Hubungan Mutu Pelayanan Keperawatan Dengan Kepuasan Pasien Di Instalasi Rawat Inap RSUD Tugurejo Semarang

Pengukuran kepuasan pelanggan merupakan elemen penting dalam menyediakan pelayanan yang lebih baik, lebih efisien dan lebih efektif. Apabila pelanggan merasa tidak puas terhadap suatu pelayanan yang disediakan, maka pelayanan tersebut dapat dipastikan tidak efektif dan tidak efisien. Hal ini terutama sangat penting bagi pelayanan publik. Penyelenggaraan pelayanan kepada masyarakat sebagai mana yang dilakukan RSUD Tugurejo Semarang, perlu mendapatkan perhatian, khususnya dalam kualitas pelayanan agar sesuai dengan kebutuhan dan harapan masyarakat. Penelitian ini memfokuskan pada mutu pelayanan keperawatan dan kepuasan pasien di Instlasi Rawat Inap RSUD Tugurejo Semaranag. Penelitian ini bertujuan untuk  mengetahui  hubungan antara mutu pelayanan dengan kepuasan pasien di Instlasi Rawat Inap RSUD Tugurejo Semaranag. Penelitian ini menggunakan jenis penelitian survei analitik dengan pendekatan cross sectional, sedangkan analisis data yang digunakan adalah uji statistik korelasi Rank Spearman.Populasi dalam penelitian ini adalah pasien yang dirawat di Instalasi Rawat Inap  RSUD Tugurejo Semarang dalam satu bulan yaitu  1200 pasien yang dirawat di kelas I, II, III, dan VIP. Adapun jumlah sampel 100 responden dengan cara pengambilan sampel Stratified Random Sampling. Hasil penelitian didapatkan bahwa mutu pelayanan keperawatan di Intalasi rawat Inap RSUD Tugurejo Semarang kategori tinggi adalah 57 responden (57 %), kategori sedang 41 responden (41 %) dan kategori rendah (2 %). Kepuasan responden di Instalasi Rawat Inap RSUD Tugurejo Semarang kategori tinggi adalah 38 responden ( 38 % ) dan kategori sedang 62 responden ( 62 % ). Kesimpilanya adalah Ada hubungan ( r = 0,293 )   antara mutu pelayanan keperawatan dengan kepuasan pasien, dimana semakin tinggi mutu pelayanan keperawatan maka semakin tinggi pula kepuasan pasien

From Things to Services: A Social IoT Approach for Tourist Service Management

In the context of Internet of Things (IoT), the cooperation and synergy between varied and disparate communicating objects is strained by trustworthiness, confidentiality and interoperability concerns. These restrictions can limit the development of IoT-based applications especially considering the emergent boost in the number of communicating objects and their growing itinerant nature in a collective service context. A new perspective arises with the paradigm of Social Internet of Things (SIoT), that relies on the implementation of semi-independent communicating objects with cooperation assessed by social relations and social feed-back. In this article, we present the development and expansion of the IoT concept towards SIoT in the context of the interactions between tourist services as communicating objects. As a proof-of-concept we propose a composition of services as virtualized social objects and the interaction between them, by taking into consideration the balance, trustworthiness, cooperation and synergy of services. Furthermore we present a solution to integrate also accessibility in SIoT services. The presented concept is presented using a demonstrator build for tourist services

Perceptions of Assistant Principals’ and Principals’ of Bahrain Government Schools about the Impact of the Bahrain Teachers College Educational Leadership Program on Their Performance

This article examines the perceptions of school assistant principals and principals who completed the Bahrain Teachers College higher diploma of education leadership program about its impact on their performance. The study sample consisted of 141 program graduates from 9- cohorts. A multilevel concept in measuring the impact of the educational leadership program on the graduates’ performance was employed. The framework consisted of 4 levels: self-learning, changing others, embedding changes in school practices and sustainability of change and scaling up the school performance. The study questionnaire was designed on the basis of this framework. Results show that the Educational Leadership program positively affected its graduates’ performance in the 4 levels. The majority of the program graduates agreed that the program positively affected their personal qualities, leadership styles and practices to support school development, school staff, students’ performance and school ranking. The majority of the program graduates also agreed that the program positively affected their skills in dealing with curriculum innovations, professional development, research, strategic planning, staff appraisal, communication with community, using ICT, improving students’ learning and applying educational ethics.     Keywords: Education Leadership, School Principals’ Performance, Leadership Styles, School Practices, Leadership Skill

Numerical Investigation on the Performance of an External Compression Supersonic Air Intake Using By-Pass Technique

Two-dimensional, supersonic flow field computation with by-pass holes has been conducted using Euler equation. An algorithm based on finite difference McCormack's technique is used to solve the subsonic-supersonic flow problem with and without by-passing. Trials on by-pass locations were also made. Operation without bypass shows the movement of the normal shock wave upstream which refers to an off-design operating regime. At a distance of 1.271 m measured from the cowl lip, the region of normal shock wave was localized near the throat which approximately represents the on-design perform 0ance condition (cells 8-9). When the flow is bypassed from the rear passages, the normal shock wave is sucked inside the flow passage save poor performance. Results show that by-passing provides a fast reaction to maintain a steady performance which meets the requirements of on-design operation. The Mach number variation corresponding to each case is presented. Results show that the tendency to unity Mach number near the cowl lip sector can be achieved using by-pass expelled. The influence of by-pass on the total pressure recovery and relative pressure is also discussed

Many-body effects in van der Waals-Casimir interaction between graphene layers

Van der Waals-Casimir dispersion interactions between two apposed graphene layers, a graphene layer and a substrate, and in a multilamellar graphene system are analyzed within the framework of the Lifshitz theory. This formulation hinges on a known form of the dielectric response function of an undoped or doped graphene sheet, assumed to be of a random phase approximation form. In the geometry of two apposed layers the separation dependence of the van der Waals-Casimir interaction for both types of graphene sheets is determined and compared with some well known limiting cases. In a multilamellar array the many-body effects are quantified and shown to increase the magnitude of the van der Waals-Casimir interactions.Comment: 13 pages, 13 figure

Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial

Microsimulation models are becoming increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. R is a programming language that has gained recognition within the field of decision modeling. It has the capacity to perform microsimulation models more efficiently than software commonly used for decision modeling, incorporate statistical analyses within decision models, and produce more transparent models and reproducible results. However, no clear guidance for the implementation of microsimulation models in R exists. In this tutorial, we provide a step-by-step guide to build microsimulation models in R and illustrate the use of this guide on a simple, but transferable, hypothetical decision problem. We guide the reader through the necessary steps and provide generic R code that is flexible and can be adapted for other models. We also show how this code can be extended to address more complex model structures and provide an efficient microsimulation approach that relies on vectorization solutions

A Multidimensional Array Representation of State-Transition Model Dynamics

Cost-effectiveness analyses often rely on cohort state-transition models (cSTMs). The cohort trace is the primary outcome of cSTMs, which captures the proportion of the cohort in each health state over time (state occupancy). However, the cohort trace is an aggregated measure that does not capture information about the specific transitions among health states (transition dynamics). In practice, these transition dynamics are crucial in many applications, such as incorporating transition rewards or computing various epidemiological outcomes that could be used for model calibration and validation (e.g., disease incidence and lifetime risk). In this article, we propose an alternative approach to compute and store cSTMs outcomes that capture both state occupancy and transition dynamics. This approach produces a multidimensional array from which both the state occupancy and the transition dynamics can be recovered. We highlight the advantages of the multidimensional array over the traditional cohort trace and provide potential applications of the proposed approach with an example coded in R to facilitate the implementation of our method

A Need for Change! A Coding Framework for Improving Transparency in Decision Modeling

The use of open-source programming languages, such as R, in health decision sciences is growing and has the potential to facilitate model transparency, reproducibility, and shareability. However, realizing this potential can be challenging. Models are complex and primarily built to answer a research question, with model sharing and transparency relegated to being secondary goals. Consequently, code is often neither well documented nor systematically organized in a comprehensible and shareable approach. Moreover, many decision modelers are not formally trained in computer programming and may lack good coding practices, further compounding the problem of model transparency. To address these challenges, we propose a high-level framework for model-based decision and cost-effectiveness analyses (CEA) in R. The proposed framework consists of a conceptual, modular structure and coding recommendations for the implementation of model-based decision analyses in R. This framework defines a set of common decision model elements divided into five components: (1) model inputs, (2) decision model implementation, (3) model calibration, (4) model validation, and (5) analysis. The first four components form the model development phase. The analysis component is the application of the fully developed decision model to answer the policy or the research question of interest, assess decision uncertainty, and/or to determine the value of future research through value of information (VOI) analysis. In this framework, we also make recommendations for good coding practices specific to decision modeling, such as file organization and variable naming conventions. We showcase the framework through a fully functional, testbed decision model, which is hosted on GitHub for free download and easy adaptation to other applications. The use of this framework in decision modeling will improve code readability and model sharing, paving the way to an ideal, open-source world

Computing the Expected Value of Sample Information Efficiently: Practical Guidance and Recommendations for Four Model-Based Methods

Value of information (VOI) analyses can help policy makers make informed decisions about whether to conduct and how to design future studies. Historically a computationally expensive method to compute the expected value of sample information (EVSI) restricted the use of VOI to simple decision models and study designs. Recently, 4 EVSI approximation methods have made such analyses more feasible and accessible. Members of the Collaborative Network for Value of Information (ConVOI) compared the inputs, the analyst's expertise and skills, and the software required for the 4 recently developed EVSI approximation methods. Our report provides practical guidance and recommendations to help inform the choice between the 4 efficient EVSI estimation methods. More specifically, this report provides: (1) a step-by-step guide to the methods' use, (2) the expertise and skills required to implement the methods, and (3) method recommendations based on the features of decision-analytic problems