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Population segmentation can be a powerful tool in healthcare management, in helping to match interventions and resources to individuals of a common health state and condition. However, studies to date indicate a lack of alignment to risk stratification – another key tool in Population Health Management – and insufficient demonstration of how segmentation can be used in practice. In this study, we obtain a five-cohort segmentation derived through four incremental thresholds on the risk-based Cambridge Multimorbidity Score, which is calculated for each member of the 762,117 adult population in and around Bristol, England. Appropriately selecting the four thresholds – 0.09, 0.69, 1.59, 2.95 – yields a segmentation with the convenient property that, with increasing risk, segments halve in size and double in per-person spend. The segmentation has been used to support various planning and management activities within the Bristol healthcare system; two of which are detailed here as case studies in demonstrating the practical value of the segmentation model. [ABSTRACT FROM AUTHOR]

The authors present a case of orbital trapdoor fracture with entrapment in an adult patient along with brief summary of the literature.

Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services. [ABSTRACT FROM AUTHOR]

Despite the many examples where simulation has successfully demonstrated its capability in modelling patient flow, there is little evidence of enduring widespread use. Bespoke academic projects provide little scope for repeatable practical application and efforts to develop generic reusable solutions have neither clearly identified the end users nor fully appreciated their multifaceted requirements. Influenced by a review of existing findings and recommendations in addition to a customised survey of prospective end users, a set of practical design principles were elicited in guiding development of a new open-source and versatile tool. Capturing variability in arrivals and length of stay as well as the stochastic nature of dynamic delays in patient discharge and transfer, the PathSimR tool can be used to model various user-defined configurations of outpatient and inpatient pathways. In addition to reporting on early use and engagement initiatives to promote the tool, this study also offers a blueprint for how simulation models can be developed and deployed within the healthcare setting. [ABSTRACT FROM AUTHOR]

Transferring individuals for treatment outside their geographic area occurs when healthcare demand exceeds local supply. This can result in significant financial cost while impacting patient outcomes and experience. The aim of this study was to assess initiatives to reduce psychiatric intensive care unit (PICU) out-of-area bed placements within a major healthcare system in South West England. Discrete event computer simulation was used to model patient flow across the healthcare system's three PICUs. A scenario analysis was performed to estimate the impact of management plans to decrease admissions and length of stay. The amount of capacity required to minimise total cost was also considered. Without increasing in-area capacity, mean out-of-area bed requirement can be reduced by 25.6% and 19.1% respectively through plausible initiatives to decrease admissions and length of stay. Reductions of 34.7% are possible if both initiatives are employed. Adjusting the in-area bed capacity can also lead to aggregate cost savings. This study supports the likely effectiveness of particular initiatives in reducing out-of-area placements for high-acuity bedded psychiatric care. This study also demonstrates the value of computer simulation in an area that has seen little such attention to date. [ABSTRACT FROM AUTHOR]

Francisella tularensis is a virulent bacterium which hijacks the host's immune response, turning cells usually tasked with killing foreign organisms as nutrient-rich receptacles for rapid multiplication. It is designated a Tier 1 Select Agent by the US CDC due to its potential to cause widespread mortality upon deliberate release. In this study, the key biological mechanisms of host infection are modelled as a continuous-time Markov chain (CTMC) and solved via discrete event simulation (DES). The efficacy of various medication strategies at the behest of public health authorities are investigated. Without treatment, the median lethal dose – not previously considered in humans – is estimated at approximately 1,000 organisms. Results suggest that fatality can be averted if antibiotics are administered for at least 7 days, no later than 10 days post exposure. In a mass casualty setting, this can reduce symptomatic cases by 18% from the baseline involving no medication. Reductions of 59% are possible if medication can be disseminated no later than 5 days post exposure, mitigating otherwise severe pressure on healthcare services. Novel use of CTMC and DES highlight the potential for OR in the field of immunology, where further opportunities may present in a post COVID-19 world. [ABSTRACT FROM AUTHOR]

A discussion of knowledge and knowledge-based design, as related to the design of aircraft, is presented. A review of several knowledge-based design activities conducted at NASA Langley Research Center is provided, and a framework for a knowledge-based design capability is proposed and reviewed. The use of information technology to improve the efficiency and effectiveness of aerodynamic and multidisciplinary design, evaluation, and analysis of aircraft through the coupling of these technologies and knowledge-based design is reviewed. The final section of the paper discusses future directions for design and the role of knowledge-based design.

Research has been conducted on the dichloro-, dibromo- and diiodobis(triphenylphosphine oxide)manganese(II) complexes. The measurements of the EPR spectra for these complexes taken at high magnetic fields are presented.

Research was conducted to examine the Na-O system to illustrate the usefulness of the bond valence sum (BVS) in explaining chemical features observed in a crystal structure determination and in evaluating the correctness of the determination. Results illustrate that a pi-type interaction between Na+ and delocalized organic pi-clouds is supported by the BVS measurements. Findings indicate that the BVS is a simple calculation that can be employed to understand the bonding in the complexes.

A bond valence sum (BVS) study of 221 KOn complexes (n = 3-9) obtained from the Cambridge Structural Database was conducted. A new R0 value of 2.113(57) angstroms was computed. Using BVS computations, an interaction between the K+ ion and negatively charged organic groups is suggested. The BVS for K in the K(18-crown-6)+ moiety is usually less than 1. The K+ ion interacted with other ligands so that the final BVS = 1, indicating that the match between the 18-crown-6 and the K+ is not suitable in terms of the electron distribution.

In an early stage of the COVID-19 outbreak, hospitals in England were asked to postpone elective treatments in order to accommodate the expected demand for COVID-19 related admissions. This study aims to forecast the extent to which waiting times could increase as a result of these measures, and estimate the level of effort required to restore performance to pre COVID-19 levels. A time-driven simulation is configured and calibrated based upon conditions in England as of February 2020. As a worst case scenario, where restrictions on elective care extend to twelve months and elective treatment rates are halved, results suggest performance could drop to levels not seen since 2007 and the size of the waiting list could double. Restoring performance would take two years assuming additional capacity injections of 12.5%, costing an estimated £14.7b. The modelling presented here offers clinicians and managers an insight into the outcomes that could result under a range of scenarios considered plausible at the early stage of the outbreak. Freely available as open source code, the model may be locally-calibrated for regional healthcare systems and used more widely in countries where similar elective performance measures exist. [ABSTRACT FROM AUTHOR]