A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

This paper examines the development of clinical pathways in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system (DSS) is developed and analyzed for this purpose. System dynamics was used as the simulation modeling tool because of its rigorous approach in capturing interrelationships among variables and in handling dynamic aspects of the system behavior in managing healthcare. The study highlights the scenarios that will help hospital administrators to redistribute caseloads amongst admitting clinicians with a focus on multiple Diagnostic Related Groups (DRG’s) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRG’s are the best known classification system used in a casemix funding model. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources. Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. The analyses act as a scratch pad for the executives as they understand what can be feasibly achieved by the implementation of clinical pathways given a number of constraints. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that the DSS can enhance group learning processes and improve decision making. The simulation model findings support recent studies of CP implementation on various DRG’s published in the medical literature. These studies showed substantial reductions in length of stay, costs and resource utilization

A dynamic policy model to manage temporal performance amongst contracting firms in a competitive situation

Studies have been conducted to measure competitiveness in the construction industry. Such research has focused on all levels from the national picture to individual projects. While useful, the results are limited in that they present a snapshot picture at one point in time. Moreover, they do not suggest how under-performance might be improved. The research reported here is part of a large collaborative study to evaluate sustained competitiveness in the UK construction industry. It enhances previous research in that a system dynamics model of contracting firms operating in competition is used to not only measure each firm’s temporal performance by means of a dynamic competitive index, but it can also suggest high leverage policies which mitigate against under-performance. The model structure is described and simulated scenario runs presented. Besides the contribution to strategic policy making at the level of the contracting firm, the exemplar shows that the system dynamics methodology could have significant utility in the field of construction management

High water availability increases the negative impact of a native hemiparasite on its non-native host

Environmental factors alter the impacts of parasitic plants on their hosts. However, there have been no controlled studies on how water availability modulates stem hemiparasites' effects on hosts. A glasshouse experiment was conducted to investigate the association between the Australian native stem hemiparasite Cassytha pubescens and the introduced host Ulex europaeus under high (HW) and low (LW) water supply. Cassytha pubescens had a significant, negative effect on the total biomass of U. europaeus, which was more severe in HW than LW. Regardless of watering treatment, infection significantly decreased shoot and root biomass, nodule biomass, nodule biomass per unit root biomass, F-v/F-m, and nitrogen concentration of U. europaeus. Host spine sodium concentration significantly increased in response to infection in LW but not HW conditions. Host water potential was significantly higher in HW than in LW, which may have allowed the parasite to maintain higher stomatal conductances in HW. In support of this, the delta C-13 of the parasite was significantly lower in HW than in LW (and significantly higher than the host). C. pubescens also had significantly higher F-v/F-m and 66% higher biomass per unit host in the HW compared with the LW treatment. The data suggest that the enhanced performance of C. pubescens in HW resulted in higher parasite growth rates and thus a larger demand for resources from the host, leading to poorer host performance in HW compared with LW. C. pubescens should more negatively affect U. europaeus growth under wet conditions rather than under dry conditions in the field

The Turkey Ig-like receptor family: identification, expression and function.

The chicken leukocyte receptor complex located on microchromosome 31 encodes the chicken Ig-like receptors (CHIR), a vastly expanded gene family which can be further divided into three subgroups: activating CHIR-A, bifunctional CHIR-AB and inhibitory CHIR-B. Here, we investigated the presence of CHIR homologues in other bird species. The available genome databases of turkey, duck and zebra finch were screened with different strategies including BLAST searches employing various CHIR sequences, and keyword searches. We could not identify CHIR homologues in the distantly related zebra finch and duck, however, several partial and complete sequences of CHIR homologues were identified on chromosome 3 of the turkey genome. They were designated as turkey Ig-like receptors (TILR). Using cDNA derived from turkey blood and spleen RNA, six full length TILR could be amplified and further divided according to the typical sequence features into one activating TILR-A, one inhibitory TILR-B and four bifunctional TILR-AB. Since the TILR-AB sequences all displayed the critical residues shown to be involved in binding to IgY, we next confirmed the IgY binding using a soluble TILR-AB1-huIg fusion protein. This fusion protein reacted with IgY derived from various gallinaceous birds, but not with IgY from other bird species. Finally, we tested various mab directed against CHIR for their crossreactivity with either turkey or duck leukocytes. Whereas no staining was detectable with duck cells, the CHIR-AB1 specific mab 8D12 and the CHIR-A2 specific mab 13E2 both reacted with a leukocyte subpopulation that was further identified as thrombocytes by double immunofluorescence employing B-cell, T-cell and thrombocyte specific reagents. In summary, although the turkey harbors similar LRC genes as the chicken, their distribution seems to be distinct with predominance on thrombocytes rather than lymphocytes

Evaluating the use of lecture capture using a revealed preference approach

This article discusses the introduction of lecture capture technology on a large undergraduate module with diverse student cohorts. Literature has so far relied on surveying students to discover their use of the technology or attempted to quantify the impact of watching lecture recordings on assessment performance. Alternatively, the principal contribution of this article is an evaluation of the use of the recorded lectures using a revealed preference approach. Specifically we identify to what extent students watched lecture recordings, rather than simply claimed to watch them when asked to provide comments on the technology. Data indicates the number of distinct students who watched recordings, the frequency with which they watched recordings, the average length of viewings as well as the time of day when lectures were viewed. We monitored viewings over two academic years, identifying ‘spikes’ in the number of viewings in the days before tests, as well as regularities in the viewing patterns across the two years. We analyse the data to assess the extent to which students used the recordings, how and when they watched the recordings. We conclude that the students value lecture recordings, making more extensive use of the recordings than has been identified in the literature to date. Ultimately, lecture recordings are suggested to offer valuable support for students’ independent study

Study of Optimal Perimetric Testing In Children (OPTIC): Normative visual field values in children

Purpose: We sought to define normative visual field (VF) values for children using common clinical test protocols for kinetic and static perimetry. Design: Prospective, observational study. Subjects: We recruited 154 children aged 5 to 15 years without any ophthalmic condition that would affect the VF (controls) from pediatric clinics at Moorfields Eye Hospital. Methods: Children performed perimetric assessments in a randomized order using Goldmann and Octopus kinetic perimetry, and Humphrey static perimetry (Swedish Interactive Thresholding Algorithm [SITA] 24-2 FAST), in a single sitting, using standardized clinical protocols, with assessment by a single examiner. Unreliable results (assessed qualitatively) were excluded from the normative data analysis. Linear, piecewise, and quantile mixed-effects regression models were used. We developed a method to display age-specific normative isopters graphically on a VF plot to aid interpretation. Main Outcome Measures: Summary measures and graphical plots describing normative VF data for 3 common perimetric tests. Results: Visual field area increased with age on testing with Goldmann isopters III4e, I4e, and I2e (linear regression; P < 0.001) and for Octopus isopters III4e and I4e (linear regression; P < 0.005). Visual field development occurs predominately in the infero-temporal field. Humphrey mean deviation (MD) showed an increase of 0.3 decibels (dB; 95% CI, 0.21-0.40) MD per year up to 12 years of age, when adult MD values were reached and thereafter maintained. Conclusions: Visual field size and sensitivity increase with age in patterns that are specific to the perimetric approach used. These developmental changes should be accounted for when interpreting perimetric test results in children, particularly when monitoring change over time

Oscillatory behavior of two nonlinear microbial models of soil carbon decomposition

A number of nonlinear models have recently been proposed for simulating soil carbon decomposition. Their predictions of soil carbon responses to fresh litter input and warming differ significantly from conventional linear models. Using both stability analysis and numerical simulations, we showed that two of those nonlinear models (a two-pool model and a three-pool model) exhibit damped oscillatory responses to small perturbations. Stability analysis showed the frequency of oscillation is proportional to √(ε⁻¹-1) Ks/Vs in the two-pool model, and to √(ε⁻¹-1) Kl/Vl in the three-pool model, where ε is microbial growth efficiency, Ks and Kl are the half saturation constants of soil and litter carbon, respectively, and /Vs and /Vl are the maximal rates of carbon decomposition per unit of microbial biomass for soil and litter carbon, respectively. For both models, the oscillation has a period of between 5 and 15 years depending on other parameter values, and has smaller amplitude at soil temperatures between 0 and 15°C. In addition, the equilibrium pool sizes of litter or soil carbon are insensitive to carbon inputs in the nonlinear model, but are proportional to carbon input in the conventional linear model. Under warming, the microbial biomass and litter carbon pools simulated by the nonlinear models can increase or decrease, depending whether ε varies with temperature. In contrast, the conventional linear models always simulate a decrease in both microbial and litter carbon pools with warming. Based on the evidence available, we concluded that the oscillatory behavior and insensitivity of soil carbon to carbon input are notable features in these nonlinear models that are somewhat unrealistic. We recommend that a better model for capturing the soil carbon dynamics over decadal to centennial timescales would combine the sensitivity of the conventional models to carbon influx with the flexible response to warming of the nonlinear model.15 page(s

Heuristics as Bayesian inference under extreme priors

Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics