Constructing Holistic Patient Flow Simulation Using System Approach
Ontology highlight
ABSTRACT:
SUBMITTER: Krzhizhanovskaya V
PROVIDER: S-EPMC7303693 | biostudies-literature | 2020 May
REPOSITORIES: biostudies-literature
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Project description:BackgroundCrowding can negatively affect patient and staff experience, and consequently the performance of health care facilities. Crowding can potentially be eased through streamlining and the reduction of duplication in patient history-taking through the use of a digital symptom-taking app.ObjectiveWe simulated the introduction of a digital symptom-taking app on patient flow. We hypothesized that waiting times and crowding in an urgent care center (UCC) could be reduced, and that this would be more efficient than simply adding more staff.MethodsA discrete-event approach was used to simulate patient flow in a UCC during a 4-hour time frame. The baseline scenario was a small UCC with 2 triage nurses, 2 doctors, 1 treatment/examination nurse, and 1 discharge administrator in service. We simulated 33 scenarios with different staff numbers or different potential time savings through the app. We explored average queue length, waiting time, idle time, and staff utilization for each scenario.ResultsDiscrete-event simulation showed that even a few minutes saved through patient app-based self-history recording during triage could result in significantly increased efficiency. A modest estimated time saving per patient of 2.5 minutes decreased the average patient wait time for triage by 26.17%, whereas a time saving of 5 minutes led to a 54.88% reduction in patient wait times. Alternatively, adding an additional triage nurse was less efficient, as the additional staff were only required at the busiest times.ConclusionsSmall time savings in the history-taking process have potential to result in substantial reductions in total patient waiting time for triage nurses, with likely effects of reduced patient anxiety, staff anxiety, and improved patient care. Patient self-history recording could be carried out at home or in the waiting room via a check-in kiosk or a portable tablet computer. This formative simulation study has potential to impact service provision and approaches to digitalization at scale.
| S-EPMC8178735 | biostudies-literature
Project description:The Montado is a silvo-pastoral system characterized by open canopy woodlands with natural or cultivated grassland in the undercover and grazing animals. The aims of this study were to present several proximal sensors with potential to monitor relevant variables in the complex montado ecosystem and demonstrate their application in a case study designed to evaluate the effect of trees on the pasture. This work uses data collected between March and June 2016, at peak of dryland pasture production under typical Mediterranean conditions, in twenty four sampling points, half under tree canopy (UTC) and half outside tree canopy (OTC). Correlations were established between pasture biomass and capacitance measured by a commercial probe and between pasture quality and normalized difference vegetation index (NDVI) measured by a commercial active optical sensor. The interest of altimetric and apparent soil electrical conductivity maps as the first step in the implementation of precision agriculture projects was demonstrated. The use of proximal sensors to monitor soil moisture content, pasture photosynthetically active radiation and temperature helped to explain the influence of trees on pasture productivity and quality. The significant and strong correlations obtained between capacitance and pasture biomass and between NDVI and pasture nutritive value (in terms of crude protein, CP and neutral detergent fibre, NDF) can make an important contribution to determination of key components of pasture productivity and quality and implementation of site-specific pasture management. Animal tracking demonstrated its potential to be an important tool for understanding the interaction between various factors and components that interrelate in the montado ecosystem and to support grazing management decisions.
| S-EPMC5855122 | biostudies-other
Project description:Modeling and simulating movement of vehicles in established transportation infrastructures, especially in large urban road networks is an important task. It helps in understanding and handling traffic problems, optimizing traffic regulations and adapting the traffic management in real time for unexpected disaster events. A mathematically rigorous stochastic model that can be used for traffic analysis was proposed earlier by other researchers which is based on an interplay between graph and Markov chain theories. This model provides a transition probability matrix which describes the traffic's dynamic with its unique stationary distribution of the vehicles on the road network. In this paper, a new parametrization is presented for this model by introducing the concept of two-dimensional stationary distribution which can handle the traffic's dynamic together with the vehicles' distribution. In addition, the weighted least squares estimation method is applied for estimating this new parameter matrix using trajectory data. In a case study, we apply our method on the Taxi Trajectory Prediction dataset and road network data from the OpenStreetMap project, both available publicly. To test our approach, we have implemented the proposed model in software. We have run simulations in medium and large scales and both the model and estimation procedure, based on artificial and real datasets, have been proved satisfactory and superior to the frequency based maximum likelihood method. In a real application, we have unfolded a stationary distribution on the map graph of Porto, based on the dataset. The approach described here combines techniques which, when used together to analyze traffic on large road networks, has not previously been reported.
| S-EPMC7872230 | biostudies-literature
Project description:Technological advances in the ability to read the human genome have accelerated the speed of sequencing, such that today we can perform whole genome sequencing (WGS) in one day. Until recently, genomic studies have largely been limited to seeking novel scientific discoveries. The application of new insights gained through cancer WGS into the clinical domain, have been relatively limited. Looking ahead, a vast amount of data can be generated by genomic studies. Of note, excellent organisation of genomic and clinical data permits the application of machine-learning methods which can lead to the development of clinical algorithms that could assist future clinicians and genomicists in the analysis and interpretation of individual cancer genomes. Here, we describe what can be gleaned from holistic whole cancer genome profiling and argue that we must build the infrastructure and educational frameworks to support the modern clinical genomicist to prepare for a future where WGS will be the norm.
| S-EPMC7043936 | biostudies-literature
Project description: Not available
| S-BSST1332 | biostudies-other
Project description:BackgroundIn zoology, species descriptions conventionally rely on invasive morphological techniques, frequently leading to damage of the specimens and thus only a partial understanding of their structural complexity. More recently, non-destructive imaging techniques have successfully been used to describe smaller fauna, but this approach has so far not been applied to identify or describe larger animal species. Here, we present a combination of entirely non-invasive as well as minimally invasive methods that permit taxonomic descriptions of large zoological specimens in a more comprehensive manner.ResultsUsing the single available representative of an allegedly novel species of deep-sea cephalopod (Mollusca: Cephalopoda), digital photography, standardized external measurements, high-field magnetic resonance imaging, micro-computed tomography, and DNA barcoding were combined to gather all morphological and molecular characters relevant for a full species description. The results show that this specimen belongs to the cirrate octopod (Octopoda: Cirrata) genus Grimpoteuthis Robson, 1932. Based on the number of suckers, position of web nodules, cirrus length, presence of a radula, and various shell characters, the specimen is designated as the holotype of a new species of dumbo octopus, G. imperator sp. nov. The digital nature of the acquired data permits a seamless online deposition of raw as well as derived morphological and molecular datasets in publicly accessible repositories.ConclusionsUsing high-resolution, non-invasive imaging systems intended for the analysis of larger biological objects, all external as well as internal morphological character states relevant for the identification of a new megafaunal species were obtained. Potentially harmful effects on this unique deep-sea cephalopod specimen were avoided by scanning the fixed animal without admixture of a contrast agent. Additional support for the taxonomic placement of the new dumbo octopus species was obtained through DNA barcoding, further underlining the importance of combining morphological and molecular datasets for a holistic description of zoological specimens.
| S-EPMC8063452 | biostudies-literature
Project description:Mycetoma, one of the badly neglected tropical diseases, it is a localised chronic granulomatous inflammatory disease characterised by painless subcutaneous mass and formation of multiple sinuses that produce purulent discharge and grains. If untreated early and appropriately, it usually spread to affect the deep structures and bone resulting in massive damage, deformities and disabilities. It can also spread via the lymphatics and blood leading to distant secondary satellites associated with high morbidity and mortality. To date and despite progress in mycetoma research, a huge knowledge gap remains in mycetoma pathogenesis and epidemiology resulting in the lack of objective and effective control programmes. Currently, the available disease control method is early case detection and proper management. However, the majority of patients present late with immense disease and for many of them, heroic substantial deforming surgical excisions or amputation are the only prevailing treatment options. In this communication, the Mycetoma Research Center (MRC), Sudan shares its experience in implementing a new holistic approach to manage mycetoma patients locally at the village level. The MRC in collaboration with Sennar State Ministry of Health, Sudan had established a region mycetoma centre in one of the endemic mycetoma villages in the state. The patients were treated locally in that centre, the local medical and health personals were trained on early case detection and management, the local community was trained on mycetoma advocacy, and environmental conditions improvement. This comprehensive approach had also addressed the patients' socioeconomic constraints that hinder early presentation and treatment. This approach has also included the active local health authorities, community and civil society participation and contributions to deliver the best management. This holistic approach for mycetoma patients' management proved to be effective for early case detection and management, optimal treatment and treatment outcome and favourable disease prognosis. During the study period, the number of patients with massive lesions and the amputation rate had dropped and that had reduced the disease medical and socioeconomic burdens on patients and families.
| S-EPMC5944909 | biostudies-literature
Project description:In this study, we present a novel methodology to infer indel parameters from multiple sequence alignments (MSAs) based on simulations. Our algorithm searches for the set of evolutionary parameters describing indel dynamics which best fits a given input MSA. In each step of the search, we use parametric bootstraps and the Mahalanobis distance to estimate how well a proposed set of parameters fits input data. Using simulations, we demonstrate that our methodology can accurately infer the indel parameters for a large variety of plausible settings. Moreover, using our methodology, we show that indel parameters substantially vary between three genomic data sets: Mammals, bacteria, and retroviruses. Finally, we demonstrate how our methodology can be used to simulate MSAs based on indel parameters inferred from real data sets.
| S-EPMC4700945 | biostudies-literature
Project description:It is difficult to simulate both the flow field and the chemical reaction using, respectively, the flow state and kinetics calculations and actually reflect the influence of the gas flow state on the chemical change in a selective catalytic reduction (SCR) system. In this study, the flow field and the chemical reaction were therefore coupled to simulate a full Cu-Zeolite SCR system and the boundary conditions of the simulation were set by a relevant diesel engine bench test which included the exhaust temperature, the mass flow, and the exhaust pressure. Then, the influence of the gas flow state on the NOx conversion efficiency was investigated. Specifically, an orthogonal experimental design was used to study the influence of the injection parameters (position, angle, and speed) on the NH3 distribution by establishing the NH3 uniformity coefficient γ at the SCR catalyst capture surface in the flow field simulation. Then, the velocity capture surface of the SCR catalyst front section was sliced into coupled data transfer interfaces to study the effects of exhaust temperature, ammonia to NOx ratio (ANR), and the NO2/NOx on the NOx conversion efficiency. This was used as guidelines to optimize the SCR system control strategy. The results showed that a 1150 mm injection position, a 45°injection angle, and a 23 m/s injection velocity provided the most uniform NH3 distribution on the SCR catalyst capture surface. For constant injection parameters, the NOx conversion efficiency was the highest when the exhaust temperature was 200°C-400°C, the ANR was 1.1, and NO2/NOx was 0.5.
| S-EPMC6625702 | biostudies-literature
Project description:How can an income tax system be designed to exploit human nature and a free market to create a poverty free society, while balancing budgets without disproportional tax burdens? Such a tax system, with universal character, is deduced from the following guiding principles: (1) a single tax rate applies to all income types and levels; (2) the tax rate adjusts to satisfy budget projections; (3) government transfer only supplements the income of households with self-generated income below the poverty line; (4) deductions for basic living expenses, itemized investments and capital losses are allowed; (5) deductions cannot be applied to government transfer. A general framework emerges with three parameters that determine a minimum allowed tax deduction, a maximum allowed itemized deduction, and a maximum deduction defined by income percentage. An income distribution that mimics the United States, and a series of log-normal distributions are considered to quantitatively compare detailed characteristics of this tax system to progressive and flat tax systems. To minimize government dependency while maximizing after-tax income, the effective tax rate (ETR) as a function of income percentile takes the shape of the letter, V, inspiring the name victory tax, where the middle class has the lowest ETR.
| S-EPMC8624733 | biostudies-literature