Discrete event simulation modelling to evaluate the impact of a quality improvement initiative on patient flow in a paediatric emergency department

Does a GP service package matter in addressing the absence of health management by the occupational population? A modelling study

OBJECTIVE

To assess the influence of supply and demand factors on the contract behavior of occupational populations with general practitioner (GP) teams.

METHODS

We employed a system dynamics approach to assess and predict the effect of the general practitioner service package (GPSP) and complementary incentive policies on the contract rate for 2015-2030. First, the GPSP is designed to address the unique needs of occupational populations, enhancing the attractiveness of GP contracting services, including three personalized service contents tailored to demand-side considerations: work-related disease prevention (WDP), health education & counseling (HEC), and health-care service (HCS). Second, the complementary incentive policies on the supply-side included income incentives (II), job title promotion (JTP), and education & training (ET). Considering the team collaboration, the income distribution ratio (IDR) was also incorporated into supply-side factors.

FINDINGS

The contract rate is predicted to increase to 57.8% by 2030 after the GPSP intervention, representing a 15.4% increase on the non-intervention scenario. WDP and HEC have a slightly higher (by 2%) impact on the contract rate than that from HCS. Regarding the supply-side policies, II have a more significant impact on the contract rate than JTP and ET by 3-5%. The maximum predicted contract rate of 75.2% is expected by 2030 when the IDR is 0.5, i.e., the GP receives 50% of the contract income and other members share 50%.

CONCLUSION

The GP service package favorably increased the contract rate among occupational population, particularly after integrating the incentive policies. Specifically, for a given demand level, the targeted content of the package enhanced the attractiveness of contract services. On the supply side, the incentive policies boost GPs' motivation, and the income distribution motivated other team members.

Is in situ simulation in emergency medicine safe? A scoping review

OBJECTIVES

To provide an overview of the available evidence regarding the safety of in situ simulation (ISS) in the emergency department (ED).

DESIGN

Scoping review.

METHODS

Original articles published before March 2021 were included if they investigated the use of ISS in the field of emergency medicine.

INFORMATION SOURCES

MEDLINE, EMBASE, Cochrane and Web of Science.

RESULTS

A total of 4077 records were identified by our search strategy and 2476 abstracts were screened. One hundred and thirty full articles were reviewed and 81 full articles were included. Only 33 studies (40%) assessed safety-related issues, among which 11 chose a safety-related primary outcome. Latent safety threats (LSTs) assessment was conducted in 24 studies (30%) and the cancellation rate was described in 9 studies (11%). The possible negative impact of ISS on real ED patients was assessed in two studies (2.5%), through a questionnaire and not through patient outcomes.

CONCLUSION

Most studies use ISS for systems-based or education-based applications. Patient safety during ISS is often evaluated in the context of identifying or mitigating LSTs and rarely on the potential impact and risks to patients simultaneously receiving care in the ED. Our scoping review identified knowledge gaps related to the safe conduct of ISS in the ED, which may warrant further investigation.

Systems approach to improving traumatic brain injury care in Myanmar: a mixed-methods study from lived experience to discrete event simulation

OBJECTIVES

Traumatic brain injury (TBI) is a global health problem, whose management in low-resource settings is hampered by fragile health systems and lack of access to specialist services. Improvement is complex, given the interaction of multiple people, processes and institutions. We aimed to develop a mixed-method approach to understand the TBI pathway based on the lived experience of local people, supported by quantitative methodologies and to determine potential improvement targets.

DESIGN

We describe a systems approach based on narrative exploration, participatory diagramming, data collection and discrete event simulation (DES), conducted by an international research collaborative.

SETTING

The study is set in the tertiary neurotrauma centre in Yangon General Hospital, Myanmar, in 2019-2020 (prior to the SARS-CoV2 pandemic).

PARTICIPANTS

The qualitative work involved 40 workshop participants and 64 interviewees to explore the views of a wide range of stakeholders including staff, patients and relatives. The 1-month retrospective admission snapshot covered 85 surgical neurotrauma admissions.

RESULTS

The TBI pathway was outlined, with system boundaries defined around the management of TBI once admitted to the neurosurgical unit. Retrospective data showed 18% mortality, 71% discharge to home and an 11% referral rate. DES was used to investigate the system, showing its vulnerability to small surges in patient numbers, with critical points being CT scanning and observation ward beds. This explorative model indicated that a modest expansion of observation ward beds to 30 would remove the flow-limitations and indicated possible consequences of changes.

CONCLUSIONS

A systems approach to improving TBI care in resource-poor settings may be supported by simulation and informed by qualitative work to ground it in the direct experience of those involved. Narrative interviews, participatory diagramming and DES represent one possible suite of methods deliverable within an international partnership. Findings can support targeted improvement investments despite coexisting resource limitations while indicating concomitant risks.

Impact of Universal Suicide Risk Screening in a Pediatric Emergency Department: A Discrete Event Simulation Approach

Objectives

The aim of this study was to use discrete event simulation (DES) to model the impact of two universal suicide risk screening scenarios (emergency department [ED] and hospital-wide) on mean length of stay (LOS), wait times, and overflow of our secure patient care unit for patients being evaluated for a behavioral health complaint (BHC) in the ED of a large, academic children’s hospital.

Methods

We developed a conceptual model of BHC patient flow through the ED, incorporating anticipated system changes with both universal suicide risk screening scenarios. Retrospective site-specific patient tracking data from 2017 were used to generate model parameters and validate model output metrics with a random 50/50 split for derivation and validation data.

Results

The model predicted small increases (less than 1 hour) in LOS and wait times for our BHC patients in both universal screening scenarios. However, the days per year in which the ED experienced secure unit overflow increased (existing system: 52.9 days; 95% CI, 51.5–54.3 days; ED: 94.4 days; 95% CI, 92.6–96.2 days; and hospital-wide: 276.9 days; 95% CI, 274.8–279.0 days).

Conclusions

The DES model predicted that implementation of either universal suicide risk screening scenario would not severely impact LOS or wait times for BHC patients in our ED. However, universal screening would greatly stress our existing ED capacity to care for BHC patients in secure, dedicated patient areas by creating more overflow.

Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review

Discrete-event simulation (DES) is a stochastic modeling approach widely used to address dynamic and complex systems, such as healthcare. In this review, academic databases were systematically searched to identify 231 papers focused on DES modeling in healthcare. These studies were sorted by year, approach, healthcare setting, outcome, provenance, and software use. Among the surveys, conceptual/theoretical studies, reviews, and case studies, it was found that almost two-thirds of the theoretical articles discuss models that include DES along with other analytical techniques, such as optimization and lean/six sigma, and one-third of the applications were carried out in more than one healthcare setting, with emergency departments being the most popular. Moreover, half of the applications seek to improve time- and efficiency-related metrics, and one-third of all papers use hybrid models. Finally, the most popular DES software is Arena and Simul8. Overall, there is an increasing trend towards using DES in healthcare to address issues at an operational level, yet less than 10% of DES applications present actual implementations following the modeling stage. Thus, future research should focus on the implementation of the models to assess their impact on healthcare processes, patients, and, possibly, their clinical value. Other areas are DES studies that emphasize their methodological formulation, as well as the development of frameworks for hybrid models.

Reducing Pediatric ED Length of Stay by Reducing Diagnostic Testing: A Discrete Event Simulation Model

Supplemental Digital Content is available in the text.

Quality improvement efforts can require significant investment before the system impact of those efforts can be evaluated. We used discrete event simulation (DES) modeling to test the theoretical impact of a proposed initiative to reduce diagnostic testing for low-acuity pediatric emergency department (ED) patients.

Quantifying Dynamic Flow of Emergency Department (ED) Patient Managements: A Multistate Model Approach

Background

Emergency department (ED) crowding and prolonged lengths of stay continue to be important medical issues. It is difficult to apply traditional methods to analyze multiple streams of the ED patient management process simultaneously. The aim of this study was to develop a statistical model to delineate the dynamic patient flow within the ED and to analyze the effects of relevant factors on different patient movement rates.

Methods

This study used a retrospective cohort available with electronic medical data. Important time points and relevant covariates of all patients between January and December 2013 were collected. A new five-state Markov model was constructed by an expert panel, including three intermediate states: triage, physician management, and observation room and two final states: admission and discharge. A day was further divided into four six-hour periods to evaluate dynamics of patient movement over time.

Results

A total of 149,468 patient records were analyzed with a median total length of stay being 2.12 (interquartile range = 6.51) hours. The patient movement rates between states were estimated, and the effects of the age group and triage level on these movements were also measured. Patients with lower acuity go home more quickly (relative rate (RR): 1.891, 95% CI: 1.881–1.900) but have to wait longer for physicians (RR: 0.962, 95% CI: 0.956–0.967) and admission beds (RR: 0.673, 95% CI: 0.666–0.679). While older patients were seen more quickly by physicians (RR: 1.134, 95% CI: 1.131–1.139), they spent more time waiting for the final state (for admission RR: 0.830, 95% CI: 0.821–0.839; for discharge RR: 0.773, 95% CI: 0.769–0.776). Comparing the differences in patient movement rates over a 24-hour day revealed that patients wait longer before seen by physicians during the evening and that they usually move from the ED to admission afternoon. Predictive dynamic illustrations show that six hours after the patients' entry, the probability of still in the ED system ranges from 28% in the evening to 38% in the morning.

Conclusions

The five-state model well described the dynamic ED patient flow and analyzed the effects of relevant influential factors at different states. The model can be used in similar medical settings or incorporate different important covariates to develop individually tailored approaches for the improvement of efficiency within the health professions.