Profiles identification on hierarchical tree structure data sets

In this work we study a way to explore and extract more information from data sets with a hierarchical tree structure. We propose that any statistical study on this type of data should be made by group, after clustering. In this sense, the most adequate approach is to use the Mahalanobis–Wasserstein distance as a measure of similarity between the cases, to carry out clustering or unsupervised classification. This methodology allows for the clustering of cases, as well as the identification of their profiles, based on the distribution of all the variables that characterises each subject associated with each case. An application to a set of teenagers' interviews regarding their habits of communication is described. The interviewees answered several questions about the kind of contacts they had on their phone, Facebook, email or messenger as well as the frequency of communication between them. The results indicate that the methodology is adequate to cluster this kind of data sets, since it allows us to identify and characterise different profiles from the data. We compare the results obtained with this methodology with the ones obtained using the entire database, and we conclude that they may lead to different findings.     

加强医院青年文化建设初探——以广西医科大学第一附属医院为例

如何加强医院青年文化建设,引导青年成才,促进青年在医疗事业中发挥更重要的作用,已经成为医院发展面临的一项新课题。针对医院青年文化建设存在的引导方式陈旧、活动组织困难、活动同质化等问题,应坚持先进文化的前进方向,用社会主义核心价值观引领青年文化建设;加大投入,加强激励,贴近实际,加强文化阵地建设,活跃青年文化生活;加强引领与品牌管理,构建特色品牌文化体系;强化医学人文精神,倡导职业文明。     

浅谈洁净手术部在医院基建工程中的特殊需求

随着现代医学的发展,洁净手术部成为各手术学科建设与发展的重要前提与支柱,对原有手术室功能进行改造势在必行。为了实现医院洁净手术部向信息化、智能化、集约化发展,从洁净手术部的选址、功能等方面介绍了当前省内部分二级以上医疗单位洁净手术室建设的新进展,总结近年来在洁净手术室规划、建设过程中的经验,为现代医院基建工程管理提供借鉴,保障医院医疗、教学、科研工作的顺利开展。     

Local estimation for varying-coefficient models with longitudinal data

Varying-coefficient models are very useful for longitudinal data analysis. In this paper, we focus on varying-coefficient models for longitudinal data. We develop a new estimation procedure using Cholesky decomposition and profile least squares techniques. Asymptotic normality for the proposed estimators of varying-coefficient functions has been established. Monte Carlo simulation studies show excellent finite-sample performance. We illustrate our methods with a real data example.     

Modified profile likelihood estimation for the Weibull regression models in survival analysis

In this study, adjustment of profile likelihood function of parameter of interest in presence of many nuisance parameters is investigated for survival regression models. Our objective is to extend the Barndorff–Nielsen’s technique to Weibull regression models for estimation of shape parameter in presence of many nuisance and regression parameters. We conducted Monte-Carlo simulation studies and a real data analysis, all of which demonstrate and suggest that the modified profile likelihood estimators outperform the profile likelihood estimators in terms of three comparison criterion: mean squared errors, bias and standard errors.     

Danish and Norwegian hospital social workers’ cross-institutional work amidst inter-sectoral restructuring of health and social welfare

Starting in the 2000s, Denmark and Norway have undergone extensive restructuring of their health-related social benefit programmes, including how they are governed. Several reforms have sought to enhance inter-sectoral collaboration. Aiming at ensuring patients’ faster return to work, policy-makers have instituted economic incentives to both individuals and the health and welfare organisations who handle them. Through an institutional logics approach, this paper explores how hospital social workers in these countries are experiencing these changes. The ‘social’ part of post-treatment care and rehabilitation receives more attention in the Norwegian institutional set-up than in the Danish, and whilst challenges are experienced in both countries, in group interviews Danish social workers in particular express concerns about the implications of the accelerated return-to-work focus. In both countries, they report increasing difficulties in ‘making their way through’ the state-municipal bureaucracy. However, by drawing on the formal health knowledge derived from medical settings and the symbolic capital it bestows on them, they often manage to negotiate the work-and-welfare services, thereby transforming the social context for the patients.     

Material logistics in hospitals: A literature review

Hospital material management has been identified as one key cost containment lever to cope with steadily increasing healthcare costs in industrialized countries. The purpose of this work is to present the state-of-the-art of research on material logistics management in hospitals. Particular focus is given to articles that apply quantitative methods. Our contribution is threefold: First, we provide research guidance through categorizing literature and identifying major research streams. Second, we discuss applied methodologies and third, we identify future research directions. A systematic approach is undertaken in order to identify the relevant literature from 1998 to 2014. Applicable publications are categorized thematically and methodologically and future research opportunities are worked out. In total, 145 publications are identified and discussed in this work. The literature is categorized into four streams, i.e., (1) Supply and procurement, (2) Inventory management, (3) Distribution and scheduling, and (4) Holistic supply chain management. The use of optimization techniques is constantly gaining importance. The number of respective publications has continually grown and has peaked over the last three years. Optimization has been successfully applied in research streams (1), (2), and (3). Category (4) comprises a rather qualitative research field of literature dealing with supply chain management issues.     

Exploring patterns of personal growth initiative and posttraumatic stress: A latent profile analysis

Objective: This study examined the inconsistent relationship found between personal growth initiative (PGI) and posttraumatic stress symptoms (PTSS) by exploring potential subgroups. In addition, after identifying the subgroups, potential predictors of these subgroups were examined. Participants: Participants were 534 undergraduate students who experienced a potentially traumatic event (PTE). Data collection occurred from March 2013 to December 2014. Methods: Because this was a preliminary study, archival data was used. Participants consisted of students who experienced a PTE within the past three years. Results: Latent profile analysis indicated a five-class model as the best-fitting model. Direct exposure and intentionality of the event were significant predictors of class membership; length of time since event and gender did not predict class membership. Conclusions: The current study provides a potential explanation of the inconsistent results between PGI and PTSS and also highlights the importance of acknowledging subgroups when utilizing PGI after a PTE.     

A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

Alarmed: sensory approaches to improving medical alarm systems

Medical alarms sound incessantly, loudly, and dissonantly, contributing to an already noisy ICU and OR soundscape, and ultimately harming both patients and staff. Sometimes triggered in error, the sheer number of alarms distracts health care professionals and results in sensory overload that contributes to hospital staff’s alarm fatigue. In turn, staff become increasingly likely to ignore alarms instead of acting on them. Furthermore, the patients’ sensitivity to alarms disturbs their hospital stay, raises their stress levels, and impedes their recovery process, with sometimes lasting effects. This article considers the sensory effects of hospital alarms and possibilities for redesigning future alarm systems, with the goal of eventually creating a more calming, less stressful, and safer hospital soundscape environment for all.