Article

Advanced Solutions for Healthcare Facility Management

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

This paper presents a simulation study carried out within a private healthcare facility with the aim of understanding whether or not it is able to handle a greater flow of incoming patients as well as the related impact on the overall efficiency. As a result, the simulation outcomes have pointed out the need for an internal work re-organization that has been devised through Lean Management tools and methodologies. The simulation model has, then, been used to predict the intended changes effects as well as their feasibility. Particular attention has been paid on the care administration process, provided that research activities are still ongoing to investigate other processes in the patient value chain where there is still substantial room for improvement. The proposed research work is grounded on an in dept analysis of the main processes and activities taking place in the healthcare facility as a starting point for the simulation model development. Afterwards, simulation has been used for “as-is” analyses and, in combination with Lean Management approaches, for “what-if” studies whose results and findings are discussed.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

ResearchGate has not been able to resolve any citations for this publication.
Conference Paper
Full-text available
Conference code: 104450, Cited By :5, Export Date: 20 August 2016, References: Andreatta, P.B., Maslowski, E., Petty, S., Shim, W., Marsh, M., Hall, T., Stern, S., Frankel, J., Virtual reality triage training provides a viable solution for disaster-preparedness (2010) Acad Emerg Med., 17 (8), pp. 870-876. , 2010 Aug Michigan Medical School, Ann Arbor, MI, USA;
Article
Full-text available
The orthopedic outpatient department (OPD) ward in a large Thai public hospital is modeled using Discrete-Event Stochastic (DES) simulation. Key Performance Indicators (KPIs) are used to measure effects across various clinical operations during different shifts throughout the day. By considering various KPIs such as wait times to see doctors, percentage of patients who can see a doctor within a target time frame, and the time that the last patient completes their doctor consultation, bottlenecks are identified and resource-critical clinics can be prioritized. The simulation model quantifies the chronic, high patient congestion that is prevalent amongst Thai public hospitals with very high patient-to-doctor ratios. Our model can be applied across five different OPD wards by modifying the model parameters. Throughout this work, we show how DES models can be used as decision-support tools for hospital management.
Chapter
Full-text available
Over the past forty years, health care organizations have faced ever-increasing pressures to deliver quality care while facing rising costs, lower reimbursements, and new regulatory demands. Discrete-event simulation has become a popular and effective decision-making tool for the optimal allocation of scarce health care resources to improve patient flow, while minimizing health care delivery costs and increasing patient satisfaction. The proliferation of increasingly sophisticated discrete-event simulation software packages has resulted in a large number of new application opportunities, including more complex implementations. In addition, combined optimization and simulation tools allow decision-makers to quickly determine optimal system configurations, even for complex integrated facilities. This chapter provides an overview of discrete-event simulation modeling applications to health care clinics and integrated health care systems (e.g. hospitals, outpatient clinics, emergency departments, and pharmacies) over the past forty years.
Article
Full-text available
This paper examines the design and development of a discrete-event (visual) simulation model of a physician clinic environment within a physician network. Biological & Popular Culture, Inc, (Biopop) sought to partner with healthcare professionals to provide high-quality, cost-effective medical care within a physician network setting. Towards this end, a discrete-event (visual) simulation model that captures both the operations of a family practice healthcare clinic and a centralized information center is presented. The research presented in this article focuses on the family practice healthcare clinic. This simulation model is built in an object-oriented, visual manner utilizing the visual simulation environment (VSE). Application of the object-oriented paradigm (OOP) allows simulation objects in the model to be easily reused. The simulation model provides a tool for risk-free evaluation of operating policies in the clinical environment. Results of a fractional factorial design to determine those input factors which significantly affect overall clinic effectiveness are reported.
Article
Full-text available
Discrete Event Simulation (DES) has been widely used in modelling health-care systems for many years and a simple citation analysis shows that the number of papers published has increased markedly since 2004. Over the last 30 years several significant reviews of DES papers have been published and we build on these to focus on the most recent era, with an interest in performance modelling within hospitals. As there are few papers that propose or illustrate general approaches, we classify papers according to the areas of application evident in the literature, discussing the apparent lack of genericity. There is considerable diversity in the objectives of reported studies and in the consequent level of detail: We discuss why specificity dominates and why more generic approaches are rare.
Article
Full-text available
In recent decades, health care costs have dramatically increased, while health care organisations have been under severe pressure to provide improved quality health care for their patients. Several health care administrators have used discrete-event simulation as an effective tool for allocating scarce resources to improve patient flow, while minimising health care delivery costs and increasing patient satisfaction. The rapid growth in simulation software technology has created numerous new application opportunities, including more sophisticated implementations, as well as combining optimisation and simulation for complex integrated facilities. This paper surveys the application of discrete-event simulation modeling to health care clinics and systems of clinics (for example, hospitals, outpatient clinics, emergency departments, and pharmacies). Future directions of research and applications are also discussed.
Article
This article describes a multi-dimensional approach to the classification of the research literature on simulation and modelling in health care. The aim of the study was to analyse the relative frequency of use of a range of operational research modelling approaches in health care, along with the specific domains of application and the level of implementation. Given the vast scale of the health care modelling literature, a novel review methodology was adopted, similar in concept to the approach of stratified sampling. The results provide new insights into the level of activity across many areas of application, highlighting important relationships and pointing to key areas of omission and neglect in the literature. In addition, the approach presented in this article provides a systematic and generic methodology that can be extended to other application domains as well as other types of information source in health-care modelling.
Conference Paper
Conference code: 104451, Cited By :2, Export Date: 20 August 2016, References: Brailsford, S.C., Harper, P.R., Patel, B., Pitt, M., An analysis of the academic literature on simulation and modelling in health care (2009) Journal of Simulation, 3, pp. 130-140;
Article
The paper focuses on a large scale problem related to population health care with special attention to obesity. The authors present a proposal for modeling human behavior and its influence on the evolution of obesity epidemics, and its effects on social networks, infrastructures and facilities. This approach is based on Intelligent Agents tools developed for reproducing country reconstruction and human factors. These models represents the base that allows to add specific and complex aspects related to pathologies and correlated behaviors that allows to reproduce these phenomena.
Article
Natural disaster events impact both the short- and long-term health of a region's population. Due to variation in the vulnerability among population segments, a severe storm event can be expected over time to have a greater public health impact upon traditionally underserved and medically fragile populations. This research illustrates the causal relationships leading to a change over time in the prevalence of chronic conditions among black and non-black populations within U.S. Hampton Roads. Using a system dynamics approach, the authors develop and integrate a macro model that captures change in regional economic and demographic profiles with a micro model that focuses on access to health services and the ability to respond within the context of the changing regional environment. The authors' study finds that: (1) the disparity in the prevalence of chronic conditions increases over time following the event, (2) the growth in health disparity may be slowed by regional resiliency intervention policies, and (3) mitigation efforts result in greater reductions in growth of chronic conditions among the black population relative the non-black general population. Knowledge of the disparate impact that such an event will have on the long-term health of underserved and medically fragile populations may be used to inform mitigation investments.
Conference Paper
A critical question related to climate change concerns to how rising sea level will affect underserved populations and medically fragile population in coastal zones and floodplains. As sea levels rise, coastal waters will regain near-tidal areas and co-mingle with human-made pollutants, resulting from decades of industrial and commercial activity. This poses potential threat and risks to public health and the environment. It is critical that decision makers will initiate a process of parsing resources to the mitigation and management of these issues. The purpose of this research is to model the inherent dynamics of this process and understand how near-term policy decisions will condition the dynamics of population health within traditionally underserved and medically fragile populations. We use a System Dynamics (SD) approach to model and simulate the sensitivity of affected populations to a range of remediation policy options intended to address these contaminated environments. Our research will assist policy makers to explore and prioritize policies with a specific focus on vulnerability, guarantee that remediation funds will be utilized effectively and equitably, and increase effectiveness of mitigation and management effort.
Article
In this paper, a simulation model of an emergency department (ED) at a large community hospital, Central Baptist Hospital in Lexington, KY, is developed. Using such a model, we can accurately emulate the patient flow in the ED and carry out sensitivity analysis to determine the most critical process for improvement in quality of care (in terms of patient length of stay). In addition, a what-if analysis is performed to investigate the potential change in operation policies and its impact. Floating nurse, combining registration with triage, mandatory requirement of physician's visit within 30 min, and simultaneous reduction of operation times of some most sensitive procedures can all result in substantial improvement. These recommendations have been submitted to the hospital leadership, and implementations are in progress.
Article
Several hundred computer simulation models have been developed in the last 15 years to solve problems in the nation's health care delivery system. These models are categorized and reviewed according to 21 areas of application, along with discussion of general model characteristics. Charts showing trends in health care simulation modeling are given, followed by discussion of problems in model implementation and directions for future research.
Conference Paper
In this article, we describe the use of tumour marker estimation models in the prediction of tumour diagnoses. In previous works, we have identified classification models for tumour markers that can be used for estimating tumour marker values on the basis of standard blood parameters. These virtual tumour markers are now used in combination with standard blood parameters for learning classifiers that are used for predicting tumour diagnoses. Several data-based modelling approaches implemented in HeuristicLab have been applied for identifying estimators for selected tumour markers and cancer diagnoses: linear regression, k-nearest neighbour (k-NN) learning, artificial neural networks (ANNs) and support vector machines (SVMs) (all optimised using evolutionary algorithms), as well as genetic programming (GP). We have applied these modelling approaches for identifying models for breast cancer diagnoses; in the results section, we summarise classification accuracies for breast cancer and we compare classification results achieved by models that use measured marker values as well as models that use virtual tumour markers.
Article
Health care has undergone a number of radical changes during the past five years. These include increased competition, fixed-rate reimbursement systems, declining hospital occupancy rates, and growth in health maintenance organizations and preferred provider organizations. Given these changes in the manner in which health care is provided, contracted, and paid for, it is appropriate to review the past research on capacity management and to determine its relevance to the changing industry. This paper provides a review, classification, and analysis of the literature on this topic. In addition, future research needs are discussed and specific problem areas not dealt with in the previous literature are targeted.
Article
Purpose: This paper analyses the problem of allocating beds among hospital wards in order to minimise crowding. Method: We present a generic discrete event simulation model of patient flow through the wards of a hospital. In the generic model, each ward can have separate probability distributions for arrival times and length of stay, which may be time dependent. Output of the model is a matrix, with statistics on the utilisation of different hypothetical numbers of beds for each ward. This matrix is fed into an allocation algorithm, which distributes the available beds among the wards in an optimal way. We define bed utilisation either in terms of how often it is in use (prevalence), or in terms of how often a newly arriving patient is placed in it (incidence). For these classes of utilisation measures we develop efficient allocation algorithms, which we prove to be optimal. Application: The model was applied to Akershus University Hospital in Norway. In 2011, some of the wards of this hospital experienced a high occupancy rate, while others had a lower utilisation. Our model was applied in order to reallocate the hospital beds among the wards. For each ward, acute arrivals were modelled with Poisson-distributions with time-varying intensity, while elective arrivals were programmed to arrive in specific numbers at specific times. The arrival rates were based on empirical data for 2010, scaled up by an expected increase of 40% due to a restructuring of the hospital districts in Oslo and the greater metropolitan area in 2011. Length of stay was modelled as beta-distributions, using a combination of subject matter experts' evaluations and empirical data from 2010. The model has been verified and validated. Results: Intuitively, both prevalence (average number of crowding beds in use) and incidence (number of patients placed in crowding beds) might seem like relevant optimisation criteria. However, our experiments show that prevalence optimisation gives more sensible solutions than incidence optimisation, as the latter tends to sacrifice entire wards where length of stay is long and patient turnover is slow. Prevalence optimisation was therefore used. The main results show that when the bed distribution is optimised, the share of crowding patient nights is reduced from 6.5% to 4.2%. Conclusion: This model provides a powerful tool for optimising hospital bed utilisation, and the application showed an important reduction in crowding bed usage. The generic model is flexible, as the level of detail in the modelling of arrivals and length of stay can vary according to the data available and accuracy required.
Article
1055 W. Joppa Road, 203, Towson, Maryland 21204, cflagle@jhsph.edu INTRODUCTION Closer to home, and also in 1952, Dr. Ellis Johnson, Several apparently independent events around the year director of the Operations Research Office of the Johns 1952 formed the nucleus of what is now almost half a Hopkins University (ORO)-actually the program and staff century of operations research in the health services as of the U.S. Army Operations Research Office, administered I have known it. In England, Norman Bailey published by the University under contract-authorized the creation \"Operational Research in Medicine\" in the June 1952 issue of an informal seminar in operations research, conducted of Operational Research Quarterly (Bailey 1952), and on the University campus and organized by an ORO histo- almost simultaneously in the Lancet, a paper on appoint- rian, Joseph McCloskey, who edited the collected seminar ment systems in outpatient departments (Welch and Bailey papers into two volumes entitled Operations Research for 1952). His work was part of an operational research effort Management (McCloskey and Trefethen 1954, McCloskey supported by the Nuffield Provincial Hospitals Trust that and Coppinger 1956). The seminar had a dual purpose, first was influential in the development of Britain\'s National the enlightening of the faculty and students about opera- Health Service. In that same year publication of the Jour- tions research, which was not a well-known topic in civil- nal of the Operations Research Society was launched, and ian life at that time, and second, searching for an academic would soon provide an outlet for communication of similar home for OR in the departmental structure and curricu- work in America. lum of the University. I recall that a place in engineering In the United States the Hill-Burton legislation of 1945 was not the first choice of an academic home for much of to fund innovation, construction, and renovation of hospi- the ORO staff, with its mix of educational backgrounds- tals created an extramural research and development pro- something in the humanities would have been preferable- gram aimed at the provision of technical assistance and but it was fortunate that the Dean of Engineering, Robert guidelines for design, construction, and management of H. Roy, an articulate and experienced manager, a student hospitals and health facilities. This created the opportunity of organizational behavior and author of several books on for operations research to participate in a multidisciplinary administration, saw in the substance of operations research effort that became the nucleus for the soon-to-emerge a complementary element in his already multidisciplinary field of health services research. The development in both Department of Industrial Engineering. The relationship intragovernmental and extramural research was led by the between ORO and the School of Engineering was formal- Assistant Surgeon General for Hospital and Medical Facil- ized, and in time the name of the department would become ities, Dr. J. R. Haldeman. His vision extended beyond the Operations Research and Industrial Engineering. design and management of the physical infrastructure of In the Johns Hopkins Medical Institutions in 1952, facilities to the determination of community needs and Russell A. Nelson, M.D., a skilled clinician and adminis- resources and the integration of services, concerns that trator, was appointed Director of the Johns Hopkins Hos- would in time dominate the directions of health services pital while maintaining for a while his position as adjunct and research centered on them. lecturer in the Department of Public Health Administration These events are indicative of the post World War II in the School of Hygiene and Public Health, where he had changes in the role of government in the health services: in been developing an educational program in hospital admin- Britain the commitment to universal coverage of care, and istration. In a few years he would become president of the in America a responsibility for funding of needed medical American Hospital Association and would chair the Advi- care facilities in the aftermath of the war and the years of sory Committee on Hospital Facilities and Services of the economic depression that preceded it. In both countries the U.S. Public Health Service. need for support of research and education was recognized At the time all this was taking place, I was a gradu- and implemented, opening the door to forms of inquiry not ate student in Dean Roy\'s department, and was one of his widely accessible to the health services in the past. advisees. I was in the throes of doctoral research and some Subject classification: Professional: comments on. Area of review: Anniversary Issue (Special). Operations Research © 2002 INFORMS 0030-364X/02/5001-0052 $05.00 Vol. 50, No. 1, January-February 2002, pp. -60 52 1526-5463 electronic ISSN
Article
This paper provides a review of the use of simulation for resource planning in the health sector. Case examples of simulation in health are provided, and the modelling problems are explored. The successes and failures of simulation modelling in this context are examined, and an approach for improving the processes, and outcomes, by the use of soft systems methodology, is suggested.
eBusiness in healthcare; from eprocurement to supply chain management
  • V Gehmlich
Gehmlich, V. (2008). ‗Opportunities of supply chain management in healthcare', In Hübner, U. and Elmhorst, M. (eds.), eBusiness in healthcare; from eprocurement to supply chain management, Springer-Verlag London Limited.
Lean management approaches applied to healthcare systems
  • F Longo
  • A Calogero
  • L Nicoletti
  • M Massei
  • F De Felice
  • A Petrillo
Longo F, Calogero A, Nicoletti L, Massei M, De Felice F, Petrillo A (2014). Lean management approaches applied to healthcare systems. In: Proceedings of the International Workshop on Innovative Simulation for Healthcare. p. 60-69, ISBN: 978-88-97999-37-9, Bordeaux, France, September 10-12, 2014
Lean management approaches applied to healthcare systems.
  • F.Longo