitionistic fuzzy decision making trial and evaluation laboratory (IF-DEMATEL) is employed to calculate the interdependence and feedback between criteria and sub-criteria under uncertainty, Finally, the combined compromise solution (CoCoSo) is implemented to rank the EDs and detect their weaknesses to device suitable improvement plans. The aforementioned methodology was validated in three emergency centers in Turkey. The results revealed that the most important criterion in ED performance was ER facilities (14.4%), while Procedures and protocols evidenced the highest positive D + R value (18.239) among the dispatchers and is therefore deemed as the main generator within the performance network.

Effective Response to Hospital Congestion Scenarios: Simulation-Based Evaluation of Decongestion Interventions

Hospital overcrowding is becoming a major concern in the modern era due to the increasing demand for hospital services. This study seeks to identify effective and efficient ways to resolve the serious problem of congestion in hospitals by testing a range of decongestion strategies with simulated scenarios. In order to determine more efficient solutions, interventions with smaller changes were consistently tested at the beginning through a simulation platform. In addition, the implementation patterns were investigated, which are important to hospital managers with respect to the decisions made to control hospital congestion. The results indicated that diverting a small number of ambulances seems to be more effective and efficient in congestion reduction compared to other approaches. Furthermore, instead of implementing an isolated approach continuously, combining one approach with other strategies is recommended as a method for dealing with hospital overcrowding.

A virtual evaluation of options for managing risk of hospital congestion with minimum intervention

Hospital congestion is a common problem for the healthcare sector. However, existing approaches including hospital resource optimization and process improvement might lead to huge cost of human and physical structure changes. This study evaluated less disruptive interventions based on a hospital simulation model and offer objective reasoning to support hospital management decisions. This study tested a congestion prevention method that estimates hospital congestion risk level (R), and activates minimum intervention when R is above certain threshold, using a virtual hospital created by simulation modelling. The results indicated that applying a less disruptive intervention is often enough, and more cost effective, to reduce the risk level of hospital congestion. Moreover, the virtual implementation approach enabled testing of the method at a more detailed level, thereby revealed interesting findings difficult to achieve theoretically, such as discharging extra two medical inpatients, rather than surgical inpatients, a day earlier on days when R is above the threshold, would bring more benefits in terms of congestion reduction for the hospital.

Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department

Increasing demand and changing case-mix have resulted in bottlenecks and longer waiting times in emergency departments (ED). However, many process improvement efforts addressing the bottlenecks have limitations, as they lack accurate models of the real system as input accounting for operational complexities. To understand the limitation, this research modelled granular procedural information, to analyse processes in a Level-1 ED of a 1200-bed teaching hospital in the UK. Semi-structured interviews with 21 clinicians and direct observations provided the necessary information. Results identified Majors as the most crowded area, hence, a systems modelling technique, role activity diagram, was used to derive highly granular process maps illustrating care in Majors which were further validated by 6 additional clinicians. Bottlenecks observed in Majors included awaiting specialist input, tests outside the ED, awaiting transportation, bed search, and inpatient handover. Process mapping revealed opportunities for using precedence information to reduce repeat tests; informed alerting; and provisioning for operational complexity into ED processes as steps to potentially alleviate bottlenecks. Another result is that this is the first study to map care processes in Majors, the area within the ED that treats complex patients whose care journeys are susceptible to variations. Findings have implications on the development of improvement approaches for managing bottlenecks.

Exploration of clinicians’ decision-making regarding transfer of patient care from the emergency department to a medical assessment unit: A qualitative study

Background

Hospitals face immense pressures in balancing patient throughput. Medical assessment units have emerged as a commonplace response to improve the flow of medical patients presenting to the emergency department requiring hospital admission and to ease overcrowding in the emergency department. The aim of this study was to understand factors influencing the decision-making behaviour of key stakeholders involved in the transfer of care of medical patients from one service to the other in a large, tertiary teaching hospital in Queensland, Australia.

Methods

We used a qualitative approach drawing on data from focus groups with key informant health and professional staff involved in the transfer of care. A theoretically-informed, semi-structured focus group guide was used to facilitate discussion and explore factors impacting on decisions made to transfer care of patients from the emergency department to the medical assessment unit. Thematic analysis was undertaken to look for patterns in the data.

Results

Two focus groups were conducted with a total of 15 participants. Four main themes were identified: (1) we have a process—we just don’t use it; (2) I can do it, but can they; (3) if only we could skype them; and (4) why can’t they just go up. Patient flow relies on efficiency in two processes—the transfer of care and the physical re-location of the patient from one service to the other. The findings suggest that factors other than clinical reasoning are at play in influencing decision-making behaviour.

Conclusions

Acknowledgement of the interaction within and between professional and health staff (human factors) with the organisational imperatives, policies, and process (system factors) may be critical to improve efficiencies in the service and minimise the introduction of workarounds that might compromise patient safety.

When patients get stuck: A systematic literature review on throughput barriers in hospital-wide patient processes

Hospital productivity is of great importance to policymakers, and previous research demonstrates that improved hospital productivity can be achieved by directing more focus towards patient throughput at healthcare organizations. There is also a growing body of literature on patient throughput barriers hampering the flow of patients. These projects rarely, however, encompass complete hospitals. Therefore, this paper provides a systematic literature review on hospital-wide patient process throughput barriers by consolidating the substantial body of studies from single settings into a hospital-wide perspective. Our review yielded a total of 2207 articles, of which 92 were finally selected for analysis. The results reveal long lead times, inefficient capacity coordination and inefficient patient process transfer as the main barriers at hospitals. These are caused by inadequate staffing, lack of standards and routines, insufficient operational planning and a lack in IT functions. As such, this review provides new perspectives on whether the root causes of inefficient hospital patient throughput are related to resource insufficiency or inefficient work methods. Finally, this study develops a new hospital-wide framework to be used by policymakers and healthcare managers when deciding what improvement strategies to follow to increase patient throughput at hospitals.

Process improvement approaches in emergency departments: a review of the current knowledge

Purpose

The healthcare system has been under pressure to provide timely and quality healthcare. The influx of patients in the emergency departments (EDs) is testing the capacity of the system to its limit. In order to increase EDs' capacity and performance, healthcare managers and practitioners are adopting process improvement (PI) approaches in their operations. Thus, this study aims to identify the main PI approaches implemented in EDs, as well as the benefits and barriers to implement these approaches.

Design/methodology/approach

The study is based on a rigorous systematic literature review of 115 papers. Furthermore, under the lens of thematic analysis, the authors present the descriptive and prescriptive findings.

Findings

The descriptive analysis found copious information related to PI approaches implemented in EDs, such as main PIs used in EDs, type of methodological procedures applied, as well as a set of barriers and benefits. Aiming to provide an in-depth analysis and prescriptive results, the authors carried out a thematic analysis that found underlying barriers (e.g. organisational, technical and behavioural) and benefits (e.g. for patients, the organisation and processes) of PI implementation in EDs.

Originality/value

The authors contribute to knowledge by providing a comprehensive review of the main PI methodologies applied in EDs, underscoring the most prominent ones. This study goes beyond descriptive studies that identify lists of barriers and benefits, and instead the authors categorize prescriptive elements that influence these barriers and benefits. Finally, this study raises discussions about the behavioural influence of patients and medical staff on the implementation of PI approaches.

Patient Experiences With Transfer for Community Hospital Inpatient Admission From an Academic Emergency Department

Emergency department (ED) crowding continues to be a major challenge and has important ramifications for patient care quality. One strategy to decrease ED crowding has been to implement alternative pathways to traditional hospital admission. Through a survey-based retrospective cohort study, we aimed to assess the patient experience for those who agreed to transfer and admission to an affiliated community hospital from a large, academic center’s ED. In all, 85% of participants rated their overall experience as either great or good, 92% did not find it hard to make the decision to be transferred, and 95% found the transfer process itself to be easy.

The prevalence and management of deteriorating patients in an Australian emergency department

BACKGROUND

Complex human and system factors impact the effectiveness of Rapid Response Systems (RRS). Emergency Department (ED) specific RRS are relatively new and the factors associated with their effectiveness are largely unknown. This study describes the period prevalence of deterioration and characteristics of care for deteriorating patients in an Australia ED and examine relationships between system factors and escalation of care.

METHODS

A retrospective medical record audit of all patients presenting to an Australian ED in two weeks.

RESULTS

Period prevalence of deterioration was 10.08% (n=269). Failure to escalate care occurred in nearly half (n=52, 47.3%) of the patients requiring a response (n=110). Appropriate escalation practices were associated with where the patient was being cared for (p=0.01), and the competence level of the person documenting deterioration (p=0.005). Intermediate competence level nurses were nine times more likely to escalate care than novices and experts (p=0.005). While there was variance in escalation practice related to system factors, these associations were not statistically significant.

CONCLUSION

The safety of deteriorating ED patients may be improved by informing care based on the escalation practices of staff with intermediate ED experience and competence levels.

Queuing Theory and Modeling Emergency Department Resource Utilization

Queueing theory is a discipline of applied mathematics that studies the behavior of lines. Queueing theory has successfully modeled throughput in a variety of industries, including within the emergency department (ED). Queueing equations model the demand for different processes within the ED, and help to factor in effects of variability on delays and service times. Utilization is a measure of the throughput of a process relative to demand, and provides a quick means of comparing the demand for certain resources. Although there have been some significant successes in applying queueing theory to EDs, the field remains underused within ED operations.

Distributed situation awareness: a health-system approach to assessing and designing patient flow management

Patient flow management is a system-wide process but many healthcare providers do not integrate multiple departments into the process to minimise the time between treatments or medical services for maximum patient throughput. This paper presents a case study of applying Distributed Situation Awareness (DSA) to characterise system-wide patient flow management and identify opportunities for improvements in a healthcare system. This case study employed a three-part method of data elicitation, extraction, and representation to investigate DSA. Social, task, and knowledge networks were developed and then combined to characterise patient flow management and identify deficiencies of the command and control centre of a healthcare facility. Social network analysis provided centrality metrics to further characterise patient flow management. The DSA model helped identify design principles and deficiencies in managing patient flow. These findings indicate that DSA is promising for analysing patient flow management from a system-wide perspective. Practitioner summary: This article examines Distribution Situation Awareness (DSA) as an analysis framework to study system-wide patient flow management. The DSA yields social, task, and knowledge networks that can be combined to characterise patient flow and identify deficiencies in the system. DSA appears promising for analysing communication and coordination of complex systems. Abbreviations: CDM: critical decision method; CTaC: carilion transfer and communications center; EAST: event analysis systematic teamwork; ED: emergency department; DES: discrete event simulation; DSA: distributed situation awareness; SA: situation awareness; SNA: social network analysis.

Liu S, A. Camargo C, Aburawi E, Moeckel M, Slagman A, Christ M, Singer A, Tazarourte K, Rathlev NK, A. Grossman S, Bellou A. Association between boarding in the emergency department and in-hospital mortality: A systematic review

IMPORTANCE

Boarding in the emergency department (ED) is a critical indicator of quality of care for hospitals. It is defined as the time between the admission decision and departure from the ED. As a result of boarding, patients stay in the ED until inpatient beds are available; moreover, boarding is associated with various adverse events.

STUDY OBJECTIVE

The objective of our systematic review was to determine whether ED boarding (EDB) time is associated with in-hospital mortality (IHM).

METHODS

A systematic search was conducted in academic databases to identify relevant studies. Medline, PubMed, Scopus, Embase, Cochrane, Web of Science, Cochrane, CINAHL and PsychInfo were searched. We included all peer-reviewed published studies from all previous years until November 2018. Studies performed in the ED and focused on the association between EDB and IHM as the primary objective were included. Extracted data included study characteristics, prognostic factors, outcomes, and IHM. A search update in PubMed was performed in May 2019 to ensure the inclusion of recent studies before publishing.

RESULTS

From the initial 4,321 references found through the systematic search, the manual screening of reference lists and the updated search in PubMed, a total of 12 studies were identified as eligible for a descriptive analysis. Overall, six studies found an association between EDB and IHM, while five studies showed no association. The last remaining study included both ICU and non-ICU subgroups and showed conflicting results, with a positive association for non-ICU patients but no association for ICU patients. Overall, a tendency toward an association between EDB and IHM using the pool random effect was observed.

CONCLUSION

Our systematic review did not find a strong evidence for the association between ED boarding and IHM but there is a tendency toward this association. Further well-controlled, international multicenter studies are needed to demonstrate whether this association exists and whether there is a specific EDB time cut-off that results in increased IHM.

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

The most commonly used techniques for addressing each Emergency Department (ED) problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient flow time, and high left-without-being-seen (LWBS) rates) were specified to provide healthcare managers and researchers with a useful framework for effectively solving these operational deficiencies. Finally, we identified the existing research tendencies and highlighted opportunities for future work. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to undertake a review including scholarly articles published between April 1993 and October 2019. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. Furthermore, computer simulation and lean manufacturing were concluded to be the most prominent approaches for addressing the leading operational problems in EDs. In future interventions, ED administrators and researchers are widely advised to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for upgrading the performance of EDs. On a different tack, more interventions are required for tackling overcrowding and high left-without-being-seen rates.

Impact on Length of Stay of a Hospital Medicine Emergency Department Boarder Service

BACKGROUND

It is not known whether delivering inpatient care earlier to patients boarding in the emergency department (ED) by a hospitalist-led team can decrease length of stay (LOS).

OBJECTIVE

To study the association between care provided by a hospital medicine ED Boarder (EDB) service and LOS.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cross-sectional study (July 1, 2016 to June 30, 2018) conducted at a single, large, urban academic medical center. Patients admitted to general medicine services from the ED were included. EDB patients were defined as those waiting for more than two hours for an inpatient bed. Patients were categorized as covered EDB, noncovered EDB, or nonboarder.

INTERVENTION

The hospital medicine team provided continuous care to covered EDB patients waiting for an inpatient bed.

PRIMARY OUTCOME AND MEASURES

The primary outcome was median hospital LOS defined as the time period from ED arrival to hospital departure. Secondary outcomes included ED LOS and 30-day ED readmission rate.

RESULTS

There were 8,776 covered EDB, 5,866 noncovered EDB, and 2,026 nonboarder patients. The EDB service covered 59.9% of eligible patients and 62.9% of total boarding hours. Median hospital LOS was 4.76 (interquartile range [IQR] 2.90-7.22) days for nonboarders, 4.92 (IQR 3.00-8.03) days for covered EDB patients, and 5.11 (IQR 3.16-8.34) days for noncovered EDB (P < .001). Median ED LOS for nonboarders was 5.6 (IQR 4.2-7.5) hours, 20.7 (IQR 15.8-24.9) hours for covered EDB, and 10.1 (IQR 7.9-13.8) hours for noncovered EDB (P < .001). There was no difference in 30-day ED readmission rates.

CONCLUSION

Admitted patients who were not boarders had the shortest LOS. Among boarded patients, coverage by a hospital medicine-led EDB service was associated with a reduced hospital LOS.

Challenges, consequences, and lessons for way-outs to emergencies at hospitals: a systematic review study

Background

Emergency Department (ED) overcrowding adversely affects patients’ health, accessibility, and quality of healthcare systems for communities. Several studies have addressed this issue. This study aimed to conduct a systematic review study concerning challenges, lessons and way outs of clinical emergencies at hospitals.

Methods

Original research articles on crowding of emergencies at hospitals published from 1st January 2007, and 1st August 2018 were utilized. Relevant studies from the PubMed and EMBASE databases were assessed using suitable keywords. Two reviewers independently screened the titles, abstracts and the methodological validity of the records using data extraction format before their inclusion in the final review. Discussions with the senior faculty member were used to resolve any disagreements among the reviewers during the assessment phase.

Results

Out of the total 117 articles in the final record, we excluded 11 of them because of poor quality. Thus, this systematic review synthesized the reports of 106 original articles. Overall 14, 55 and 29 of the reviewed refer to causes, effects, and solutions of ED crowding, respectively. The review also included four articles on both causes and effects and another four on causes and solutions. Multiple individual patients and healthcare system related challenges, experiences and responses to crowding and its consequences are comprehensively synthesized.

Conclusion

ED overcrowding is a multi-facet issue which affects by patient-related factors and emergency service delivery. Crowding of the EDs adversely affected individual patients, healthcare delivery systems and communities. The identified issues concern organizational managers, leadership, and operational level actions to reduce crowding and improve emergency healthcare outcomes efficiently.

Predictors of Delayed Emergency Department Throughput Among Blunt Trauma Patients

BACKGROUND

Delayed emergency department (ED) LOS has been associated with increased mortality and increased hospital length of stay (LOS) for various patient populations. Trauma patients often require significant effort in evaluation, workup, and disposition; however, patient and hospital characteristics associated with increased LOS in the ED for trauma patients remain unclear.

METHODS

The Trauma Quality Improvement Project database (2014-2016) was queried for all adult blunt trauma patients. Patients discharged from the ED to the operating room were excluded. Univariate and multivariable linear regression analysis was conducted to identify independent predictors of ED LOS, controlling for patient characteristics (age, gender, race, insurance status), hospital characteristics (teaching status, ACS trauma verification level, geographic region), abbreviated injury scale and comorbid status.

RESULTS

412,000 patients met inclusion criteria for analysis. When controlling for covariates, an increase in age by 1 y resulted in 0.63 increased minutes in the ED (P < 0.001). In multivariable linear regression controlling for injury severity and comorbid conditions, non-white race groups, university status, and northeast region were associated with increased ED LOS. Black and Hispanic patients spent on average 41 and 42 more minutes, respectively, in the ED room when compared with white patients (P < 0.001). Patients seen at University hospitals spent 52 more minutes in the ED when compared with community hospitals, whereas patients at nonteaching hospitals spent 31 fewer minutes (P < 0.001). Patients seen in the Midwest spent the least amount of time in the ED, with patients in the South, West, and Northeast spending 45, 36, and 89 more minutes, respectively (P < 0.001). Non-Medicaid patients at level 1 trauma centers and those requiring intensive care admission had significantly decreased ED LOS. Medicaid patients took the longest to move through the ED with Medicare, BlueCross, and Private insurance outpacing them by 17, 23, and 23 min, respectively (P < 0.001). ACS level 1 trauma centers moved patients through the ED fastest, whereas ACS level II trauma centers and level III trauma centers moved patients through 50 and 130 min slower when compared with ACS level 1 trauma centers (P < 0.001).

CONCLUSIONS

ED LOS varied significantly by patient and hospital characteristics. Medicaid patients and those patients at university hospitals were associated with significantly higher ED LOS, whereas ACS trauma verification level status had strong correlation with ED LOS. These results may allow targeted quality improvement programs to enhance ED LOS.

Development and Evaluation of a Virtual Research Environment to Improve Quality of Care in Overcrowded Emergency Departments: Observational Study

BACKGROUND

Despite a wide range of literature on emergency department (ED) overcrowding, scientific knowledge on emergency physicians' cognitive processes coping with overcrowding is limited.

OBJECTIVE

This study aimed to develop and evaluate a virtual research environment that will allow us to study the effect of physicians' strategies and behaviors on quality of care in the context of ED overcrowding.

METHODS

A simulation-based observational study was conducted over two stages: the development of a simulation model and its evaluation. A research environment in emergency medicine combining virtual reality and simulated patients was designed and developed. Afterwards, 12 emergency physicians took part in simulation scenarios and had to manage 13 patients during a 2-hour period. The study outcome was the authenticity of the environment through realism, consistency, and mastering. The realism was the resemblance perceived by the participants between virtual and real ED. The consistency of the scenario and the participants' mastering of the environment was expected for 90% (12/13) of the participants.

RESULTS

The virtual ED was considered realistic with no significant difference from the real world with respect to facilities and resources, except for the length of time of procedures that was perceived to be shorter. A total of 100% (13/13) of participants deemed that patient information, decision making, and managing patient flow were similar to real clinical practice. The virtual environment was well-mastered by all participants over the course of the scenarios.

CONCLUSIONS

The new simulation tool, Virtual Research Environment in Emergency Medicine, has been successfully designed and developed. It has been assessed as perfectly authentic by emergency physicians compared with real EDs and thus offers another way to study human factors, quality of care, and patient safety in the context of ED overcrowding.

Decreasing the Lag Between Result Availability and Decision-Making in the Emergency Department Using Push Notifications

Introduction

Emergency department (ED) patient care often hinges on the result of a diagnostic test. Frequently there is a lag time between a test result becoming available for review and physician decision-making or disposition based on that result. We implemented a system that electronically alerts ED providers when test results are available for review via a smartphone- and smartwatch-push notification. We hypothesized this would reduce the time from result to clinical decision-making.

Methods

We retrospectively assessed the impact of the implementation of a push notification system at three EDs on time-to-disposition or time-to-follow-up order in six clinical scenarios of interest: chest radiograph (CXR) to disposition, basic metabolic panel (BMP) to disposition, urinalysis (UA) to disposition, respiratory pathogen panel (RPP) to disposition, hemoglobin (Hb) to blood transfusion order, and abnormal D-dimer to computed tomography pulmonary angiography (CTPA) order. All ED patients during a one-year period of push-notification availability were included in the study. The primary outcome was median time in each scenario from result availability to either disposition order or defined follow-up order. The secondary outcome was the overall usage rate of the opt-in push notification system by providers.

Results

During the study period there were 6115 push notifications from 4183 ED encounters (2.7% of all encounters). Of the six clinical scenarios examined in this study, five were associated with a decrease in median time from test result availability to patient disposition or follow-up order when push notifications were employed: CXR to disposition, 80 minutes (interquartile range [IQR] 32–162 minutes) vs 56 minutes (IQR 18–141 minutes), difference 24 minutes (p<0.01); BMP to disposition, 128 minutes (IQR 62–225 minutes) vs 116 minutes (IQR 33–226 minutes), difference 12 minutes (p<0.01); UA to disposition, 105 minutes (IQR 43–200 minutes) vs 55 minutes (IQR 16–144 minutes), difference 50 minutes (p<0.01); RPP to disposition, 80 minutes (IQR 28–181 minutes) vs 37 minutes (IQR 10–116 minutes), difference 43 minutes (p<0.01); and D-dimer to CTPA, 14 minutes (IQR 6–30 minutes) vs 6 minutes (IQR 2.5–17.5 minutes), difference 8 minutes (p<0.01). The sixth scenario, Hb to blood transfusion (difference 19 minutes, p=0.73), did not meet statistical significance.

Conclusion

Implementation of a push notification system for test result availability in the ED was associated with a decrease in lag time between test result and physician decision-making in the examined clinical scenarios. Push notifications were used in only a minority of ED patient encounters.

Can point-of-care testing shorten hospitalization length of stay? An exploratory investigation of infectious agents using regression modelling

This retrospective study investigates the potential benefits from the introduction of point-of-care tests for rapid diagnosis of infectious diseases. We analysed a sample of 441 hospitalized patients who had received a final diagnosis related to 18 pathogenic agents. These pathogens were mostly detected by standard tests but were also detectable by point-of-care testing. The length of hospital stay was partitioned into pre- and post-laboratory diagnosis stages. Regression analysis and elementary queueing theory were applied to estimate the impact of quick diagnosis on the mean length of stay and the utilization of healthcare resources. The analysis suggests that eliminating the pre-diagnosis times through point-of-care testing could shorten the mean length of hospital stay for infectious diseases by up to 34 per cent and result in an equal reduction in bed occupancy and other resources. Regression and other more sophisticated models can aid the financing decision-making of pilot point-of-care laboratories in healthcare systems.

Impact of Urinalysis on Medical Decision-making and Length of Stay

Introduction

The emergency department (ED) is under pressure to meet length of stay (LOS) metrics for care in the ED. An aspect that we propose affects LOS is the order for urine sample collection and subsequent urinalysis (UA) as both are time consuming steps. This project’s primary goals are to determine if ordering a UA increases LOS and how often UA contributes to clinical decision-making and/or disposition decisions in the ED. Secondary objectives were to identify factors that contribute to the ordering of a UA and to decipher if LOS was more impacted in patients who were discharged vs. admitted to the hospital.

Methods

Retrospective chart review was conducted of patients who presented to our ED in April 2016 during 12 consecutive days. Data were abstracted onto a data collection sheet with the abstractor blinded to study hypotheses. Variables included whether a UA was ordered, times of UA order and result, who ordered the UA (mid-level provider [MLP] vs. physician), whether the UA was cancelled, whether the UA result influenced clinical decision-making (based on the medical decision-making section of the physician chart) or disposition decision, LOS, age, and gender. Descriptive statistics and multivariable regression analysis were used to analyze relationships between the variables collected and their influence on LOS.

Results

The overall median LOS was 157 minutes, with an interquartile range (IQR) of 81 to 246 minutes. For discharged patients, it was 142 minutes, with an IQR of 46 to 236 minutes. For admitted patients, it was 177 minutes, with an IQR of 118 to 260 minutes. Amongst admitted patients, multivariable regression analysis demonstrated that the following factor was associated with increased LOS: being seen first by the provider-in-triage (PIT) then physician in main ED (p < 0.0001). Amongst discharged patients, multivariable regression analysis demonstrated that the following factors were associated with increased LOS: being seen first by the PIT then physician in main ED (p = 0.0296), being seen by MLP only (p < 0.0001), having a UA ordered (p = 0.0005), being seen on weekend (p = 0.0166), and being an older patient (p = 0.0475). The UA was cancelled in 9% of our patients, and in 60% of cases, these UAs were ordered by the PIT. Patient disposition decision was made prior to UA resulting in 60 cases (25%). The UA was used in clinical decision-making in 118 cases (66%). The following predictor factors were associated via univariate analysis with using a UA for decision-making: being female (p = 0.0050, 95% CI: 0.0068–0.378), being an older patient (p < 0.0001, 95% CI: -0.010 to -0.004), being first seen by the PIT and then a physician (p = 0.0486, 95% CI: 0.0048–0.1555), and discharged patients (p < 0.0001, 95% CI: -0.6749 to -0.4487).

Conclusion

Our results suggest that having a UA ordered increased ED LOS, especially in patients who are ultimately discharged. In our ED, routine UAs are ordered more often by MLPs than physicians. A routine UA may not impact clinical decision-making up to 33% of the time, nor alter disposition decision one out of four times. Given that 9% have the test eventually cancelled, one should reconsider the utility in ordering routine UAs in ED patients, as they increase LOS and place an additional burden on the patient and the ED personnel.

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.

Setting the Stage: A Comparative Analysis of an Onstage/Offstage and a Linear Clinic Modules

Objective:

The purpose of this study was to understand how two different ambulatory design modules—traditional and onstage/offstage—impact operational efficiency, patient throughput, staff collaboration, and patient privacy.

Background:

Delivery of healthcare is greatly shifting to ambulatory settings because of rapid advancement of medicine and technology, resulting in more day procedures and follow-up care occurring outside of hospitals. It is anticipated that outpatient services will grow roughly 15–23% within the next 10 years (Sg2, 2014). Nonetheless, there is limited research that evaluates how the built environment impacts care delivery and patient outcomes.

Method:

This is a cross-sectional, comparative study consisted of a mixed-method approach that included shadowing clinic staff and observing and surveying patients. The linear module had shared corridors and publicly exposed workstations, whereas the onstage/offstage module separates patient/visitors from staff with dedicated patient corridors leading to exam rooms (onstage) and enclosed staff work cores (offstage). Roughly 35 hr of clinic staff shadowing and 55 hr of patient observations occurred. A total of 269 questionnaires were completed by patients/visitors.

Results:

The results demonstrate that the onstage/offstage module significantly improved staff workflow, reduced travel distances, increased communication in private areas, and significantly reduced patient throughput and wait times. However, patients’ perception of privacy did not change among the two modules.

Conclusion:

Compared to the linear module, this study provides evidence that the onstage/offstage module could have helped to optimize operational efficiencies, staff workflow, and patient throughput.

Simulation of a Novel Schedule for Intensivist Staffing to Improve Continuity of Patient Care and Reduce Physician Burnout

OBJECTIVE

Despite widespread adoption of in-house call for ICU attendings, there is a paucity of research on optimal scheduling of intensivists to provide continuous on-site coverage. Overnight call duties have traditionally been added onto 7 days of continuous daytime clinical service. We designed an alternative ICU staffing model to increase continuity of attending physician care for patients while also decreasing interruptions to attendings' nonclinical weeks.

DESIGN

Computer-based simulation of a 1-year schedule.

SETTING

A simulated ICU divided into two daytime teams each covered by a different attending and both covered by one overnight on-call attending.

SUBJECTS

Simulated patients were randomly admitted on different service days to assess continuity of care.

INTERVENTIONS

A "shared service schedule" was compared to a standard "7 days on schedule." For the 7 days on schedule, an attending covered a team for 7 consecutive days and off-service attendings cross-covered each night. For the shared schedule, four attendings shared the majority of daytime and nighttime service for two teams over 2 weeks, with recovery periods built into the scheduled service time.

MEASUREMENTS AND MAIN RESULTS

Continuity of care as measured by the Continuity of Attending Physician Index increased by 9% with the shared schedule. Annually, the shared service schedule was predicted to increase free weekends by 3.4 full weekends and 1.3 weekends with either Saturday or Sunday off. Full weeks without clinical obligations increased by 4 weeks. Mean time between clinical obligations increased by 5.8 days.

CONCLUSIONS

A shared service schedule is predicted to improve continuity of care while increasing free weekends and continuity of uninterrupted nonclinical weeks for attendings. Computer-based simulation allows assessment of benefits and tradeoffs of the alternative schedule without disturbing existing clinical systems.

Does certificate of need law enhance competition in inpatient care market? An empirical analysis

This article investigates the impact of Certificate of Need (CON) laws on competition in the inpatient care market. One of the major criticisms of these laws is that it may hinder competition in the health care market, which can lead to higher prices. However, from a theoretical standpoint, CON laws could also promote competition by limiting excessive expansion from incumbents. Our main conclusion is that CON laws by and large enhanced competition in the inpatient market during the period of our study. This indicates that the effects of CON laws to hinder predatory behavior could dominate its effects of preventing new entrants into the inpatient care market. We do not find statistically significant evidence to reject the exogeneity assumption of either CON laws or their stringency in our study. We also find factors such as proportion of population aged 18-44, proportion of Asian American population, obesity rate, political environment, etc., in a state significantly impact competition. Our findings could shed some light to public policy makers when deciding the appropriate health programs or legislative framework to promote health care market competition and thereby facilitate quality health care.

Push-Alert Notification of Troponin Results to Physician Smartphones Reduces the Time to Discharge Emergency Department Patients: A Randomized Controlled Trial

STUDY OBJECTIVE

For emergency department (ED) patients with chest pain, discharge decisions often hinge on troponin results. Push-alert notifications deliver results immediately to physician smartphones. Our objective is to determine whether troponin push alerts improve the time to discharge decisions for ED patients with chest pain.

METHODS

In an academic ED, we assessed the effect of a quality improvement initiative using troponin push alerts to physician smartphones, with a cluster-randomized evaluation. Participating physicians were randomized to receive troponin push alerts (intervention) or not receive them (control). We retrospectively identified patients treated by participating physicians during the study period who were discharged from the ED with chest pain. The primary outcome was the time from final troponin result to discharge decision. Secondary outcomes included length of stay. A linear mixed model was used to adjust for physician clustering.

RESULTS

During the study, 1,554 patients were discharged from the ED with chest pain. There were 551 patients in the control group and 554 in the intervention group who met inclusion criteria. The overall median interval from final troponin result to discharge decision was 79.7 minutes (interquartile range [IQR] 33.6 to 167.8 minutes); it was 94.3 minutes (IQR 36.2 to 177.8 minutes) in the control group and 68.5 minutes (IQR 30.5 to 157.2 minutes) in the intervention group. This 25.8-minute difference in medians (95% confidence interval 24.6 to 28.0 minutes) was statistically significant. Total ED length of stay was 345 minutes (IQR 261 to 419 minutes) in the control group and 328 minutes (IQR 250 to 408 minutes) in the intervention group.

CONCLUSION

Physicians who received troponin push alerts discharged their patients with chest pain 26 minutes faster than those without troponin notifications. Total ED length of stay did not significantly improve for these patients.

Applying Systems Engineering Reduces Radiology Transport Cycle Times in the Emergency Department

INTRODUCTION

Emergency department (ED) crowding is widespread, and can result in care delays, medical errors, increased costs, and decreased patient satisfaction. Simultaneously, while capacity constraints on EDs are worsening, contributing factors such as patient volume and inpatient bed capacity are often outside the influence of ED administrators. Therefore, systems engineering approaches that improve throughput and reduce waste may hold the most readily available gains. Decreasing radiology turnaround times improves ED patient throughput and decreases patient waiting time. We sought to investigate the impact of systems engineering science targeting ED radiology transport delays and determine the most effective techniques.

METHODS

This prospective, before-and-after analysis of radiology process flow improvements in an academic hospital ED was exempt from institutional review board review as a quality improvement initiative. We hypothesized that reorganization of radiology transport would improve radiology cycle time and reduce waste. The intervention included systems engineering science-based reorganization of ED radiology transport processes, largely using Lean methodologies, and adding no resources. The primary outcome was average transport time between study order and complete time. All patients presenting between 8/2013-3/2016 and requiring plain film imaging were included. We analyzed electronic medical record data using Microsoft Excel and SAS version 9.4, and we used a two-sample t-test to compare data from the pre- and post-intervention periods.

RESULTS

Following the intervention, average transport time decreased significantly and sustainably. Average radiology transport time was 28.7 ± 4.2 minutes during the three months pre-intervention. It was reduced by 15% in the first three months (4.4 minutes [95% confidence interval [CI] 1.5-7.3]; to 24.3 ± 3.3 min, P=0.021), 19% in the following six months (5.4 minutes, 95% CI [2.7-8.2]; to 23.3 ± 3.5 min, P=0.003), and 26% one year following the intervention (7.4 minutes, 95% CI [4.8-9.9]; to 21.3 ± 3.1 min, P=0.0001). This result was achieved without any additional resources, and demonstrated a continual trend towards improvement. This innovation demonstrates the value of systems engineering science to increase efficiency in ED radiology processes.

CONCLUSION

In this study, reorganization of the ED radiology transport process using systems engineering science significantly increased process efficiency without additional resource use.

Development of a Model to Measure Emergency Department Staffing Limitations

BACKGROUND

The optimal staffing model for emergency departments (EDs) is not known. Improving staffing could lead to more timely, efficient, and effective care. We created a model of staffing to identify times of staffing limitation by provider type.

METHODS

We analyzed data from an academic pediatric ED with 60,000 visits per year. Each 10-minute interval from January 1, 2011, through December 31, 2012, was categorized as nonlimited (no staffing limitation), space limited (≥2 patients in the waiting room with wait times > 30 minutes and ≥ 80% ED bed occupancy), nurse limited (≥2 patients in the waiting room with wait times > 30 min and < 80% ED bed occupancy), or physician limited (≥2 patients in examination rooms who have waited > 30 minutes for a physician) using computer modeling. We calculated the percentage of time each type of limitation was in effect and the median lengths of stay for patients presenting during times of each category of limitation.

RESULTS

The ED was space limited 5.0% of the time, nurse limited 16.1% of the time, and physician limited 0.1% of the time. In nonlimited times, length of stay was 201 minutes (interquartile range, 128-301), whereas patients presenting during space-limited, nurse-limited, and physician-limited times had statistically significantly higher LOS of 265 (187-360), 244 (169-337), and 247 (174-334) minutes, respectively.

CONCLUSIONS

Times identified as space and staffing limited were associated with longer LOS. This computer model could be used to rapidly identify targeted staffing needs and then measure the effect of modifying staffing.

The impact of emergency department segmentation and nursing staffing increase on inpatient mortality and management times

Background

The aim of our study was to investigate the impact of a new organization of our emergency department (ED) on patients’ mortality and management delays.

Methods

The ED segmentation consisted of the development of a new patient care geographical layout on a pre-existing site and changing the organization of patient flow. It took place on May 10, 2012. We did a before-after study in the ED of a university hospital, “before” (winter 2012) and “after” (summer 2012) reorganization by segmentation into sectors. All ED patients were included.

Results

Eighty-three thousand three hundred twenty-two patient visits were analyzed, 61,118 in phase “before”, 22,204 during the phase “after”. The overall inpatient mortality was 1.5 % during summer 2011 (“before” period), 1.8 % during winter 2012 (“before” period), 1.3 % during summer 2012 (“after” period) period (summer 2012 vs. winter 2012, OR = 0.72; 95 % CIs [0.61, 0.85], and summer 2012 vs. summer 2011, OR = 0.85; 95 % CIs [0.72, 0.99]). The mean (SD) time to first medical contact was 129 min (±133) during winter 2012 and 104 min (± 95) during summer 2012 (p < .05).

Conclusions

Our study showed a decrease in mortality and improvement in time to first medical contact after the segmentation of our ED and nursing staffing increase, without an increase in medical personnel. Improving patient care through optimizing ED segmentation may be an effective strategy.

Quality Improvement With Discrete Event Simulation: A Primer for Radiologists

The application of simulation software in health care has transformed quality and process improvement. Specifically, software based on discrete-event simulation (DES) has shown the ability to improve radiology workflows and systems. Nevertheless, despite the successful application of DES in the medical literature, the power and value of simulation remains underutilized. For this reason, the basics of DES modeling are introduced, with specific attention to medical imaging. In an effort to provide readers with the tools necessary to begin their own DES analyses, the practical steps of choosing a software package and building a basic radiology model are discussed. In addition, three radiology system examples are presented, with accompanying DES models that assist in analysis and decision making. Through these simulations, we provide readers with an understanding of the theory, requirements, and benefits of implementing DES in their own radiology practices.

Forecasting patient length of stay in an emergency department by artificial neural networks

Emergency departments (EDs) have faced with high patient demand during peak hours in comparison to the other departments of hospitals because of their complexity and uncertainty. Therefore prolonged waiting times in EDs have caused the dissatisfaction on patients. Patient length of stay (LOS), also known as patient throughput time, is generally considered to be the length of time that passes from the patient’s time of arrival at the ED until time of discharge or transfer to another department of the hospital. Starting from patient admissions to the EDs it becomes important have to be known the overall LOS in terms of right resource allocation and efficient utilization of the department. For this purpose this paper aims to forecast patient LOS using Artificial Neural Network (ANN) within the input factors that are predictive such as patient age, sex, mode of arrival, treatment unit, medical tests and inspection in the ED. The method can be used to provide insights to ED medical staff (doctors, nurses etc.) determining patient LOS.

Computer modeling of lung cancer diagnosis-to-treatment process

We introduce an example of a rigorous, quantitative method for quality improvement in lung cancer care-delivery. Computer process modeling methods are introduced for lung cancer diagnosis, staging and treatment selection process. Two types of process modeling techniques, discrete event simulation (DES) and analytical models, are briefly reviewed. Recent developments in DES are outlined and the necessary data and procedures to develop a DES model for lung cancer diagnosis, leading up to surgical treatment process are summarized. The analytical models include both Markov chain model and closed formulas. The Markov chain models with its application in healthcare are introduced and the approach to derive a lung cancer diagnosis process model is presented. Similarly, the procedure to derive closed formulas evaluating the diagnosis process performance is outlined. Finally, the pros and cons of these methods are discussed.

Using discrete event computer simulation to improve patient flow in a Ghanaian acute care hospital

OBJECTIVES

Crowding and limited resources have increased the strain on acute care facilities and emergency departments worldwide. These problems are particularly prevalent in developing countries. Discrete event simulation is a computer-based tool that can be used to estimate how changes to complex health care delivery systems such as emergency departments will affect operational performance. Using this modality, our objective was to identify operational interventions that could potentially improve patient throughput of one acute care setting in a developing country.

METHODS

We developed a simulation model of acute care at a district level hospital in Ghana to test the effects of resource-neutral (eg, modified staff start times and roles) and resource-additional (eg, increased staff) operational interventions on patient throughput. Previously captured deidentified time-and-motion data from 487 acute care patients were used to develop and test the model. The primary outcome was the modeled effect of interventions on patient length of stay (LOS).

RESULTS

The base-case (no change) scenario had a mean LOS of 292 minutes (95% confidence interval [CI], 291-293). In isolation, adding staffing, changing staff roles, and varying shift times did not affect overall patient LOS. Specifically, adding 2 registration workers, history takers, and physicians resulted in a 23.8-minute (95% CI, 22.3-25.3) LOS decrease. However, when shift start times were coordinated with patient arrival patterns, potential mean LOS was decreased by 96 minutes (95% CI, 94-98), and with the simultaneous combination of staff roles (registration and history taking), there was an overall mean LOS reduction of 152 minutes (95% CI, 150-154).

CONCLUSIONS

Resource-neutral interventions identified through discrete event simulation modeling have the potential to improve acute care throughput in this Ghanaian municipal hospital. Discrete event simulation offers another approach to identifying potentially effective interventions to improve patient flow in emergency and acute care in resource-limited settings.

Emergency care and health systems: consensus-based recommendations and future research priorities

The theme of the 14th annual Academic Emergency Medicine consensus conference was "Global Health and Emergency Care: A Research Agenda." The goal of the conference was to create a robust and measurable research agenda for evaluating emergency health care delivery systems. The concept of health systems includes the organizations, institutions, and resources whose primary purpose is to promote, restore, and/or maintain health. This article further conceptualizes the vertical and horizontal delivery of acute and emergency care in low-resource settings by defining specific terminology for emergency care platforms and discussing how they fit into broader health systems models. This was accomplished through discussion surrounding four principal questions touching upon the interplay between health systems and acute and emergency care. This research agenda is intended to assist countries that are in the early stages of integrating emergency services into their health systems and are looking for guidance to maximize their development and health systems planning efforts.