Health Systems最新文献

An accurate forecast of Emergency Department (ED) arrivals by an hour of the day is critical to meet patients' demand. It enables planners to match ED staff to the number of arrivals, redeploy staff, and reconfigure units. In this study, we develop a model based on Generalised Additive Models and an advanced dynamic model based on exponential smoothing to generate an hourly probabilistic forecast of ED arrivals for a prediction window of 48 hours. We compare the forecast accuracy of these models against appropriate benchmarks, including TBATS, Poisson Regression, Prophet, and simple empirical distribution. We use Root Mean Squared Error to examine the point forecast accuracy and assess the forecast distribution accuracy using Quantile Bias, PinBall Score and Pinball Skill Score. Our results indicate that the proposed models outperform their benchmarks. Our developed models can also be generalised to other services, such as hospitals, ambulances or clinical desk services.

Healthcare systems are under pressure to control costs and improve performance. Efforts to apply improvement trends such as "Lean" and other industrial engineering approaches have led to degradation of the working environment for healthcare professionals. Research is increasingly demonstrating how poor working environments contribute to declines in care quality and has led to calls for a "quadruple aim" with a focus on the working environment alongside quality, cost, and patient experience factors. This paper contributes to the debate by using a "systems" perspective to propose seven strategies by which healthcare systems might be improved without compromising the working environment. This article presents a rationale for these strategies based on current organisational psychology and human factors research and how these strategies might be deployed in practice. The authors argue that better working conditions leads to better care for patients and presents a viable approach for both practitioners and researchers to pursue the "Better Work, Better Care" agenda.

Kidney exchange programs (KEPs) aim to find compatible kidneys for recipients with incompatible donors. Patients without a living donor depend upon deceased donor (DD) donations to get a kidney transplant. In India, a ©DD donates kidneys directly to a©DD wait-list. The idea of initiating an exchange chain starting from a ©DD kidney is proposed in a few articles (and executed in Italy in 2018), but no mathematical formulation has been given for this merger. We have introduced an integer programming formulation that creates ©DD-initiated chains, considering both paired exchange registry and ©DD allocations simultaneously and addressing the overlap issue between the exchange registry and ©DD wait-list as recipients can register for both registries independently. A long-term simulation study is done to ©analyse the gain of these DD-initiated chains over time. It suggests that even with small numbers of ©DDs, these chains can significantly increase potential transplants.

Home Health Care Routing and Scheduling Problem (HHCRSP) has been widely investigated in operations research. In this paper, a model based on the Constraint Satisfaction Problem (CSP) is proposed, which is able to deal with daily HHCRSPs. Human factors are considered in our formulation of the problem and we seek a balance between the different stakeholders' satisfaction criteria. The considered temporal constraints are soft and controlled by the stakeholders' personalised tolerance and satisfaction rates. We will explain how this new Satisfaction-Oriented HHCRSP (SOH2CRSP) model is built and solved by using an open-source solver: the OptaPlanner. In order to examine the impact of human factors, a study will estimate the added value provided when satisfaction is considered in the problem formulation. The comparison is based on a use case derived from the dataset of an existing HHC organisation. The numerical results will show the benefits of our approach.

Digital transformation is demanding for incumbent organizations such as healthcare, where legacy-based IT architectures challenge the establishment of effective digital services. We refer to this as the IT silo problem, where multiple non-consolidated IT systems are implemented to support expert practices. In this paper, we analyze this challenge using a mirroring lens. Our research question is, how can we create efficient digital services, utilizing the existing legacy systems in healthcare IT architectures? Our empirical evidence comes from a Norwegian case and contributes to the literature on IT architecture within Healthcare. First, we demonstrate how strict mirroring leading to sub-optimization and silofication is a major cause for the presence of IT silos. Second, we describe a process towards adaptive mirroring, and the resulting adaptive mirroring architecture. Adaptive mirroring is an architectural combinatory device that facilitates the design and use of efficient services, while also improving the flexibility of IT architectures.

Shortage of general practitioners (GP) is a challenge worldwide, not only in Europe, but also in countries like New Zealand. Providing primary care in rural areas is especially challenging. In order to support decision makers, it is necessary to first assess the current GP coverage and then to determine different scenarios and plans for the future. In this paper, we first present a thorough overview of related literature on locating GP practices. Second, we propose an approach for assessing the GP coverage and determining future GP locations based on a genetic algorithm framework. As a use case, we have chosen the rural New Zealand region of Northland. We also perform a sensitivity analysis for the main input parameters.

The implementation challenges for modelling and simulation in health and social care are well-known and understood. Yet increasing availability of data and a better understanding of the value of Operational Research (OR) applications are strengthening opportunities to support healthcare delivery. Participative approaches in healthcare modelling have shown value through stakeholder engagement and commitment towards co-creation of models and knowledge but are limited in focus on model design and development. For simulation modelling, a participative design research methodology can support development for sustained use, emphasising model usefulness and usability using iterative cycles of development and evaluation. Within a structured methodology, measures of success are built into the design process, focusing on factors which contribute to success, with implicit goals of implementation and improvement. We illustrate this through a participative case study which demonstrates development of the component parts of a real-time simulation model aimed at reducing emergency department crowding.

Health and medical care are safety-critical environments. The development of a safe and reliable healthcare software system is one of the most important processes which may affect the accuracy of clinical decision making and have an impact on determining diagnoses of and treatment for diseases. The aim of this study is to assess if software quality models, such as McCall, can have an impact on healthcare software quality for the purpose of reducing software failures. We have identified the main criticalities of healthcare software systems based on existing literature, software quality models and programming language standards; we have related these criticalities to software characteristics; we have analysed the relationship between the main criticalities of healthcare software systems and their software characteristics. The following criticalities - the risk of changing hard-coded software and the importance of developing maintainable software - must be addressed at the start of the software development process.