A simulation/optimisation approach to support the resource allocation in service firms

Romano, Elpidio; Iuliano, Domenico

doi:10.1504/ijpm.2018.088615

Cited by 6 publications

(2 citation statements)

References 18 publications

(21 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To improve resource management, cost containment, and responsibility in healthcare, it is crucial to establish information systems that can aid hospital managers in financial management, resource allocation, and activity planning [ 91 – 94 ]. The impacts of different operating strategies can be identified by building and validating computer simulation models, which leads to higher efficiency for the hospital’s resources without decreasing the quality of patient care [ 95 ].…”

Section: Resultsmentioning

confidence: 99%

The application of artificial intelligence in health financing: a scoping review

Ramezani,

Takian,

Bakhtiari

et al. 2023

Cost Eff Resour Alloc

View full text Add to dashboard Cite

Introduction Artificial Intelligence (AI) represents a significant advancement in technology, and it is crucial for policymakers to incorporate AI thinking into policies and to fully explore, analyze and utilize massive data and conduct AI-related policies. AI has the potential to optimize healthcare financing systems. This study provides an overview of the AI application domains in healthcare financing. Method We conducted a scoping review in six steps: formulating research questions, identifying relevant studies by conducting a comprehensive literature search using appropriate keywords, screening titles and abstracts for relevance, reviewing full texts of relevant articles, charting extracted data, and compiling and summarizing findings. Specifically, the research question sought to identify the applications of artificial intelligence in health financing supported by the published literature and explore potential future applications. PubMed, Scopus, and Web of Science databases were searched between 2000 and 2023. Results We discovered that AI has a significant impact on various aspects of health financing, such as governance, revenue raising, pooling, and strategic purchasing. We provide evidence-based recommendations for establishing and improving the health financing system based on AI. Conclusions To ensure that vulnerable groups face minimum challenges and benefit from improved health financing, we urge national and international institutions worldwide to use and adopt AI tools and applications.

show abstract

Section: Resultsmentioning

confidence: 99%

The application of artificial intelligence in health financing: a scoping review

Ramezani,

Takian,

Bakhtiari

et al. 2023

Cost Eff Resour Alloc

View full text Add to dashboard Cite

show abstract

“…The discrete process is realized within the SD simulation environment itself. A previous attempt of such an approach can be traced back to [36][37][38][39][40]. The idea, by now consolidated for the authors, is to follow the states' evolution of the system, e.g., being time-driven, that is, recording the values of the state's variable states at regular intervals of time.…”

Section: Related Literaturementioning

confidence: 99%

Lean ICU Layout Re-Design: A Simulation-Based Approach

et al. 2022

View full text Add to dashboard Cite

Healthcare facilities require flexible layouts that can adapt quickly in the face of various disruptions. COVID-19 confirmed this need for both healthcare and manufacturing systems. Starting with the transfer of decision support systems from manufacturing, this paper generalizes layout re-design activities for complex systems by presenting a simulation framework. Through a real case study concerning the proliferation of nosocomial cross-infection in an intensive care unit (ICU), the model developed in systems dynamics, based on a zero order immediate logic, allows reproducing the evolution of the different agencies (e.g., physicians, nurses, ancillary workers, patients), as well as of the cyber-technical side of the ICU, in its general but also local aspects. The entire global workflow is theoretically founded on lean principles, with the goal of balancing the need for minimal patient throughput time and maximum efficiency by optimizing the resources used during the process. The proposed framework might be transferred to other wards with minimal adjustments; hence, it has the potential to represent the initial step for a modular depiction of an entire healthcare facility.

show abstract