Estimating Bed Requirements for a Pediatric Department in a University Hospital in Egypt

Every day, a considerable number of children in need for health monitoring and control are turned away because of lack of beds in the Pediatric department in Zagazig University hospital in Egypt. This paper estimates the required number of beds needed for controlling this number of turned away children. The paper also investigates the effect of redistributing beds among different specialties on the service level. An Erlang Loss model is applied for estimating required capacity, then an optimization model is used for finding the optimum bed distribution that minimize number of turned away children

Dynamic Resource Allocation For Coordination Of Inpatient Operations In Hospitals

Healthcare systems face difficult challenges such as increasing complexity of processes, inefficient utilization of resources, high pressure to enhance the quality of care and services, and the need to balance and coordinate the staff workload. Therefore, the need for effective and efficient processes of delivering healthcare services increases. Data-driven approaches, including operations research and predictive modeling, can help overcome these challenges and improve the performance of health systems in terms of quality, cost, patient health outcomes and satisfaction. Hospitals are a key component of healthcare systems with many scarce resources such as caregivers (nurses, physicians) and expensive facilities/equipment. Most hospital systems in the developed world have employed some form of an Electronic Health Record (EHR) system in recent years to improve information flow, health outcomes, and reduce costs. While EHR systems form a critical data backbone, there is a need for platforms that can allow coordinated orchestration of the relatively complex healthcare operations. Information available in EHR systems can play a significant role in providing better operational coordination between different departments/services in the hospital through optimized task/resource allocation. In this research, we propose a dynamic real-time coordination framework for resource and task assignment to improve patient flow and resource utilization across the emergency department (ED) and inpatient unit (IU) network within hospitals. The scope of patient flow coordination includes ED, IUs, environmental services responsible for room/bed cleaning/turnaround, and patient transport services. EDs across the U.S. routinely suffer from extended patient waiting times during admission from the ED to the hospital\u27s inpatient units, also known as ED patient `boarding\u27. This ED patient boarding not only compromises patient health outcomes but also blocks access to ED care for new patients from increased bed occupancy. There are also significant cost implications as well as increased stress and hazards to staff. We carry out this research with the goal of enabling two different modes of coordination implementation across the ED-to-IU network to reduce ED patient boarding: Reactive and Proactive. The proposed `reactive\u27 coordination approach is relatively easy to implement in the presence of modern EHR and hospital IT management systems for it relies only on real-time information readily available in most hospitals. This approach focuses on managing the flow of patients at the end of their ED care and being admitted to specific inpatient units. We developed a deterministic dynamic real-time coordination model for resource and task assignment across the ED-to-IU network using mixed-integer programming. The proposed \u27proactive\u27 coordination approach relies on the power of predictive analytics that anticipate ED patient admissions into the hospital as they are still undergoing ED care. The proactive approach potentially allows additional lead-time for coordinating downstream resources, however, it requires the ability to accurately predict ED patient admissions, target IU for admission, as well as the remaining length-of-stay (care) within the ED. Numerous other studies have demonstrated that modern EHR systems combined with advances in data mining and machine learning methods can indeed facilitate such predictions, with reasonable accuracy. The proposed proactive coordination optimization model extends the reactive deterministic MIP model to account for uncertainties associated with ED patient admission predictions, leading to an effective and efficient proactive stochastic MIP model. Both the reactive and proactive coordination methods have been developed to account for numerous real-world operational requirements (e.g., rolling planning horizon, event-based optimization and task assignments, schedule stability management, patient overflow management, gender matching requirements for IU rooms with double occupancy, patient isolation requirements, equity in staff utilization and equity in reducing ED patient waiting times) and computational efficiency (e.g., through model decomposition and efficient construction of scenarios for proactive coordination). We demonstrate the effectiveness of the proposed models using data from a leading healthcare facility in SE-Michigan, U.S. Results suggest that even the highly practical optimization enabled reactive coordination can lead to dramatic reduction in ED patient boarding times. Results also suggest that signification additional reductions in patient boarding are possible through the proposed proactive approach in the presence of reliable analytics models for prediction ED patient admissions and remaining ED length-of-stay. Future research can focus on further extending the scope of coordination to include admissions management (including any necessary approvals from insurance), coordination needs for admissions that stem from outside the ED (e.g., elective surgeries), as well as ambulance diversions to manage patient flows across the region and hospital networks

An Optimization Model for Integrated Capacity Management and Bed Allocation Planning of Hospitals

Hospitals are facing with increasing demands of unlimited needs of people health. On the other hand, due to the rising cost of healthcare services, hospitals need to put more effort in order to overcome these two problems. This paper deals with proposing an integrated strategy for solving these problems. We address an integer optimization model which integrate capacity staff management problem and bed allocation planning problem. We solve the model using a direct approach, based on the notion of superbasic variables

The Optimal Number of Hospital Beds Under Uncertainty: A Costs Management Approach

Equipping hospital beds uses a great deal of a hospital''''s resources. Therefore, it is essential to consider the hospital beds'''' efficiency. To increase its efficiency, a fuzzy unrestricted model for managing hospital expenses is presented in this paper. The lack of beds in hospitals leads to patients’ admission loss and consecutively profit loss. On the other hand, increasing the bed count leads to an increase in equipment expenses. Therefore, in order to determine optimal bed capacity, it is of utmost importance to consider these two costs simultaneously. In our paper, hospital admission system is modeled with a multi-server queuing system (M/M/K). Therefore, to calculate the total cost function, limiting probabilities of multi-server queueing model is used. Furthermore, due to uncertain nature of parameters, such as interest rate and hospitalization profit in various future time periods, these uncertainties are covered by fuzzy logic. Finally, to determine the optimal bed count, Lee and Li''''s fuzzy ranking method is used. This model is implemented ona case study. Its goal is to determine the optimal bed count for emergency unit of Razi hospital in Torbat Heydarieh. Considering the high capability of Markovian chains in modeling different circumstances and the various queueing models, the proposed model can be extended for various hospital units

Improvement of outpatient service processes based on BRP theory and information technology: a case study of the University of Hong Kong-Shenzhen Hospital

JEL Classification: M15 – IT Management, I12 – Health ProductionCurrently, due to some irrational allocation of medical and healthcare resources, a considerable proportion of state-of-the-art medical equipment and talented medical personnel are concentrated in large urban hospitals. This situation is particularly common in 3A hospitals (3A hospitals are hospitals which are equipped with more than 501 beds, can provide medical and healthcare services with high-level specialty to various regions and with scores higher than 900 according to the grading standard), which are often crowded with patients. According to the normal outpatient process, patients need to undergo a prolonged procedure from registration, treatment, laboratory test, diagnosis to drug dispensing. Often patients have to spend a long time waiting for treatment, receiving tests and paying for medical care. The congestion of patients at certain time-consuming processes allows doctors little time to check and treat patients thoroughly. As a result, doctors are often unable to make accurate and comprehensive diagnosis. Considered the window of a hospital, outpatient service is extremely important. Whether the design of its process is reasonable and whether its management is able to maximize interests for patients will directly affect the hospital’s medical level, and even its social benefits and reputation. Therefore, it has become a major issue for a hospital achieves to optimize the business process of its outpatient service. Outpatient process, as a core business process of a hospital, is critical to improving the quality of its medical service, upgrading its performance and minimizing its operating costs. Therefore, re-designing the outpatient process of a hospital can help enhance its comprehensive strength by endowing it with a core competence. In addition, the hospital will be impelled to provide patients with more convenient medical services with higher quality and lower price. This work conducts a case study on The University of Hong Kong-Shenzhen Hospital (HKU-SZH), which was the first to implement an outpatient appointment registration system. This thesis gives an anatomy of the outpatient process of the hospital through various methods and theories, such as literature review, field research, expert consultation, Business Process Reengineering Theory and Information technology, aiming to identify objectives and strategies of the case hospital in improving its outpatient process. The study consists of: - An investigation into the current situation of HKU-SZH’s outpatient registration process: through questionnaires and structured interviews, the defects and weak links in the hospital’s appointment registration model were analyzed. A structural equation model for existing outpatient processes was established and the influence of different variables on patients’ satisfaction level as well as the correlation between these variables was analyzed by means of a simulation model. - Research on outpatient process reengineering: with the needs and satisfaction of patients as a goal, this thesis reexamines the strategic goals and internal and external environment of HKU-SZH on the basis of Business Process Reengineering Theory, Queuing Theory, Six Sigma Theory and Information technology. This thesis improves HKU-SZH’s registration process, using methods of order modification, integration, simplification and automation and materializes the process by network technology and outpatient information system. - An empirical study on outpatient process: this thesis conducts a systemic and empirical analysis in a functional integration of registration and payment, process reengineering research through information technology (development of new functions of appointment system) and an empirical study on queuing theory. - Research on local adaptation of outpatient process: this thesis explores solutions and suggestions for HKU-SZH with the objective of optimize its outpatient process through the perspectives of hospital organizational structure, information technology, human resources, building of outpatient culture and optimization of waiting cost. By means of outpatient process reengineering, this thesis aim to increase the case hospital’s efficiency and raise its patients’ satisfaction so that the hospital may enhance its comprehensive competence. In addition, an effective and operable methodology will be generated, which is expected to serve as a reference for other hospitals to improve their operation and their management.Atualmente, devido a alguma atribuição irracional dos recursos médicos e de saúde, uma proporção considerável de modernos equipamentos médicos e pessoal médico talentoso estão concentrados em grandes hospitais urbanos. Esta situação é particularmente comum em hospitais 3A (hospitais 3A são os hospitais que estão equipados com mais de 501 camas, e que podem fornecer serviços médicos e de saúde com alto nível de especialidade para diversas regiões e com pontuações superiores a 900 de acordo com o padrão de classificação), que são frequentemente sobrelotados com pacientes. De acordo com o processo ambulatório normal, os pacientes precisam passar por um procedimento prolongado desde o registo, tratamento, análise laboratorial, diagnóstico, até à distribuição de medicamentos. Muitas vezes os pacientes têm de passar um longo tempo de espera para tratamento, para receber testes e para pagar por cuidados médicos. O congestionamento de pacientes em determinados processos demorados, leva a que os médicos tenham pouco tempo para verificar e tratar os pacientes completamente. Como resultado, os médicos são muitas vezes incapazes de fazer um diagnóstico preciso e abrangente. Considerado a montra de um hospital, o serviço ambulatório é extremamente importante. Se o desenho do seu processo é razoável e se a sua gestão é capaz de maximizar os interesses dos pacientes, irá afetar diretamente o nível médico do hospital, e até mesmo os seus benefícios sociais e reputação. Portanto, tornou-se um importante problema para um hospital conseguir otimizar o processo do seu serviço ambulatório. O processo ambulatório, como um processo de negócio nuclear de um hospital, é fundamental para melhorar a qualidade do seu serviço médico, aumentar o seu desempenho e minimizar seus custos operacionais. Portanto, reprojetar o processo ambulatório de um hospital pode ajudar a aumentar a sua força global dotando-o de uma competência essencial. Além disso, o hospital será impelido a oferecer aos pacientes serviços médicos mais convenientes com maior qualidade e menor preço. Este trabalho apresenta um estudo de caso sobre o Hospital da Universidade de Hong Kong-Shenzhen (HKU-SZH), que foi o primeiro a implementar um sistema de registo de consulta externa. Esta tese apresenta uma análise do processo ambulatório do hospital através de vários métodos e teorias, como a revisão de literatura, pesquisa de campo, consultas a especialistas, teoria da reengenharia de processos e tecnologias da informação, com o objetivo de identificar os objetivos e estratégias do hospital na melhoria do seu serviço ambulatório. O estudo consiste em: - Investigação sobre a situação atual do processo de registo ambulatório de HKU-SZH. Através de questionários e entrevistas estruturadas, foram analisados os defeitos e pontos fracos no modelo de registro de consultas do hospital. Um modelo de equações estruturais para os processos ambulatórios existentes foi estabelecido, e a influência de diferentes variáveis sobre o nível de satisfação dos pacientes, bem como a correlação entre essas variáveis foi analisada por meio de um modelo de simulação. - Investigação sobre a reengenharia do processo ambulatório. Tendo as necessidades e satisfação dos pacientes como objetivo, esta tese reexamina as metas estratégicas e o ambiente interno e externo de HKU-SZH com base na Teoria da Reengenharia de Processos, Teoria das Filas, Teoria Six Sigmae Tecnologias da Informação. Esta tese melhora o processo de registro de HKU-SZH, usando métodos de modificação, integração, simplificação e automação e materializa o processo através de tecnologias de rede e um sistema de informação para o processo ambulatório. - Estudo empírico sobre o processo ambulatório. Esta tese conduz uma análise sistémica e empírica sobre a integração funcional de inscrições e pagamentos, a pesquisa de reengenharia de processos através de tecnologias da informação (desenvolvimento de novas funções do sistema de consultas) e um estudo empírico sobre a teoria das filas. - Investigação sobre a adaptação local do processo ambulatório. Esta tese explora soluções e sugestões para o HKU-SZH para otimizar seu processo ambulatório através das perspetivas de estrutura hospitalar organizacional, tecnologias da informação, recursos humanos, construção da cultura do ambulatório e otimização do custo de espera. Por meio do processo de reengenharia do serviço de ambulatório, esta tese visa aumentar a eficiência do processo de internamento e aumentar a satisfação dos seus pacientes para que o hospital possa aumentar a sua capacidade global. Além disso, foi gerada uma metodologia eficiente e operacionalizavel, a qual se espera possa servir como referência para outros hospitais, para melhorar o seu funcionamento e a sua gestão

Process improvement approaches for increasing the response of emergency departments against the Covid-19 pandemic: a systematic review

The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions

Integral resource capacity planning for inpatient care services based on hourly bed census predictions

The design and operations of inpatient care facilities are typically largely historically shaped. A better match with the changing environment is often possible, and even inevitable due to the pressure on hospital budgets. Effectively organizing inpatient care requires simultaneous consideration of several interrelated planning issues. Also, coordination with upstream departments like the operating theater and the emergency department is much-needed. We present a generic analytical approach to predict bed census on nursing wards by hour, as a function of the Master Surgical Schedule (MSS) and arrival patterns of emergency patients. Along these predictions, insight is gained on the impact of strategic (i.e., case mix, care unit size, care unit partitioning), tactical (i.e., allocation of operating room time, misplacement rules), and operational decisions (i.e., time of admission/discharge). The method is used in the Academic Medical Center Amsterdam as a decision support tool in a complete redesign of the inpatient care operations