Leveraging discrete event simulation modeling to evaluate design and process improvements of an emergency department

This study exemplifies the practical application of the Discrete Event Simulation (DES) approach for evaluating the effectiveness of suggested processes and design modifications in improving the existing bottlenecks of an Emergency Department. EDs are under escalating pressure to deliver efficient care while handling considerable challenges, such as overcrowding, delays, length of stay, safety risks, or staffing. Many ED appointments are non-urgent and can be treated in an alternative outpatient setting. Suitable demand-capacity matching and adjusted admission protocols reduce ED patients' Length of Stay (LOS) and improve boarding times. Alternatively, new design suggestions include applying results-pending areas where lower acuity patients wait for their pending lab or imaging results. In this study, DES assesses underlying conditions and existing bottlenecks in an existing ED. The current ED flow involved a "pull-until-full" for exam room boarding and bedside registration after triage fulfillment. Nonetheless, the ED experienced boarding delays for patients waiting to be admitted into the hospital. This study explored two scenarios in DES as potential alternatives for reducing LOS: the implication of a "rapid-admit" protocol and a "results-pending" area. Findings showed that the Rapid-Admit process reduced the admitted patient's LOS by 16%. On average, the results-pending implication reduced the admit LOS by an average of 32% across all ESI levels. These findings suggest the importance of process, staffing, and spatial modifications to achieve ED operational improvements. DES enabled a data-driven approach to evaluate bottlenecks, enhance architect-owner communication, and optimize the system for future design and process improvement alternatives

Improving Patient’s Satisfaction at Urgent Care Clinics by Using Simulation-based Risk Analysis and Quality Improvement

Several factors are expected to significantly increase stakeholders’ interest in healthcare simulation studies in the foreseeable future, e.g., the use of metrics for performance measurement, and increasing patients’ expectations. Total time spent by a patient as an important issue leads to patients’ dissatisfaction which should be improved in any healthcare facility. We reported on the use of discrete event simulation modeling, quality function deployment (QFD) and failure mode effects analysis (FMEA) to support process improvements at urgent care clinics. The modeling helped identify improvement alternatives such as optimized healthcare facility staff numbers. It also showed that lack of identified role for all team members and inconsistent process of ordering and receiving blood products and lab results are crucial failures that may occur. Moreover, using experienced staff and forcing staff to follow correct procedures are important technical aspects of improving the urgent care clinics in order to increase patient’s satisfaction. Quantitative results from the modeling provided motivation to implement the improvements. Statistical analysis of data taken before and after the implementation indicate that total time spent by a patient was significantly improved and the after result of waiting time is also decreased

Improving Patient’s Satisfaction at Urgent Care Clinics by Using Simulation-based Risk Analysis and Quality Improvement

Several factors are expected to significantly increase stakeholders’ interest in healthcare simulation studies in the foreseeable future, e.g., the use of metrics for performance measurement, and increasing patients’ expectations. Total time spent by a patient as an important issue leads to patients’ dissatisfaction which should be improved in any healthcare facility. We reported on the use of discrete event simulation modeling, quality function deployment (QFD) and failure mode effects analysis (FMEA) to support process improvements at urgent care clinics. The modeling helped identify improvement alternatives such as optimized healthcare facility staff numbers. It also showed that lack of identified role for all team members and inconsistent process of ordering and receiving blood products and lab results are crucial failures that may occur. Moreover, using experienced staff and forcing staff to follow correct procedures are important technical aspects of improving the urgent care clinics in order to increase patient’s satisfaction. Quantitative results from the modeling provided motivation to implement the improvements. Statistical analysis of data taken before and after the implementation indicate that total time spent by a patient was significantly improved and the after result of waiting time is also decreased

Integration of simulation and DEA to determine the most efficient patient appointment scheduling model for a specific healthcare setting

Purpose: This study is to develop a systematic approach for determining the most efficient patient appointment scheduling (PAS) model for a specific healthcare setting with its multiple appointments requests characteristics in order to increase patients’ accessibility and resource utilization, and reduce operation cost. In this study, three general appointment scheduling models, centralized scheduling model (CSM), decentralized scheduling model (DSM) and hybrid scheduling model (HSM), are considered. Design/methodology/approach: The integration of discrete event simulation and data envelopment analysis (DEA) is applied to determine the most efficient PAS model. Simulation analysis is used to obtain the outputs of different configurations of PAS, and the DEA based on the simulation outputs is applied to select the best configuration in the presence of multiple and contrary performance measures. The best PAS configuration provides an optimal balance between patient satisfaction, schedulers’ utilization and the cost of the scheduling system and schedulers’ training. Findings: In the presence of high proportion (more than 70%) of requests for multiple appointments, CSM is the best PAS model. If the proportion of requests for multiple appointments is medium (25%-50%), HSM is the best. Finally, if the proportion of requests for multiple appointments is low (less than 15%), DSM is the best. If the proportion is in the interval from 15% to 25% the selected PAS model could be either DSM or HSM based on expert idea. Similarly, if the proportion is in the interval from 50% to 70% the best PAS model could be either CSM or HSM. Originality/value: This is the first study that determines the best PAS model for a particular healthcare setting. The proposed approach can be used in a variety of the healthcare settings. Keywords: data envelopment analysis, discrete event simulation, patient appointment scheduling, multiple appointments, centralized scheduling model, decentralized scheduling model, hybrid scheduling modelPeer Reviewe

Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years

[EN] Objective To evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years. Materials and methods Temporal Variability Assessment (TVA) based on probabilistic data quality assessment was applied to the historic monthly-batched admission data of Hospital La Fe Valencia, Spain from 2010 to 2016. Routine healthcare data with a complete EHR was expanded by processed variables such as the Charlson Comorbidity Index. Results Four Process-Reengineering interventions were detected by quantifiable effects on the EHR: (1) the hospital relocation in 2011 involved progressive reduction of admissions during the next four months, (2) the hospital services re-configuration incremented the number of inter-services transfers, (3) the care-services re-distribution led to transfers between facilities (4) the assignment to the hospital of a new area with 80,000 patients in 2015 inspired the discharge to home for follow up and the update of the pre-surgery planned admissions protocol that produced a significant decrease of the patient length of stay. Discussion TVA provides an indicator of the effect of process re-engineering interventions on healthcare practice. Evaluating the effect of facilities¿ relocation and increment of citizens (findings 1, 3¿4), the impact of strategies (findings 2¿3), and gradual changes in protocols (finding 4) may help on the hospital management by optimizing interventions based on their effect on EHRs or on data reuse. Conclusions The effects on hospitals EHR due to process re-engineering interventions can be evaluated using the TVA methodology. Being aware of conditioned variations in EHR is of the utmost importance for the reliable reuse of routine hospitalization data.F.J.P.B, C.S., J.M.G.G. and J.A.C. were funded Universitat Politecnica de Valencia, project "ANALISIS DE LA CALIDAD Y VARIABILIDAD DE DATOS MEDICOS". www.upv.es. J.M.G.G.is also partially supported by: Ministerio de Economia y Competitividad of Spain through MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R); and European Commission projects H2020-SC1-2016-CNECT Project (No. 727560) and H2020-SC1-BHC-2018-2020 (No. 825750). The funders did not play any role in the study design, data collection and analysis, decision to publish, nor preparation of the manuscript.Perez-Benito, FJ.; Sáez Silvestre, C.; Conejero, JA.; Tortajada, S.; Valdivieso, B.; Garcia-Gomez, JM. (2019). Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years. PLoS ONE. 14(8):1-19. https://doi.org/10.1371/journal.pone.0220369S119148Aguilar-Savén, R. S. (2004). Business process modelling: Review and framework. International Journal of Production Economics, 90(2), 129-149. doi:10.1016/s0925-5273(03)00102-6Poulymenopoulou, M. 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Emergency department design evaluation and optimization using discrete event simulation

The proposed research would help any architect/owner decide the number of rooms/ cubicles for each sub-department of the ED, as well as have an estimated price for the ED, in order to optimally serve patients entering the ED with a known arrival rate. A thorough literature review was undertaken to collect data concerning the application of decision support tools for minimizing patient waiting times and maximizing the utilization rate in health care systems. Interviews were made with hospital managers in order to verify process flow, waiting times, activity durations, and resources. In addition, several floor plans of EDs have been studied in order to assure the logical flow of the process. Based on the data collected and the several verifications, a discrete event simulation model was developed using ARENA software. This simulation model was then verified by building a similar model on different software, which was AnyLogic. The results proved the accuracy of the model. Twenty additional simulation runs were performed to be used for the regression analysis. The equations resulted from the regression analysis were used for the optimization model. A genetic algorithm was used for the purpose of obtaining optimized resource allocation for different arrival rates within a constrained budget, area, and patient waiting time in the system

Transverse Reflexive Simulation: a method for anchoring human activity at the heart of the company’s performance

Cet article présente la genèse et la mise en œuvre d’une méthode qui a consisté à simuler l’activité de traitement d’une demande client dans le domaine de la relation de service. L’objectif de cette simulation était double: révéler une activité collective qui se déroule de façon distribuée dans le temps et dans l’espace et identifier des leviers de transformation pour faciliter et fluidifier la relation de service. Cette simulation, que nous avons nommée « Simulation Réflexive Transverse » convoque le travail par le biais des connaissances acquises sur l’activité humaine dans ses différentes dimensions au travers d’un programme de recherche technologique existant au sein de la R&D (Recherche et Développement) d’une grande entreprise. Elle permet ainsi de travailler sur la continuité, élément crucial de la qualité de service et de la satisfaction client, en ouvrant des espaces de construction de cette continuité. En favorisant le développement des individus, des collectifs et des organisations, la Simulation Réflexive Transverse contribue à la performance de l’entreprise sur le long terme.This article presents the genesis and implementation of a method that consisted in simulating the activity of processing a customer request in the field of the service relationship. The purpose of this simulation was twofold: to reveal a collective activity that unfolds in a distributed way in time and space and to identify the levers of transformation to facilitate the service relationship and make it more fluid. This simulation, known as "Transverse Reflexive Simulation", elicits the work thanks to the knowledge acquired on human activity in its various dimensions in an existing research programme in the R&D (Research and Development) division of a large company. It makes it possible to work on continuity, an element crucial to quality of service and customer satisfaction, by opening spaces for constructing this continuity. By promoting the development of individuals, collectives and organizations, Transverse Reflexive Simulation contributes to the company's long-term performance

Examining patients’ satisfaction in Jordanian emergency departments through business process improvement implementation

There have been recent advancements in healthcare services provision to enhance patients’ satisfaction. Previous research has concluded that Jordanian ratings of service quality and quality of care provided in public hospitals are lower compared to other nations in the region and abroad. These studies, however, failed to utilize any standardized customer satisfaction tools. At the same little empirical research has attempted to investigate the link of business process improvement in Jordanian hospitals to the enhancement of patients’ satisfaction. This research bridges the gap in the literature by first testing and validating SERVQUAL, a customer satisfaction tool, in Jordanian hospital environments while examining the effect the split-flow model, a proven business process improvement model, on increasing the positive experience of patients in public hospitals’ emergency departments in Jordan. Based on data obtained from a questionnaire comprised of the validated SERVQUAL instrument and a new survey measuring patients’ ratings of the split-flow model implementation components, the dissertation concluded that SERVQUAL is an effective tool for measuring customer (patient) satisfaction and that the business process improvements influences patients’ satisfaction. Overall, a clear, specified, and monitored process of receiving, handling, and discharging patients yield better experience. More specifically, the look, feel, and appeal of facilities is related to patients’ satisfaction in Jordan. The more modern, up-to-date, and neat looking facilities and staff are, the better experience patients reported. Further, higher degrees of responsiveness and empathy are associated with increased levels of patients’ satisfaction in Jordan. The implementation of split-flow model component decreased wait times, hastened v general team assessment, and provided clear information on patients’ conditions, discharge instructions, and future visits, which generated better ratings. This research is important in many respects. It uncovered the dearth of specific quantitative metrics on patients’ satisfaction in Jordan. Most measures of the construct are survey-based, jeopardizing the reliability and validity of inferences drawn from the analyses utilized. Further, the analysis has demonstrated that Jordanian emergency departments have business processes that need reengineering to enhance patients’ satisfaction. More experimental research is needed to test the viability of different business processes in emergency departments to yield an optimized design and process guaranteeing higher rates of satisfaction