Systematic review of the use of computer simulation modeling of patient flow in surgical care

Evaluating the Impact of the Level of Robustness in Operating Room Scheduling Problems

Managing uncertainty in surgery times presents a critical challenge in operating room (OR) scheduling, as it can have a significant impact on patient care and hospital efficiency. Objectives: By incorporating robustness into the decision-making process, we can provide a more reliable and adaptive solution compared to traditional deterministic approaches. Materials and methods: In this paper, we consider a cardinality-constrained robust optimization model for OR scheduling, addressing uncertain surgery durations. By accounting for patient waiting times, urgency levels and delay penalties in the objective function, our model aims to optimise patient-centred outcomes while ensuring operational resilience. However, to achieve an appropriate balance between resilience and robustness cost, the robustness level must be carefully tuned. In this paper, we conduct a comprehensive analysis of the model's performance, assessing its sensitivity to robustness levels and its ability to handle different uncertainty scenarios. Results: Our results show significant improvements in patient outcomes, including reduced waiting times, fewer missed surgeries and improved prioritisation of urgent cases. Key contributions of this research include an evaluation of the representativeness and performance of the patient-centred objective function, a comprehensive analysis of the impact of robustness parameters on OR scheduling performance, and insights into the impact of different robustness levels. Conclusions: This research offers healthcare providers a pathway to increase operational efficiency, improve patient satisfaction, and mitigate the negative effects of uncertainty in OR scheduling.

A critical review of implementing lean and simulation to improve resource utilization and patient experience in outpatient clinics

Purpose

The purpose of this paper is to explore and critically review the existing literature on applications of Lean Methodology (LM) and Discrete-Event Simulation (DES) to improve resource utilization and patient experience in outpatient clinics. In doing, it is aimed to identify how to implement LM in outpatient clinics and discuss the advantages of integrating both lean and simulation tools towards achieving the desired outpatient clinics outcomes.

Design/methodology/approach

A theoretical background of LM and DES to define a proper implementation approach is developed. The search strategy of available literature on LM and DES used to improve outpatient clinic operations is discussed. Bibliometric analysis to identify patterns in the literature including trends, associated frameworks, DES software used, and objective and solutions implemented are presented. Next, an analysis of the identified work offering critical insights to improve the implementation of LM and DES in outpatient clinics is presented.

Findings

Critical analysis of the literature on LM and DES reveals three main obstacles hindering the successful implementation of LM and DES. To address the obstacles, a framework that integrates DES with LM has been recommended and proposed. The paper provides an example of such a framework and identifies the role of LM and DES towards improving the performance of their implementation in outpatient clinics.

Originality/value

This study provides a critical review and analysis of the existing implementation of LM and DES. The current roadblocks hindering LM and DES from achieving their expected potential has been identified. In addition, this study demonstrates how LM with DES combined to achieve the desired outpatient clinic objectives.

Patient Throughput Initiatives in Ambulatory Care Organizations during the COVID-19 Pandemic: A Systematic Review

BACKGROUND AND OBJECTIVES

Ambulatory (outpatient) health care organizations continue to respond to the COVID-19 global pandemic using an array of initiatives to provide a continuity of care for both COVID-19 and non-COVID-19 patients. The purpose of this study is to systematically identify the facilitators and barriers experienced by outpatient health care organizations in an effort to maintain effective and efficient patient throughput during the pandemic.

MATERIALS AND METHODS

This study systematically reviewed articles focused on initiatives taken by ambulatory care organizations to maintain optimal outpatient throughput levels while balancing pandemic precautions, published during 2020.

RESULTS

Among the 30 articles that met the inclusion criteria, three initiatives healthcare organizations have taken to maintain throughput were identified: the use (and enhanced use) of telehealth, protocol development, and health care provider training. The research team also identified three barriers to patient throughput: lack of telehealth, lack of resources, and overall lack of knowledge.

CONCLUSIONS

To maintain patient throughput during the COVID-19 pandemic, healthcare organizations need to develop strategies such as the use of virtual consultation and follow-up, new guidelines to move patients along the care delivery value-chain, and ongoing training of providers. Additionally, the availability of required technology for telehealth, availability of resources, and adequate knowledge are vital for continuous patient throughput to ensure continuity of care during a pandemic.

Surgical workflow simulation for the design and assessment of operating room setups in orthopedic surgery

BACKGROUND

The design and internal layout of modern operating rooms (OR) are influencing the surgical team's collaboration and communication, ergonomics, as well as intraoperative hygiene substantially. Yet, there is no objective method for the assessment and design of operating room setups for different surgical disciplines and intervention types available. The aim of this work is to establish an improved OR setup for common procedures in arthroplasty.

METHODS

With the help of computer simulation, a method for the design and assessment of enhanced OR setups was developed. New OR setups were designed, analyzed in a computer simulation environment and evaluated in the actual intraoperative setting. Thereby, a 3D graphical simulation representation enabled the strong involvement of clinical stakeholders in all phases of the design and decision-making process of the new setup alternatives.

RESULTS

The implementation of improved OR setups reduces the instrument handover time between the surgeon and the scrub nurse, the travel paths of the OR team as well as shortens the procedure duration. Additionally, the ergonomics of the OR staff were improved.

CONCLUSION

The developed simulation method was evaluated in the actual intraoperative setting and proved its benefit for the design and optimization of OR setups for different surgical intervention types. As a clinical result, enhanced setups for total knee arthroplasty and total hip arthroplasty surgeries were established in daily clinical routine and the OR efficiency was improved.

The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review

This study systematically examines the diffusion of the discrete event simulation (DES) approach in health services and health care management by examining relevant factors such as research areas, channels with the objective of promoting the application of DES in the health field. We examined 483 journal papers referencing this approach that were published in 230 journals during 1981 to 2014. The application of DES has extended from health service operational research evaluation to the assessment of interventions in diverse health arenas. The increase in the number of adopters (paper authors) of DES and the increase in number of related channels (journals publishing DES-related articles) are highly correlated, which suggests an increase of DES-related publications in health research. The same conclusion is reached, that is, an increased diffusion of DES in health research, when we focus on the temporal trends of the channels and adopters. The applications of DES in health research cover 22 major areas based on our categorization. The expansion in the health areas also suggests to a certain extent the rapid diffusion of DES in health research.

Decision makers' experience of participatory dynamic simulation modelling: methods for public health policy

BACKGROUND

Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviours. Advances in technology have led to increased accessibility and interest in systems methods to address complex health policy issues. However, the involvement of policy decision makers in health-related simulation model development has been lacking. Where end-users have been included, there has been limited examination of their experience of the participatory modelling process and their views about the utility of the findings. This paper reports the experience of end-user decision makers, including senior public health policy makers and health service providers, who participated in three participatory simulation modelling for health policy case studies (alcohol related harm, childhood obesity prevention, diabetes in pregnancy), and their perceptions of the value and efficacy of this method in an applied health sector context.

METHODS

Semi-structured interviews were conducted with end-user participants from three participatory simulation modelling case studies in Australian real-world policy settings. Interviewees were employees of government agencies with jurisdiction over policy and program decisions and were purposively selected to include perspectives at different stages of model development.

RESULTS

The 'co-production' aspect of the participatory approach was highly valued. It was reported as an essential component of building understanding of the modelling process, and thus trust in the model and its outputs as a decision-support tool. The unique benefits of simulation modelling included its capacity to explore interactions of risk factors and combined interventions, and the impact of scaling up interventions. Participants also valued simulating new interventions prior to implementation in the real world, and the comprehensive mapping of evidence and its gaps to prioritise future research. The participatory aspect of simulation modelling was time and resource intensive and therefore most suited to high priority complex topics with contested options for intervening.

CONCLUSION

These findings highlight the value of a participatory approach to dynamic simulation modelling to support its utility in applied health policy settings.

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.

Informing Hospital Change Processes through Visualization and Simulation: A Case Study at a Children's Emergency Clinic

OBJECTIVE

To demonstrate the use of visualization and simulation tools in order to involve stakeholders and inform the process in hospital change processes, illustrated by an empirical study from a children's emergency clinic.

BACKGROUND

Reorganization and redevelopment of a hospital is a complex activity that involves many stakeholders and demands. Visualization and simulation tools have proven useful for involving practitioners and eliciting relevant knowledge. More knowledge is desired about how these tools can be implemented in practice for hospital planning processes.

METHODS

A participatory planning process including practitioners and researchers was executed over a 3-year period to evaluate a combination of visualization and simulation tools to involve stakeholders in the planning process and to elicit knowledge about needs and requirements.

RESULTS

The initial clinic proposal from the architect was discarded as a result of the empirical study. Much general knowledge about the needs of the organization was extracted by means of the adopted tools. Some of the tools proved to be more accessible than others for the practitioners participating in the study. The combination of tools added value to the process by presenting information in alternative ways and eliciting questions from different angles.

CONCLUSIONS

Visualization and simulation tools inform a planning process (or other types of change processes) by providing the means to see beyond present demands and current work structures. Long-term involvement in combination with accessible tools is central for creating a participatory setting where the practitioners' knowledge guides the process.

A Generic Simulation Model of the Relative Cost-Effectiveness of ICU Versus Step-Down (IMCU) Expansion

BACKGROUND

Many jurisdictions are facing increased demand for intensive care. There are two long-term investment options: intensive care unit (ICU) versus step-down or intermediate care unit (IMCU) capacity expansion. Relative cost-effectiveness of the two investment strategies with regard to patient lives saved has not been studied to date.

METHODS

We expand a generic system dynamics simulation model of emergency patient flow in a typical hospital, populated with empirical evidence found in the medical and hospital administration literature, to estimate the long-term effects of expanding ICU versus IMCU beds on patient lives saved under a common assumption of 2.1% annual increase in hospital arrivals. Two alternative policies of expanding ICU by two beds versus introducing a two-bed IMCU are compared over a ten-year simulation period. Russel equation is used to calculate total cost of patients' hospitalization. Using two possible values for the ratio of ICU to IMCU cost per inpatient day and four possible values for the percentage of patients transferred from ICU to IMCU found in the literature, nine scenarios are compared against the baseline scenario of no capacity expansion.

RESULTS

Expanding ICU capacity by two beds is demonstrated as the most cost-effective scenario with an incremental cost-effectiveness ratio of 3684 (US $) per life saved against the baseline scenario. Sensitivity analyses on the mortality rate of patients in IMCU, direct transfer of IMCU-destined patients to the ward upon completing required IMCU length of stay in the ICU, admission of IMCU patient to ICU, adding two ward beds, and changes in hospital size do not change the superiority of ICU expansion over other scenarios.

CONCLUSIONS

In terms of operational costs, ICU beds are more cost effective for saving patients than IMCU beds. However, capital costs of setting up ICU versus IMCU beds should be considered for a complete economic analysis.

Using Discrete-Event Simulation to Promote Quality Improvement and Efficiency in a Radiation Oncology Treatment Center

BACKGROUND

To meet demand for radiation oncology services and ensure patient-centered safe care, management in an academic radiation oncology department initiated quality improvement efforts using discrete-event simulation (DES). Although the long-term goal was testing and deploying solutions, the primary aim at the outset was characterizing and validating a computer simulation model of existing operations to identify targets for improvement.

METHODS

The adoption and validation of a DES model of processes and procedures affecting patient flow and satisfaction, employee experience, and efficiency were undertaken in 2012-2013. Multiple sources were tapped for data, including direct observation, equipment logs, timekeeping, and electronic health records.

RESULTS

During their treatment visits, patients averaged 50.4 minutes in the treatment center, of which 38% was spent in the treatment room. Patients with appointments between 10 AM and 2 PM experienced the longest delays before entering the treatment room, and those in the clinic in the day's first and last hours, the shortest (<5 minutes). Despite staffed for 14.5 hours daily, the clinic registered only 20% of patients after 2:30 PM. Utilization of equipment averaged 58%, and utilization of staff, 56%.

CONCLUSION

The DES modeling quantified operations, identifying evidence-based targets for next-phase remediation and providing data to justify initiatives.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling

BACKGROUND

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools.

OBJECTIVE

This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings.

CONCLUSION

Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Simulation Modelling in Healthcare: An Umbrella Review of Systematic Literature Reviews

BACKGROUND

Numerous studies examine simulation modelling in healthcare. These studies present a bewildering array of simulation techniques and applications, making it challenging to characterise the literature.

OBJECTIVE

The aim of this paper is to provide an overview of the level of activity of simulation modelling in healthcare and the key themes.

METHODS

We performed an umbrella review of systematic literature reviews of simulation modelling in healthcare. Searches were conducted of academic databases (JSTOR, Scopus, PubMed, IEEE, SAGE, ACM, Wiley Online Library, ScienceDirect) and grey literature sources, enhanced by citation searches. The articles were included if they performed a systematic review of simulation modelling techniques in healthcare. After quality assessment of all included articles, data were extracted on numbers of studies included in each review, types of applications, techniques used for simulation modelling, data sources and simulation software.

RESULTS

The search strategy yielded a total of 117 potential articles. Following sifting, 37 heterogeneous reviews were included. Most reviews achieved moderate quality rating on a modified AMSTAR (A Measurement Tool used to Assess systematic Reviews) checklist. All the review articles described the types of applications used for simulation modelling; 15 reviews described techniques used for simulation modelling; three reviews described data sources used for simulation modelling; and six reviews described software used for simulation modelling. The remaining reviews either did not report or did not provide enough detail for the data to be extracted.

CONCLUSION

Simulation modelling techniques have been used for a wide range of applications in healthcare, with a variety of software tools and data sources. The number of reviews published in recent years suggest an increased interest in simulation modelling in healthcare.

Operational strategies to manage non-elective orthopaedic surgical flows: a simulation modelling study

OBJECTIVES

To explore the value of simulation modelling in evaluating the effects of strategies to plan and schedule operating room (OR) resources aimed at reducing time to surgery for non-elective orthopaedic inpatients at a Swedish hospital.

METHODS

We applied discrete-event simulation modelling. The model was populated with real world data from a university hospital with a strong focus on reducing waiting time to surgery for patients with hip fracture. The system modelled concerned two patient groups that share the same OR resources: hip-fracture and other non-elective orthopaedic patients in need of surgical treatment. We simulated three scenarios based on the literature and interaction with staff and managers: (1) baseline; (2) reduced turnover time between surgeries by 20 min and (3) one extra OR during the day, Monday to Friday. The outcome variables were waiting time to surgery and the percentage of patients who waited longer than 24 hours for surgery.

RESULTS

The mean waiting time in hours was significantly reduced from 16.2 hours in scenario 1 (baseline) to 13.3 hours in scenario 2 and 13.6 hours in scenario 3 for hip-fracture surgery and from 26.0 hours in baseline to 18.9 hours in scenario 2 and 18.5 hours in scenario 3 for other non-elective patients. The percentage of patients who were treated within 24 hours significantly increased from 86.4% (baseline) to 96.1% (scenario 2) and 95.1% (scenario 3) for hip-fracture patients and from 60.2% (baseline) to 79.8% (scenario 2) and 79.8% (scenario 3) for patients with other non-elective patients.

CONCLUSIONS

Healthcare managers who strive to improve the timelines of non-elective orthopaedic surgeries may benefit from using simulation modelling to analyse different strategies to support their decisions. In this specific case, the simulation results showed that the reduction of surgery turnover times could yield the same results as an extra OR.

A Literature Review on Validated Simulations of the Surgical Services

The surgical department is a critical unit that oversees multiple surgical-based clinical pathways and works with various other units in a hospital. This department faces numerous challenges relating to variability in demand and management of resources. The aim of this article is to review the application of validated simulation models on hospital-wide surgical services. Each of these models is broadly classified by (i) simulation method and (ii) level of detail given to the management of "patient pathways" and "staff workflows". We remark that very few studies have given attention to the management of staff workflows in their validated simulation models.

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol

BACKGROUND

Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making.

METHODS/DESIGN

The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants' engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change.

DISCUSSION

The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

StratBAM: A Discrete-Event Simulation Model to Support Strategic Hospital Bed Capacity Decisions

The ability to accurately measure and assess current and potential health care system capacities is an issue of local and national significance. Recent joint statements by the Institute of Medicine and the Agency for Healthcare Research and Quality have emphasized the need to apply industrial and systems engineering principles to improving health care quality and patient safety outcomes. To address this need, a decision support tool was developed for planning and budgeting of current and future bed capacity, and evaluating potential process improvement efforts. The Strategic Bed Analysis Model (StratBAM) is a discrete-event simulation model created after a thorough analysis of patient flow and data from Geisinger Health System's (GHS) electronic health records. Key inputs include: timing, quantity and category of patient arrivals and discharges; unit-level length of care; patient paths; and projected patient volume and length of stay. Key outputs include: admission wait time by arrival source and receiving unit, and occupancy rates. Electronic health records were used to estimate parameters for probability distributions and to build empirical distributions for unit-level length of care and for patient paths. Validation of the simulation model against GHS operational data confirmed its ability to model real-world data consistently and accurately. StratBAM was successfully used to evaluate the system impact of forecasted patient volumes and length of stay in terms of patient wait times, occupancy rates, and cost. The model is generalizable and can be appropriately scaled for larger and smaller health care settings.

Research on nursing unit layouts: an integrative review

Purpose

– This paper aims to present an integrative review of the research studies on nursing unit layouts.

Design/methodology/approach

– Studies selected for review were published between 1956 and 2014. For the purpose of this review, a framework for integrative review was developed using research orientations. The three primary dimensions – technical, psychological and social – of the designed environment and various combinations of these dimensions were used to define the research orientations of these studies.

Findings

– Of all the publications reviewed for the paper, 21 presented technical orientations, 16 psychological orientations, 3 social orientations, 20 psychotechnical orientations, 10 sociotechnical orientations, 2 psychosocial orientations and 13 presented psychosociotechnical orientations. With only a few exceptions, several issues related to nursing unit layouts were investigated no more than one time in any one category of research orientations. Several other seemingly important issues including patient and family behavior and perception, health outcomes and social and psychosocial factors in relation to unit layouts have not been studied adequately.

Research limitations/implications

– Future studies on nursing unit layouts will need to focus on patient and family behavior and perception, health outcomes and social and psychosocial factors in different units. They will also need to focus on developing theories concerning the effects of layouts on the technical, psychological and social dimensions of nursing units.

Originality/value

– Despite a long history of research on nursing unit layouts, an integrative review of these studies is still missing in the literature. This review fills in the gap using a novel framework for integrative review developed based on research orientations.

Systems modelling and simulation in health service design, delivery and decision making

The ever increasing pressures to ensure the most efficient and effective use of limited health service resources will, over time, encourage policy makers to turn to system modelling solutions. Such techniques have been available for decades, but despite ample research which demonstrates potential, their application in health services to date is limited. This article surveys the breadth of approaches available to support delivery and design across many areas and levels of healthcare planning. A case study in emergency stroke care is presented as an exemplar of an impactful application of health system modelling. This is followed by a discussion of the key issues surrounding the application of these methods in health, what barriers need to be overcome to ensure more effective implementation, as well as likely developments in the future.

Improving patient waiting times: a simulation study of an obesity care service

Background

Obesity care services are often faced with the need to adapt their resources to rising levels of demand. The main focus of this study was to help prioritise planned investments in new capacity allowing the service to improve patient experience and meet future anticipated demand.

Methods

We developed computer models of patient flows in an obesity service in an Academic Health Science Centre that provides lifestyle, pharmacotherapy and surgery treatment options for the UK's National Health Service. Using these models we experiment with different scenarios to investigate the likely impact of alternative resource configurations on patient waiting times.

Results

Simulation results show that the timing and combination of adding extra resources (eg, surgeons and physicians) to the service are important. For example, increasing the capacity of the pharmacotherapy clinics equivalent to adding one physician reduced the relevant waiting list size and waiting times, but it then led to increased waiting times for surgical patients. Better service levels were achieved when the service operates with the resource capacity of two physicians and three surgeons. The results obtained from this study had an impact on the planning and organisation of the obesity service.

Conclusions

Resource configuration combined with demand management (reduction in referral rates) along the care service can help improve patient waiting time targets for obesity services, such as the 18 week target of UK's National Health Service. The use of simulation models can help stakeholders understand the interconnectedness of the multiple microsystems (eg, clinics) comprising a complex clinical service for the same patient population, therefore, making stakeholders aware of the likely impact of resourcing decisions on the different microsystems.

A generic simulation model to assess the performance of sterilization services in health establishments

The work presented here is with a view to improving performance of sterilization services in hospitals. We carried out a survey in a large number of health establishments in the Rhône-Alpes region in France. Based on the results of this survey and a detailed study of a specific service, we have built a generic model. The generic nature of the model relies on a common structure with a high level of detail. This model can be used to improve the performance of a specific sterilization service and/or to dimension its resources. It can also serve for quantitative comparison of performance indicators of various sterilization services.

On the designing of a tamper resistant prescription RFID access control system

Recently, Chen et al. have proposed a novel tamper resistant prescription RFID access control system, published in the Journal of Medical Systems. In this paper we consider the security of the proposed protocol and identify some existing weaknesses. The main attack is a reader impersonation attack which allows an active adversary to impersonate a legitimate doctor, e.g. the patient's doctor, to access the patient's tag and change the patient prescription. The presented attack is quite efficient. To impersonate a doctor, the adversary should eavesdrop one session between the doctor and the patient's tag and then she can impersonate the doctor with the success probability of '1'. In addition, we present efficient reader-tag to back-end database impersonation, de-synchronization and traceability attacks against the protocol. Finally, we propose an improved version of protocol which is more efficient compared to the original protocol while provides the desired security against the presented attacks.

Achieving efficiency in crowded emergency departments: a research agenda

In 2011, Academic Emergency Medicine convened a consensus conference entitled "Interventions to Assure Quality in the Crowded Emergency Department." This article, a product of the breakout session on "interventions to safeguard efficiency of care," explores various elements of the research agenda on efficiency and quality in crowded emergency departments (EDs). The authors discuss four areas identified as critical to achieving progress in the research agenda for improving ED efficiency: 1) What measures can be used to understand and improve the efficiency and quality of interventions in the ED? 2) Which factors outside of the ED's control affect ED efficiency? 3) How do workforce factors affect ED efficiency? 4) How do ED design, patient flow structures, and use of technology affect efficiency? Filling these knowledge gaps is vital to identifying interventions that improve the delivery of emergency care in all EDs.