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

Simulation to optimize the laboratory diagnosis of bacteremia

Blood cultures are central to the management of patients with sepsis and bloodstream infection. Clinical decisions depend on the timely availability of laboratory information, which, in turn, depends on the optimal laboratory processing of specimens. Discrete event simulation (DES) offers insights into where optimization efforts can be targeted. Here, we generate a detailed process map of blood culture processing within a laboratory and use it to build a simulator. Direct observation of laboratory staff processing blood cultures was used to generate a flowchart of the blood culture laboratory pathway. Retrospective routinely collected data were combined with direct observations to generate probability distributions over the time taken for each event. These data were used to inform the DES model. A sensitivity analysis explored the impact of staff availability on turnaround times. A flowchart of the blood culture pathway was constructed, spanning labeling, incubation, organism identification, and antimicrobial susceptibility testing. Thirteen processes in earlier stages of the pathway, not otherwise captured by routinely collected data, were timed using direct observations. Observations revealed that specimen processing is predominantly batched. Another eight processes were timed using retrospective data. A simulator was built using DES. Sensitivity analysis revealed that specimen progression through the simulation was especially sensitive to laboratory technician availability. Gram stain reporting time was also sensitive to laboratory scientist availability. Our laboratory simulation model has wide-ranging applications for the optimization of laboratory processes and effective implementation of the changes required for faster and more accurate results.

IMPORTANCE

Optimization of laboratory pathways and resource availability has a direct impact on the clinical management of patients with bloodstream infection. This research offers an insight into the laboratory processing of blood cultures at a system level and allows clinical microbiology laboratories to explore the impact of changes to processes and resources.

Optimization models for patient and technician scheduling in hemodialysis centers

Patient and technician scheduling problem in hemodialysis centers presents a unique setting in healthcare operations as (1) unlike other healthcare problems, dialysis appointments have a steady state and the treatment times are determined in advance of the appointments, and (2) once the appointments are set, technicians will have to be assigned to two types of jobs per appointment: putting on and taking off patients (connecting to and disconnecting from dialysis machines). In this study, we design a mixed-integer programming model to minimize technicians' operating costs (regular and overtime costs) at large-scale hemodialysis centers. As this formulation proves to be computationally challenging to solve, we propose a novel reformulation of the problem as a discrete-time assignment model and prove that the two formulations are equivalent under a specific condition. We then simulate instances based on the data from our collaborating hemodialysis center to evaluate the performance of our proposed formulations. We compare our results to the current scheduling policy at the center. In our numerical analysis, we reduced the technician operating costs by 17% on average (up to 49%) compared to the current practice. We further conduct a post-optimality analysis and develop a predictive model that can estimate the number of required technicians based on the center's attributes and patients' input variables. Our predictive model reveals that the optimal number of technicians is strongly related to the time flexibility of patients and their dialysis times. Our findings can help clinic managers at hemodialysis centers to accurately estimate the technician requirements.

Planning for resilience in screening operations using discrete event simulation modeling: example of HPV testing in Peru

Background

The World Health Organization (WHO) has called for the elimination of cervical cancer. Unfortunately, the implementation of cost-effective prevention and control strategies has faced significant barriers, such as insufficient guidance on best practices for resource and operations planning. Therefore, we demonstrate the value of discrete event simulation (DES) in implementation science research and practice, particularly to support the programmatic and operational planning for sustainable and resilient delivery of healthcare interventions. Our specific example shows how DES models can inform planning for scale-up and resilient operations of a new HPV-based screen and treat program in Iquitos, an Amazonian city of Peru.

Methods

Using data from a time and motion study and cervical cancer screening registry from Iquitos, Peru, we developed a DES model to conduct virtual experimentation with “what-if” scenarios that compare different workflow and processing strategies under resource constraints and disruptions to the screening system.

Results

Our simulations show how much the screening system’s capacity can be increased at current resource levels, how much variability in service times can be tolerated, and the extent of resilience to disruptions such as curtailed resources. The simulations also identify the resources that would be required to scale up for larger target populations or increased resilience to disruptions, illustrating the key tradeoff between resilience and efficiency. Thus, our results demonstrate how DES models can inform specific resourcing decisions but can also highlight important tradeoffs and suggest general “rules” for resource and operational planning.

Conclusions

Multilevel planning and implementation challenges are not unique to sustainable adoption of cervical cancer screening programs but represent common barriers to the successful scale-up of many preventative health interventions worldwide. DES represents a broadly applicable tool to address complex implementation challenges identified at the national, regional, and local levels across settings and health interventions—how to make effective and efficient operational and resourcing decisions to support program adaptation to local constraints and demands so that they are resilient to changing demands and more likely to be maintained with fidelity over time.

Using discrete event simulation to optimize nucleic acid testing process for coronavirus disease 2019 (COVID-19)

Background

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus-2 (SARS-CoV-2) has placed enormous diagnostic burden on hospitals and testing laboratories. It is thus critical for such facilities to optimize the diagnostic process to enable maximum testing on minimum resources. The current standard of diagnosis is the detection of the viral nucleic acid in clinical specimens.

Methods

In order to optimize the laboratory’s nucleic acid testing system for COVID-19, we performed a Discrete-Event-Simulation using the Arena Simulation Software to model the detection process based on the data obtained from the First Affiliated Hospital of Guangzhou Medical University (FAHGMU). The maximum of total time that specimens spent and the equipment consumption was compared under different scenarios in the model.

Results

Seven scenarios were performed to simulate actual situation and improved situations. We analyzed conditions that adding a new nucleic acid extraction system (NAES), shifting a member from night duty to morning duty, using specimen tubes containing guanidine isothiocyanate (GITC), then tested the maximum testing capacity in the current number of technicians. In addition, the costs including personal protective equipment (PPE) and testing kits was calculated.

Conclusions

A work schedule based on specimen-load improves efficiency without incurring additional costs, while using the specimen tubes containing GITC could reduce testing time by 30 min. In contrast, adding new NAESs or polymerase chain reaction (PCR) instruments has minimal impact on testing efficiency.

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.

Variation in referral rates to emergency departments and inpatient services from a GP out of hours service and the potential impact of alternative staffing models

Introduction

Out of hours (OOHs) primary care is a critical component of the acute care system overnight and at weekends. Referrals from OOH services to hospital will add to the burden on hospital assessment in the ED and on-call specialties.

Methods

We studied the variation in referral rates (to the ED and direct specialty admission) of individual clinicians working in the Oxfordshire, UK OOH service covering a population of 600 000 people. We calculated the referral probability for each clinician over a 13-month period of practice (1 December 2014 to 31 December 2015), stratifying by clinician factors and location and timing of assessment. We used Simul8 software to determine the range of hospital referrals potentially due to variation in clinician referral propensity.

Results

Among the 119 835 contacts with the service, 5261 (4.4%) were sent directly to the ED and 3474 (3.7%) were admitted directly to specialties. More referrals were made to ED by primary care physicians if they did not work in the local practices (5.5% vs 3.5%, p=0.011). For clinicians with >1000 consultations, percentage of patients referred varied from 1% to 21% of consultations. Simulations where propensity to refer was made less extreme showed a difference in maximum referrals of 50 patients each week.

Conclusions

There is substantial variation in clinician referral rates from OOHs primary care to the acute hospital setting. The number of patients referred could be influenced by this variation in clinician behaviour. Referral propensity should be studied including casemix adjustment to determine if interventions targeting such behaviour are effective.

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.

Integrating HIV, syphilis, malaria and anaemia point-of-care testing (POCT) for antenatal care at dispensaries in western Kenya: discrete-event simulation modelling of operational impact

BACKGROUND

Despite WHO advocating for an integrated approach to antenatal care (ANC), testing coverage for conditions other than HIV remains low and women are referred to distant laboratories for testing. Using point-of-care tests (POCTs) at peripheral dispensaries could improve access to testing and timely treatment. However, the effect of providing additional services on nurse workload and client wait times are unknown. We use discrete-event simulation (DES) modelling to understand the effect of providing four point-of-care tests for ANC on nurse utilization and wait times for women seeking maternal and child health (MCH) services.

METHODS

We collected detailed time-motion data over 20 days from one high volume dispensary in western Kenya during the 8-month implementation period (2014-2015) of the intervention. We constructed a simulation model using empirical arrival distributions, activity durations and client pathways of women seeking MCH services. We removed the intervention from the model to obtain wait times, length-of-stay and nurse utilization rates for the baseline scenario where only HIV testing was offered for ANC. Additionally, we modelled a scenario where nurse consultations were set to have minimum durations for sufficient delivery of all WHO-recommended services.

RESULTS

A total of 183 women visited the dispensary for MCH services and 14 of these women received point-of-care testing (POCT). The mean difference in total waiting time was 2 min (95%CI: < 1-4 min, p = 0.026) for MCH women when integrated POCT was given, and 9 min (95%CI: 4-14 min, p < 0.001) when integrated POCT with adequate ANC consult times was given compared to the baseline scenario. Mean length-of-stay increased by 2 min (95%CI: < 1-4 min, p = 0.015) with integrated POCT and by 16 min (95%CI: 10-21 min, p < 0.001) with integrated POCT and adequate consult times compared to the baseline scenario. The two nurses' overall daily utilization in the scenario with sufficient minimum consult durations were 72 and 75%.

CONCLUSION

The intervention had a modest overall impact on wait times and length-of-stay for women seeking MCH services while ensuring pregnant women received essential diagnostic testing. Nurse utilization rates fluctuated among days: nurses experienced spikes in workload on some days but were under-utilized on the majority of days. Overall, our model suggests there was sufficient time to deliver all WHO's required ANC activities and offer integrated testing for ANC first and re-visits with the current number of healthcare staff. Further investigations on improving healthcare worker, availability, performance and quality of care are needed. Delivering four point-of-care tests together for ANC at dispensary level would be a low burden strategy to improve ANC.

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

Background

Resource allocation in patient care relies heavily on individual judgements of healthcare professionals. Such professionals perform coordinating functions by managing the timing and execution of a multitude of care processes for multiple patients. Based on advances in simulation, new technologies that could be used for establishing realistic representations have been developed. These simulations can be used to facilitate understanding of various situations, coordination training and education in logistics, decision-making processes, and design aspects of the healthcare system. However, no study in the literature has synthesized the types of simulations models available for non-technical skills training and coordination of care.

Methods

A systematic literature review, following the PRISMA guidelines, was performed to identify simulation models that could be used for training individuals in operative logistical coordination that occurs on a daily basis. This article reviewed papers of simulation in healthcare logistics presented in the Web of Science Core Collections, ACM digital library, and JSTOR databases. We conducted a screening process to gather relevant papers as the knowledge foundation of our literature study. The screening process involved a query-based identification of papers and an assessment of relevance and quality.

Results

Two hundred ninety-four papers met the inclusion criteria. The review showed that different types of simulation models can be used for constructing scenarios for addressing different types of problems, primarily for training and education sessions. The papers identified were classified according to their utilized paradigm and focus areas. (1) Discrete-event simulation in single-category and single-unit scenarios formed the most dominant approach to developing healthcare simulations and dominated all other categories by a large margin. (2) As we approached a systems perspective (cross-departmental and cross-institutional), discrete-event simulation became less popular and is complemented by system dynamics or hybrid modeling. (3) Agent-based simulations and participatory simulations have increased in absolute terms, but the share of these modeling techniques among all simulations in this field remains low.

Conclusions

An extensive study analyzing the literature on simulation in healthcare logistics indicates a growth in the number of examples demonstrating how simulation can be used in healthcare settings. Results show that the majority of studies create situations in which non-technical skills of managers, coordinators, and decision makers can be trained. However, more system-level and complex system-based approaches are limited and use methods other than discrete-event simulation.

Comparison of patient flow and provider efficiency of two delivery strategies for HPV-based cervical cancer screening in Western Kenya: a time and motion study

Background: Improving patient flow and reducing over-crowding can improve quality, promptness of care, and patient satisfaction. Given low utilization of preventive care in low-resource countries, improved patient flows are especially important in these settings.

Objective: Compare patient flow and provider efficiency between two cervical cancer screening strategies via self-collected human papillomavirus (HPV).

Methods: We collected time and motion data for patients screened for cervical cancer in 12 communities in rural Migori County, Kenya as part of a larger cluster randomized trial. Six communities were randomized to screening in community health campaigns (CHCs) and six to screening at government clinics. We quantified patient flow: duration spent on each active stage of screening and wait times, and the number of patients arriving at CHCs and clinics each hour of the day. In addition, for four CHCs, we collected time and motion data for providers, and measured provider efficiency as a ratio of active (service delivery) time to total time spent at the clinic.

Results: Total duration of screening visits, at CHCs and clinics was 42 and 87 minutes, respectively (p < 0.001 for difference). Total active time lasted longer at CHCs, with a mean of 28 minutes per patient versus 15 minutes at clinics, largely due to differences in duration for group education (p < 0.001). Wait time for registration at clinics was 36 minutes, explaining most of the difference between settings, but sometimes incorporated other health services.

Conclusions: There is a substantial difference in patient flow at clinics compared to CHCs. Shorter duration at CHCs suggests that the model is favorable for patients in limiting time spent on screening. Future cervical cancer screening programs designed for scale-up should consider how this advantage may enhance satisfaction and uptake. For clinic-based screening programs, efforts could be made towards reducing registration wait times.

The Impact of One-Dose Package of Medicines on Patient Waiting Time in Dispensing Pharmacy: Application of a Discrete Event Simulation Model

Improvement in patient waiting time in dispensing pharmacies is an important element for patient and pharmacists. The One-Dose Package (ODP) of medicines was implemented in Japan to support medicine adherence among elderly patients; however, it also contributed to increase in patient waiting times. Given the projected increase in ODP patients in the near future owing to rapid population aging, development of improved strategies is a key imperative. We conducted a cross-sectional survey at a single dispensing pharmacy to clarify the impact of ODP on patient waiting time. Further, we propose an improvement strategy developed with use of a discrete event simulation (DES) model. A total of 673 patients received pharmacy services during the study period. A two-fold difference in mean waiting time was observed between ODP and non-ODP patients (22.6 and 11.2 min, respectively). The DES model was constructed with input parameters estimated from observed data. Introduction of fully automated ODP (A-ODP) system was projected to reduce the waiting time for ODP patient by 0.5 times (from 23.1 to 11.5 min). Furthermore, assuming that 40% of non-ODP patients would transfer to ODP, the waiting time was predicted to increase to 56.8 min; however, introduction of the A-ODP system decreased the waiting time to 20.4 min. Our findings indicate that ODP is one of the elements that increases the waiting time and that it might become longer in the future. Introduction of the A-ODP system may be an effective strategy to improve waiting time.

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.

Redesigning the diagnostic pathway for chest pain patients in emergency departments

Patients presenting with chest pain at an emergency department in the United Kingdom receive troponin tests to assess the likelihood of an acute myocardial infarction (AMI). Until recently, serial testing with two blood samples separated by at least six hours was necessary in order to analyse the change in troponin levels over time. New high-sensitivity troponin tests, however, allow the inter-test time to be shortened from six to three hours. Recent evidence also suggests that the new generation of troponin tests can be used to rule out AMI on the basis of a single test if patients at low risk of AMI present with very low cardiac troponin levels more than three hours after onset of worst pain. This paper presents a discrete event simulation model to assess the likely impact on the number of hospital admissions if emergency departments adopt strategies for serial and single testing based on the use of high-sensitivity troponin. Data sets from acute trusts in the South West of England are used to quantify the resulting benefits.

A preliminary study of a novel emergency department nursing triage simulation for research applications

Background

Studying the effect on functioning of the emergency department of disasters with a potential impact on staff members themselves usually involves table top and simulated patient exercises. Computerized virtual reality simulations have the potential to configure a variety of scenarios to determine likely staff responses and how to address them without intensive utilization of resources. To decide whether such studies are justified, we determined whether a novel computer simulation has the potential to serve as a valid and reliable model of on essential function in a busy ED.

Methods

Ten experienced female ED triage nurses (mean age 51) mastered navigating a virtual reality model of triage of 4 patients in an ED with which they were familiar, after which they were presented in a testing session with triage of 6 patients whose cases were developed using the Emergency Severity Index to represent a range of severity and complexity. Attitudes toward the simulation, and perceived workload in the simulation and on the job, were assessed with questionnaires and the NASA task load index. Z-scores were calculated for data points reflecting subject actions, the time to perform them, patient prioritization according to severity, and the importance of the tasks. Data from questionnaires and scales were analyzed with descriptive statistics and paired t tests using SPSS v. 21. Microsoft Excel was used to compute a correlation matrix for all standardized variables and all simulation data.

Results

Nurses perceived their work on the simulation task to be equivalent to their workload on the job in all aspects except for physical exertion. Although they were able to work with written communications with the patients, verbal communication would have been preferable. Consistent with the workplace, variability in performance during triage reflected subject skill and experience and was correlated with comfort with the task. Time to perform triage corresponded to the time required in the ED and virtual patients were prioritized appropriately according to severity.

Conclusions

This computerized simulation appears to be a reasonable accurate proxy for ED triage. If future studies of this kind of simulation with a broader range of subjects that includes verbal communication between virtual patients and subjects and interactions of multiple subjects, supports the initial impressions, the virtual ED could be used to study the impact of disaster scenarios on staff functioning.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-016-2337-3) contains supplementary material, which is available to authorized users.