Review on Master Patient Index

In today's health care establishments there is a great diversity of information systems. Each with different specificities and capacities, proprietary communication methods, and hardly allow scalability. This set of characteristics hinders the interoperability of all these systems, in the search for the good of the patient. It is vulgar that, when we look at all the databases of each of these information systems, we come across different registers that refer to the same person; records with insufficient data; records with erroneous data due to errors or misunderstandings when inserting patient data; and records with outdated data. These problems cause duplicity, incoherence, discontinuation and dispersion in patient data. With the intention of minimizing these problems that the concept of a Master Patient Index is necessary. A Master Patient Index proposes a centralized repository, which indexes all patient records of a given set of information systems. Which is composed of a set of demographic data sufficient to unambiguously identify a person and a list of identifiers that identify the various records that the patient has in the repositories of each information system. This solution allows for synchronization between all the actors, minimizing incoherence, out datedness, lack of data, and a decrease in duplicate registrations. The Master Patient Index is an asset to patients, the medical staff and health care providers

Understanding the relationship between design margins and trade-offs

To achieve an objective designers often need to make trade-offs between multiple parameters. In incremental design or during the design process an additional objective is often to minimise the changes they need to make to meet the objective. This is in particular an issue for systems with product platforms, over individual components are over-designed. This paper argues that designers can think about this problem in terms of the margins on the objective parameters as well as the parameters that are traded-off. This is illustrated with the case study of an engineering cooling system

BIM-based Generative Modular Housing Design and Implications for Post-Disaster Housing Recovery

The adverse social and financial impacts of catastrophic disasters are increasing as population centers grow. After disastrous events, the government agencies must respond to post-disaster housing issues quickly and efficiently and provide sufficient resources for the reconstruction of destroyed and damaged houses for full rehabilitation. However, post-disaster housing reconstruction is a highly complex process because of the large number of projects, shortage of resources, and heavy pressure for delivery of the projects after a disastrous event. This complexity and lack of an inconsistent, systematic approach for planning lead to an ad-hoc decision-making process and inefficient recovery. This research explored modular construction as a highly time-efficient approach to tackle the abovementioned challenges and facilitate the housing reconstruction process. Firstly, this research investigated the feasibility of using the modular construction method for rapid post-disaster housing reconstruction through a targeted literature review and survey of subject matter experts to broaden the understanding of modular construction-based post-disaster housing reconstruction, benefits, and barriers. Second, this research focused on improving the design and pre-planning phase of modular construction that can facilitate the successful implementation of modular construction in a post-disaster situation. To this end, a BIM-based generative modular housing design system was developed by using Generative Adversarial Networks (GANs) to automate the entire design process by incorporating manufacturing and construction constraints to fit the needs of the modular construction method. The framework was further extended by developing an optimization model to optimize the modularization strategy in the early design phase which was capable of reflecting the entire multi-stage process of modular construction (production, transportation, and assembly), and considering both individual project’s requirements and post-disaster housing reconstruction portfolio’s requirements. The outcomes of this study fit the MC industry that may be used by designers and modular housing companies looking to automate their design process. It is also expected to provide critical benchmarks for planners, decision-makers, and community developers to facilitate their decision-making process on considering modular construction as an efficient way for mass post-disaster housing reconstruction and addressing communities’ housing needs following a disastrous event

Minimizing the Cost of Innovative Nuclear Technology Through Flexibility: The Case of a Demonstration Accelerator-Driven Subcritical Reactor Park

Presented is a methodology to analyze the expected Levelised Cost Of Electricity (LCOE) in the face of technology uncertainty for Accelerator-Driven Subcritical Reactors (ADSRs). It shows that flexibility in the design and deployment strategy of an ADSR park demonstrator significantly reduces its expected LCOE. The methodology recognizes in the conceptual design a range of possible technological outcomes for the ADSR accelerator system. It identifies flexibility “on” and “in” the design to modify the future development path in light of such uncertain scenarios. Uncertainty and flexibility are incorporated in the ADSR valuation. The resulting economic assessment is more realistic than typical discounted cash flow analysis that does not consider a range of development outcomes, or the flexibility to change development path