Modeling the impact of changing patient flow processes in an emergency department: Insights from a computer simulation study

A review of applications of operational research in healthcare coordination in disaster management

Many disasters that have happened in the last decades, including the latest COVID-19 pandemic, have caused a shortage of healthcare resources and change in healthcare operations. Given these impacts, the Operational Research (OR) community has applied various approaches to improve the emergency medical responses. Coordination of healthcare facilities is one of the emergency medical response strategies to ensure the continued provision of medical services during disasters. Although the existing literature reviews of OR approaches have included the perspective of healthcare management, they focused mostly on the application of OR in disaster operations and logistics management. The importance of coordination in healthcare systems during disasters is well recognised in the literature, but to the best of our knowledge there has been no review of the published research in this area. This study provides a focused literature review of the OR contributions in the coordination in healthcare systems during disasters. Definitions of the terms in use in this field are provided. An overall descriptive statistics of the reviewed articles is given, followed by the review of the presented research problems, disaster types, and developed methodologies. The main characteristics of models for the coordination in the healthcare system are described. Measures of coordination effectiveness that denote healthcare resilience are discussed. Based on our findings, we suggest future research directions in the context of existing models extension, and application and development of other methodologies with the aim to provide a solid basis for OR research in the healthcare disaster management.

Process mining based on patient waiting time: an application in health processes

Purpose

Similar to many business processes, waiting times are also essential for health care processes, especially in obstetrics and gynecology outpatient department (GOD), because pregnant women may be affected by long waiting times. Since creating process models manually presents subjective and nonrealistic flows, this study aims to meet the need of an objective and realistic method.

Design/methodology/approach

In this study, the authors investigate time-related bottlenecks in both departments for different doctors by process mining. Process mining is a pragmatic analysis to obtain meaningful insights through event logs. It applies data mining techniques to business process management with more comprehensive perspectives. Process mining in this study enables to automatically create patient flows to compare considering each department and doctor.

Findings

The study concludes that average waiting times in the GOD are higher than obstetrics outpatient department. However, waiting times in departments can change inversely for different doctors.

Research limitations/implications

The event log was created by expert opinions because activities in the processes had just starting timestamp. The ending time of activity was computed by considering the average duration of the corresponding activity under a normal distribution.

Originality/value

This study focuses on administrative (nonclinical) health processes in obstetrics and GOD. It uses a parallel activity log inference algorithm (PALIA) to produce process trees by handling duplicate activities. Infrequent information in health processes can have critical information about the patient. PALIA considers infrequent activities in the event log to extract meaningful information, in contrast to many discovery algorithms.

Simulation-based optimisation approach to improve emergency department resource planning: A case study of Tunisian hospital

BACKGROUND

The emergency department (ED) is a gateway to hospitals and is in the centre of hospital management efforts. It is often saturated by a continuous flow of patients, which causes excessive patient waiting time.

AIMS

This study integrates simulations with optimisation to design planning decision support for an ED. We considered all the processes of the ED, from triage to bed assignment. This study's main objective was to determine the optimal number of doctors, nurses, and beds required to schedule patients with different acuity levels to minimise both the total patient waiting time and the patient average length of stay and balance the resource utilisation rates. The problem is also characterised by multiple uncertainties, such as the patient arrival rate and service times in each stage of the process.

METHOD

We first propose a stochastic mixed-integer programing model that is solved using the sample average approximation approach. The resulting resource sizing is then evaluated using a discrete-event simulation model by comparing different patient scheduling rules.

RESULTS

Numerical experiments highlight the performance of the proposed approach using data from a Tunisian ED hospital.

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.

Data-Driven Design Strategies to Address Crowding and Boarding in an Emergency Department: A Discrete-Event Simulation Study

OBJECTIVE

To address prolonged lengths of stay (LOS) in a Level 1 trauma center, we examined the impact of implementing two data-driven strategies with a focus on the physical environment.

BACKGROUND

Crowding in emergency departments (EDs) is a widely reported problem leading to increased service times and patients leaving without being seen.

METHODS

Using ED historical data and expert estimates, we created a discrete-event simulation model. We analyzed the likely impact of initiating care and boarding patients in the hallway (hallway care) instead of the exam rooms and adding a dedicated triage space for patients who arrive by emergency medical services (EMS triage) to decrease hallway congestion. The scenarios were compared in terms of LOS, time spent in exam rooms and hallway spaces, service time, blocked time, and utilization rate.

RESULTS

The hallway care scenario resulted in significantly lower LOS and exam room time only for EMS patients but when implemented along with the EMS triage scenario, a significantly lower LOS and exam room time was observed for all patients (EMS and walk-in). The combination of two simulated scenarios resulted in significant improvements in other flow metrics as well.

CONCLUSIONS

Our findings discourage boarding of admitted patients in ED exam rooms. If space limitations require that admitted patients be placed in ED hallways, designers and planners should consider enabling hallway spaces with features recommended in this article. Alternative locations for boarding should be prioritized in or out of the ED. Our findings also encourage establishing a triage area dedicated to EMS patients in the ED.

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.

Validating Service Quality (SERVQUAL) in Healthcare: Measuring Patient Satisfaction Using their Perceptions in Jordan

Patient satisfaction in the developing world has not received sufficient interest in the healthcare literature. More importantly, models predicting patient satisfaction seldom incorporates patient perspectives into their measurement providing ill-suited metrics for healthcare administrators to make decisive decisions concerning service quality improvements. The current analysis utilizes original data collected from 336 patients in Jordan. This paper tests whether service quality (SERVQUAL) is suitable to be used in the new context and concluded that SERVQUAL is reliable and valid in supplying stakeholders with reliable and valid information concerning patient satisfaction. Further, the analysis suggests a large gap between perceived and expected services performed by Jordanian hospitals signalling the need to service quality enhancement. The study calls for the adoption of agile and rapid patient screening models in emergency departments to reduce wait times and decrease the number of patients left without being seen. This study constitutes an emerging attempt at better understanding how service quality influences patient satisfaction, and more importantly, introduce affordable and cost-effective solutions capable of improving satisfaction in the short run.

Constructing Holistic Patient Flow Simulation Using System Approach

Patient flow often described as a systemic issue requiring a systemic approach because hospital is a collection of highly dynamic, interconnected, complex, ad hoc and multi-disciplinary sub-processes. However, studies on holistic patient flow simulation following system approach are limited and/or poorly understood. Several researchers have been investigating single departments such as ambulatory care unit, Intensive Care Unit (ICU), emergency department, surgery department or patients’ interaction with limited resources such as doctor, endoscopy or bed, independently. Hence, this article demonstrates how to achieve system approach in constructing holistic patient flow simulation, while maintaining the balance between the complexity and the simplicity of the model. To this end, system approach, network analysis and discrete event simulation (DES) were employed. The most important departments in the diagnosis and treatment process are identified by analyzing network of hospital departments. Holistic patient flow simulation is constructed using DES following system approach. Case studies are conducted and the results illustrate that healthcare systems must be modeled and investigated as a complex and interconnected system so that the real impact of changes on the entire system or parts of the system could be observed at strategic as well as operational levels.

Improving service in an emergency department by designing the health production flow

Background

Most emergency departments have overcapacity with poor service measured by length of stay. We hypothesized that a formal design of the emergency department production flows will improve service. Thus, we propose a methodology that was tested in a large hospital, including new flow implementation.

Results

We implemented new workflows during June to July 2017. A comparison of the patients’ average length of stay from June to September shows a decrease of 26%. Additionally, a comparison with 2016 shows a decrease of 50%. Direct evaluation of the value generated reveals an emergency department admissions increase of 540 monthly, equivalent of a savings of approximately US$250.000 annually. This savings is a very conservative estimate because the most significant value of this work is fast service that diminishes the patients’ risks.

Conclusions

Production design is an important problem in health services in terms of potential service improvements, executable with a formal, systemic, replicable method founded on several disciplines. Thus, we are replicating the approach at other hospitals with extensions to other services.

Performance Analysis of Emergency Room Episodes Through Process Mining

The performance analysis of Emergency Room episodes is aimed at providing decision makers with knowledge that allows them to decrease waiting times, reduce patient congestion, and improve the quality of care provided. In this case study, Process Mining is used to determine which activities, sub-processes, interactions, and characteristics of episodes explain why some episodes have a longer duration. The employed method and the results obtained are described in detail to serve as a guide for future performance analysis in this domain. It was discovered that the main cause of the increment in the episode duration is the occurrence of a loop between the Examination and Treatment sub-processes. It was also found out that as the episode severity increases, the number of repetitions of the Examination-Treatment loop increases as well. Moreover, the episodes in which this loop is more common are those that lead to Hospitalization as discharge destination. These findings might help to reduce the occurrence of this loop, in turn lowering the episode duration and, consequently, providing faster attention to more patients.

Theoretical bounds and approximation of the probability mass function of future hospital bed demand

Failing to match the supply of resources to the demand for resources in a hospital can cause non-clinical transfers, diversions, safety risks, and expensive under-utilized resource capacity. Forecasting bed demand helps achieve appropriate safety standards and cost management by proactively adjusting staffing levels and patient flow protocols. This paper defines the theoretical bounds on optimal bed demand prediction accuracy and develops a flexible statistical model to approximate the probability mass function of future bed demand. A case study validates the model using blinded data from a mid-sized Massachusetts community hospital. This approach expands upon similar work by forecasting multiple days in advance instead of a single day, providing a probability mass function of demand instead of a point estimate, using the exact surgery schedule instead of assuming a cyclic schedule, and using patient-level duration-varying length-of-stay distributions instead of assuming patient homogeneity and exponential length of stay distributions. The primary results of this work are an accurate and lengthy forecast, which provides managers better information and more time to optimize short-term staffing adaptations to stochastic bed demand, and a derivation of the minimum mean absolute error of an ideal forecast.

Queueing theoretic analysis of labor and delivery : Understanding management styles and C-section rates

Childbirth is a complex clinical service requiring the coordinated support of highly trained healthcare professionals as well as management of a finite set of critical resources (such as staff and beds) to provide safe care. The mode of delivery (vaginal delivery or cesarean section) has a significant effect on labor and delivery resource needs. Further, resource management decisions may impact the amount of time a physician or nurse is able to spend with any given patient. In this work, we employ queueing theory to model one year of transactional patient information at a tertiary care center in Boston, Massachusetts. First, we observe that the M/G/∞ model effectively predicts patient flow in an obstetrics department. This model captures the dynamics of labor and delivery where patients arrive randomly during the day, the duration of their stay is based on their individual acuity, and their labor progresses at some rate irrespective of whether they are given a bed. Second, using our queueing theoretic model, we show that reducing the rate of cesarean section - a current quality improvement goal in American obstetrics - may have important consequences with regard to the resource needs of a hospital. We also estimate the potential financial impact of these resource needs from the hospital perspective. Third, we report that application of our model to an analysis of potential patient coverage strategies supports the adoption of team-based care, in which attending physicians share responsibilities for patients.

A Review on the Contribution of Emergency Department Simulation Studies in Reducing Wait Time

Background: Because of the important role of hospital emergency departments (EDs) in providing urgent care, EDs face a constantly large demand that often results in long wait times. Objective: To review and analyze the existing literature in ED simulation modeling and its contribution in reducing patient wait time. Methods: A literature review was conducted on simulation modeling in EDs. Results: A total of 41 articles have met the inclusion criteria. The papers were categorized based on their motivations, modeling techniques, data collection processes, patient classification, recommendations, and implementation statuses. Real impact is seldom measured; only four papers (~10%) have reported the implementation of their recommended changes in the real world. Conclusion: The reported implementations contributed significantly to wait time reduction, but the proportion of simulation studies that are implemented is too low to conclude causality. Researchers should budget resources to implement their simulation recommendations in order to measure their impact on patient wait time.

Optimization of healthcare supply chain in context of macro-ergonomics factors by a unique mathematical programming approach

This study presents an integrated approach for analyzing the impact of macro-ergonomics factors in healthcare supply chain (HCSC) by data envelopment analysis (DEA). The case of this study is the supply chain (SC) of a real hospital. Thus, healthcare standards and macro-ergonomics factors are considered to be modeled by the mathematical programming approach. Over 28 subsidiary SC divisions with parallel missions and objectives are evaluated by analyzing inputs and outputs through DEA. Each division in this HCSC is considered as decision making unit (DMU). This approach can analyze the impact of macro-ergonomics factors on supply chain management (SCM) in healthcare sector. Also, this method ranks the relevant performance efficiencies of each HCSC. In this study by using proposed method, the most effective macro-ergonomics factor on HCSC is identified as "teamwork" issue. Also, this study would help managers to identify the areas of weaknesses in their SCM system and set improvement target plan for the related SCM system in healthcare industry. To the best of our knowledge, this is the first study for macro-ergonomics optimization of HCSC.

Are Split Flow and Provider in Triage Models in the Emergency Department Effective in Reducing Discharge Length of Stay?

A quality improvement (QI) project was completed early in 2015 to evaluate the split flow model of care delivery and a provider in triage model within a newly constructed emergency department. The QI project compared 2 emergency departments of similar volumes, one that splits the patient flow and employs a provider in triage model and the other that blends the patient flow and employs a traditional nurse triage model. A total of 68,603 patients were included in this project. The purpose of the split flow model is to create a second flow stream of patients through the emergency department, parallel to the regular acute/critical care flow stream, for patients with problems that are not complex. Specific patient outcomes that were evaluated for the purpose of this QI project were door to discharge or discharge length of stay (DLOS) for all ED patients. The provider in triage model enhances patient triage assessment, as well as patient flow within the emergency department, by allowing patients to be evaluated by an ED provider immediately at the point of triage when the patient first presents to the emergency department. The QI project demonstrated that the split flow model alone reduced DLOS for all ED patients, and when coupled with the provider in triage model, a greater reduction in DLOS, as well as an improvement in front-end throughput metrics, was realized.

Solving the worldwide emergency department crowding problem - what can we learn from an Israeli ED?

ED crowding is a prevalent and important issue facing hospitals in Israel and around the world, including North and South America, Europe, Australia, Asia and Africa. ED crowding is associated with poorer quality of care and poorer health outcomes, along with extended waits for care. Crowding is caused by a periodic mismatch between the supply of ED and hospital resources and the demand for patient care. In a recent article in the Israel Journal of Health Policy Research, Bashkin et al. present an Ishikawa diagram describing several factors related to longer length of stay (LOS), and higher levels of ED crowding, including management, process, environmental, human factors, and resource issues. Several solutions exist to reduce ED crowding, which involve addressing several of the issues identified by Bashkin et al. This includes reducing the demand for and variation in care, and better matching the supply of resources to demands in care in real time. However, what is needed to reduce crowding is an institutional imperative from senior leadership, implemented by engaged ED and hospital leadership with multi-disciplinary cross-unit collaboration, sufficient resources to implement effective interventions, access to data, and a sustained commitment over time. This may move the culture of a hospital to facilitate improved flow within and across units and ultimately improve quality and safety over the long-term.