Tracking the patient journey by combining multiple hospital database systems

With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.

Living well with diabetes: 24-month outcomes from a randomized trial of telephone-delivered weight loss and physical activity intervention to improve glycemic control

OBJECTIVE: To evaluate the effectiveness of a telephone-delivered behavioral weight loss and physical activity intervention targeting Australian primary care patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: Pragmatic randomized controlled trial of telephone counseling (n = 151) versus usual care (n = 151). Reported here are 18-month (end-of-intervention) and 24-month (maintenance) primary outcomes of weight, moderate-to-vigorous-intensity physical activity (MVPA; via accelerometer), and HbA1c level. Secondary outcomes include dietary energy intake and diet quality, waist circumference, lipid levels, and blood pressure. Data were analyzed via adjusted linear mixed models with multiple imputation of missing data. RESULTS: Relative to usual-care participants, telephone counseling participants achieved modest, but significant, improvements in weight loss (relative rate [RR] -1.42% of baseline body weight [95% CI -2.54 to -0.30% of baseline body weight]), MVPA (RR 1.42 [95% CI 1.06-1.90]), diet quality (2.72 [95% CI 0.55-4.89]), and waist circumference (-1.84 cm [95% CI -3.16 to -0.51 cm]), but not in HbA1c level (RR 0.99 [95% CI 0.96-1.02]), or other cardio-metabolic markers. None of the outcomes showed a significant change/deterioration over the maintenance period. However, only the intervention effect for MVPA remained statistically significant at 24 months. CONCLUSIONS: The modest improvements in weight loss and behavior change, but the lack of changes in cardio-metabolic markers, may limit the utility, scalability, and sustainability of such an approach.

Optimizing the quantum dot: Plasmon interaction in a nano gap waveguide

Spontaneous emission (SE) of a Quantum emitter depends mainly on the transmission strength between the upper and lower energy levels as well as the Local Density of States (LDOS)[1]. When a QD is placed in near a plasmon waveguide, LDOS of the QD is increased due to addition of the non-radiative decay and a plasmonic decay channel to free space emission[2-4]. The slow velocity and dramatic concentration of the electric field of the plasmon can capture majority of the SE into guided plasmon mode (Гpl ). This paper focused on studying the effect of waveguide height on the efficiency of coupling QD decay into plasmon mode using a numerical model based on finite elemental method (FEM). Symmetric gap waveguide considered in this paper support single mode and QD as a dipole emitter. 2D simulation models are done to find normalized Гpl and 3D models are used to find probability of SE decaying into plasmon mode ( β) including all three decay channels. It is found out that changing gap height can increase QD-plasmon coupling, by up to a factor of 5 and optimally placed QD up to a factor of 8. To make the paper more realistic we briefly studied the effect of sharpness of the waveguide edge on SE emission into guided plasmon mode. Preliminary nano gap waveguide fabrication and testing are already underway. Authors expect to compare the theoretical results with experimental outcomes in the future

Effects of a multiple health behavior change intervention for colorectal cancer survivors on psychosocial outcomes and quality of life: A randomized controlled trial

Background Multiple health behavior change can ameliorate adverse effects of cancer. Purpose The purpose of this study was to determine the effects of a multiple health behavior change intervention (CanChange) for colorectal cancer survivors on psychosocial outcomes and quality of life. Methods A total of 410 colorectal cancer survivors were randomized to a 6-month telephone-based health coaching intervention (11 sessions using acceptance and commitment therapy strategies focusing on physical activity, weight management, diet, alcohol, and smoking) or usual care. Posttraumatic growth, spirituality, acceptance, mindfulness, distress, and quality of life were assessed at baseline, 6 and 12 months. Results Significant intervention effects were observed for posttraumatic growth at 6 (7.5, p < 0.001) and 12 months (4.1, p = 0.033), spirituality at 6 months (1.8, p = 0.011), acceptance at 6 months (0.2, p = 0.005), and quality of life at 6 (0.8, p = 0.049) and 12 months (0.9, p = 0.037). Conclusions The intervention improved psychosocial outcomes and quality of life (physical well-being) at 6 months with most effects still present at 12 months. (Trial Registration Number: ACTRN12608000399392).

Applying POVM to model non-orthogonality in quantum cognition

Much of the work currently occurring in the field of Quantum Interaction (QI) relies upon Projective Measurement. This is perhaps not optimal, cognitive states are not nearly as well behaved as standard quantum mechanical systems; they exhibit violations of repeatability, and the operators that we use to describe measurements do not appear to be naturally orthogonal in cognitive systems. Here we attempt to map the formalism of Positive Operator Valued Measure (POVM) theory into the domain of semantic memory, showing how it might be used to construct Bell-type inequalities.

Covitality constructs as predictors of psychological well-being and depression for secondary school students'

This study was an examination of the strength of relations among covitality, and its underlying constructs of belief in self, emotional competence, belief in others, and engaged living, and two outcome variables; subjective well-being and depression. Participants included 361 Australian secondary school students (75 males and 286 females) who completed a series of online questionnaires related to positive psychological well-being in adolescents. The results from the first standard multiple regression analysis indicated that higher levels of belief in self, belief in others, and engaged living were significant predictors of increased subjective well-being. The results from the second standard multiple regression showed that higher levels of belief in self, belief in others, and engaged living were significant predictors of decreased feelings of depression. In both standard multiple regression models, the combined effect of the traits that comprise covitality was greater than the effect of each individual positive psychological trait.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

Estimation of growth parameters from multiple-recapture data

This article develops a method for analysis of growth data with multiple recaptures when the initial ages for all individuals are unknown. The existing approaches either impute the initial ages or model them as random effects. Assumptions about the initial age are not verifiable because all the initial ages are unknown. We present an alternative approach that treats all the lengths including the length at first capture as correlated repeated measures for each individual. Optimal estimating equations are developed using the generalized estimating equations approach that only requires the first two moment assumptions. Explicit expressions for estimation of both mean growth parameters and variance components are given to minimize the computational complexity. Simulation studies indicate that the proposed method works well. Two real data sets are analyzed for illustration, one from whelks (Dicathais aegaota) and the other from southern rock lobster (Jasus edwardsii) in South Australia.

Taiwanese migrants in Australia: An investigation of their accultration and well-being

Taiwanese migrants settled in Brisbane, Australia (N=271) completed a questionnaire battery available in both Mandarin and English. A series of multiple and hierarchical regression analyses were used to investigate the factors associated with these migrants’ acculturation and indicators of psychological well-being. Results indicated that various personal factors (age, English language proficiency and duration of stay) were associated with acculturation and indicators of psychological wellbeing. Acculturation was not associated with wellbeing. Social support was associated with the indicators of the participants’ wellbeing. The outcome indicated that although associated with similar personal and environmental factors, acculturation and psychological wellbeing occurred separately. The study highlights the significance of certain personal resources and social support.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.