Investigating the Correlation between Patient Education on Web-Based Portal Functionality and the Reduction in 30-Day Hospital Readmission Rates

Background: The growing use of web-based patient portals offers patients valuable tools for accessing health information, communicating with healthcare providers, and engaging in self-management. However, the influence of educating patients on these portals’ functionality on clinical outcomes, such as all-cause readmission rates, remains underexplored. Objective: This research proposal tested the hypothesis that educating a subset of patients with Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF), on how to effectively access and utilize the functionality of web-based patient portals can reduce all-cause readmission rates. Methods: We performed a prospective, quasi-experimental study at Bon Secours St. Mary’s Hospital in Richmond, Virginia, USA;dividing participants into an intervention group, receiving education about accessing and navigating “My Chart”, the Bon Secours Web based portal, and a control group, receiving standard care. We then compared 30-day readmission rates, patient engagement, and self-management behaviors between the groups. Data was analyzed using statistical tests to assess the intervention’s impact. Results: We projected that educated patients will exhibit lower readmission rates, improved engagement, and better self-management. The results of the study showed that there was a significant decrease in 30-day readmissions in the intervention group in comparison with the control group (22.7% and 40.9%, respectively). This reduction of 18. 2% of readmissions evaluated here for a trial of meaningful clinical effect is statistically insignificant (p = 0. 184). The practical significance of the intervention is considered small-to-moderate (Cramer V = 0. 20) suggesting that the observed difference has a potential clinical importance even though the difference was not statistically significant. Conclusion: These results imply that the proposed educational intervention might have a positive impact on readmissions;nonetheless, the patient’s characteristics that make him or her capable of readmission cannot be changed and are assessed by the RoR (Risk of Readmission) score. The potential impact of the intervention may be offset, in part, by these baseline risk factors. The study’s power may be limited by sample size, potentially affecting the detection of significant differences. Future studies with larger, multi-center samples and longer follow-up periods are recommended to confirm these findings.

Orthopaedic care provided by the 14th combat support hospital in support of humanitarian and disaster relief after hurricane Maria in Puerto Rico

On September 20,2017 Hurricane Maria,a category 4 hurricane,made landfall on the eastern coast of Puerto Rico.This was preceded by Hurricane Irma,a category 5 hurricane,which passed just off the coast 13 d prior.The destruction from both Hurricane Irma and Maria precipitated a coordinated federal response which included the Federal Emergency Management Agency(FEMA)and the United States military.The United States Army dispatched the 14^th Combat Support Hospital(CSH)to Humacao,a city on the eastern side of the island where Maria made landfall.The mission of the 14^th CSH was to provide medical humanitarian aid and conduct disaster relief operations in support of the government of Puerto Rico and FEMA.During the 14^th CSH deployment to Puerto Rico,1157 patients were evaluated and treated.Fifty-seven operative cases were performed to include 23 orthopaedic cases.The mean age of the orthopaedic patients treated was 45.7 years(range 13-76 years).The most common operation was irrigation and debridement of open contaminated and/or infected wounds.Patients presented a mean 10.8 d from their initial injury(range 1-40 d).Fractures and infections were the most common diagnoses with the greatest delay in treatment from the initial date of injury.The deployment of the 14^th CSH to Puerto Rico was unique in its use of air transport,language and local customs encountered,as well as deployment to a location outside the continental United States.These factors coupled with the need for rapid deployment of the 14^th CSH provided valuable experience which will undoubtedly enable future success in similar endeavors.

A Study on the Explainability of Thyroid Cancer Prediction:SHAP Values and Association-Rule Based Feature Integration Framework

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable progress.Accurate predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce overtreatment.However,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency.This paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present state-of-the-artmodels.Our study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction models.In the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the dataset.The original dataset is used in trainingmachine learning models,and further used in generating SHAP values fromthesemodels.In the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based analysis.This new integrated dataset is used in re-training the machine learning models.The new SHAP values generated from these models help in validating the contributions of feature sets in predicting malignancy.The conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making systems.In this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the predictions.The study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of explainability.The proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area under the receiver operating characteristic(AUROC)are also higher than the baseline models.The results of the proposed model help us identify the dominant feature sets that impact thyroid cancer classification and prediction.The features{calcification}and{shape}consistently emerged as the top-ranked features associated with thyroid malignancy,in both association-rule based interestingnessmetric values and SHAPmethods.The paper highlights the potential of the rule-based integrated models with SHAP in bridging the gap between the machine learning predictions and the interpretability of this prediction which is required for real-world medical applications.

Support effect of the supported ceria-based catalysts during NH_3-SCR reaction

To investigate how the physicochemical properties and NH3‐selective catalytic reduction(NH3‐SCR)performance of supported ceria‐based catalysts are influenced as a function of support type,a series of CeO2/SiO2,CeO2/γ‐Al2O3,CeO2/ZrO2,and CeO2/TiO2catalysts were prepared.The physicochemical properties were probed by means of X‐ray diffraction,Raman spectroscopy,Brunauer‐Emmett‐Teller surface area measurements,X‐ray photoelectron spectroscopy,H2‐temperature programmed reduction,and NH3‐temperature programmed desorption.Furthermore,the supported ceria‐based catalysts'catalytic performance and H2O+SO2tolerance were evaluated by the NH3‐SCR model reaction.The results indicate that out of the supported ceria‐based catalysts studied,the CeO2/γ‐Al2O3catalyst exhibits the highest catalytic activity as a result of having a high relative Ce3+/Ce4+ratio,optimum reduction behavior,and the largest total acid site concentration.Finally,the CeO2/γ‐Al2O3catalyst also presents excellent H2O+SO2tolerance during the NH3‐SCR process.

Is There an Improvement in Patient Survival/Code Blue Activation after Training Based on Simulation (Basic Life Support—BLS) Based Practice of Cardiopulmonary Resuscitation?

Background and Aim: The only way to survive a sudden cardiac arrest is when the CPR is performed immediately after the arrest. The focus of the present research study is to assess the effectiveness of a pre- and post-simulation-based BLS training (BLS) and the outcome was measured on the basis of patient survival after the cardiac arrest. Study Design: This pre- and post-training BLS/CPR training study enrolled all nursing staff, all hospital residents, internees, throughout the hospital in a simulation-based BLS training as per the standards of American Heart Association (AHA), to make them respond to immediate resuscitation and code blue activation during the cardiac arrest within the hospital premises including ED, wards, ICUs, MRI, CT and all miscellaneous areas. The providers completed self-efficacy questionnaires as per the AHA protocol before being certified and were evaluated during the emergency in hospital cardiopulmonary arrest. Results: 296 nursing staff, 206 non-healthcare professionals, 143 residents, 212 internees, and 98 medical staff grade doctors completed the BLS training (total 955 hospital staff—providers) were graded for the response by pre- and post-training testing. In the course of pre-BLS training period out of the 250 cardiac arrest patients, 68 patients (27.2%) had ROSC, while after instituting the BLS training period, 143 individuals (40.86%) of the 350 patients who had cardiac arrest had ROSC (p < 0.05). Conclusion: A simulation-based CPR and BLS training curriculum greatly improves patient outcome by reducing mortality and morbidity with improved subjectivity, self-efficiency along with the objective assessment of the performance scores during acute cardiac arrest in Emergency Cardiovascular Care (ECC).

Internet-Based Support and Coaching for Adolescents and Young Adults with Neuropsychiatric Disorders—The Implementation of an Intervention from an Organizational Perspective

There is a documented and often unmet need for interventions aimed at supporting young people with attention-deficit/hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) in their transition between adolescence and adulthood. Difficulties with social interaction, initiation difficulties, and impairments in executive function can complicate visits at a clinic, i.e. traditional treatment, for individuals with neuropsychiatric disorders (NPD). A model for internet-based support and coaching aimed at young people with ASD and/or ADHD was developed and tested at three treatment sites in western Sweden. The implementation was analyzed against an inventory according to which implementations are more likely to be successful if an intervention: 1) has advantages compared to other existing methods, 2) matches the individual and organizational values, norms and work practices of its recipients, 3) is perceived as easy to use, and 4) is adaptable to local conditions and the recipients’ needs. Data were collected through group interviews with professionals involved in the implementation of the intervention. The implementation of the intervention showed promising results on measures such as access, delivery/quality of healthcare services, and equality of distribution of healthcare services. The identified impediments to successful implementation related to a wide range of factors and levels, including the design of the intervention, technical issues, attitudes of staff, organizational culture, and organizational structure at the implementation sites in terms of patient stock, work division, and resource allocation. The results are consistent with previous studies that stress the need for multi-component implementation strategies.

Exploring the Multivariate Relationships between Adolescent Depression and Social Support, Religiosity, and Spirituality in a Faith-Based High School

Depression is one of the most common psychological disorders that affect adolescents. In this study, we investigated how depression in adolescents relates to social support, religiosity, and spirituality in multivariate analyses. We also investigated whether age, gender and ethnicity are predictors of depression among adolescents in a faith-based high school. We measured social support using the Child and Adolescent Social Support Scale (CASSS), religiosity with the Duke University Religion Index (DUREL);spirituality with the Spiritual Well-Being Scale (SWBS);and depression with the Center for Epidemiological Studies Depression Scale for Children (CES-DC). Results of the bivariate analyses showed a significant negative association between depression and social support, religiosity, and spirituality (p –0.548, p = 0.00) was negatively related to depression in adolescents. The study found significant gender differences only in religiosity, while significant ethnic differences were only found in social support. Implications to education, practice, research and future directions of study are discussed.

Rate of Inappropriate Imaging Utilization by the Emergency Department in Community Hospitals

Objective: To retrospectively analyse the use of imaging studies in the Emergency Department of community hospitals using evidence based guidelines and clinical judgement. Methods: Medical records of 661 patients who visited the Emergency Department (ED) in 2015 and underwent imaging studies were reviewed. The Canadian Association of Radiologists, American College of Radiologists and Choosing Wisely Canada guidelines were used to determine the appropriateness of imaging studies. The use of prior patient imaging, the rate at which studies were repeated and the respective impacts on patient management of the imaging studies were also examined. Results: Of the 1056 imaging studies reviewed, 228 (22%) were found to be clinical situations where no imaging study was indicated while 168 (16%) were considered a suboptimal choice of imaging study or modality. When no study was recommended, a positive impact on the diagnosis was noted in 105 (46%) cases and on patient management 83 (36%) times. Notably, 219 (21%) patients had a relevant examination performed in the last 30 days, and 147 (14%) reports noted that the results of the prior study also concurred with the imaging study evaluated. Conclusion: In this study, 228 (22%) radiographs and CT studies, excluding MVC related imaging and extremity imaging, were not indicated based on appropriateness criteria and consequently had a limited impact on patient management. This supports the need for increased clinical decision support for ED physicians, regional health information exchanges and consideration of Computerized Physician Order Entry in the ED with embedded appropriateness criteria at the point of ordering.

Evaluation of the Performance of Financial Support for Agriculture in Guizhou Province Using Secondary Relative Benefit Model Based on DEA

We use the secondary relative benefit model based on DEA to evaluate the performance of agricultural financial expenditure in Guizhou Province, which can give due consideration to the production effectiveness determined by objective natural conditions, and management effectiveness of all regions (as decision-making body) in the use of financial fund for supporting agriculture. In general, there is north-south gradient difference in the performance of financial support for agriculture between regions in Guizhou Province. The drought in 2010 has significant impact on the technical efficiency in the whole province; the performance score of each item in Liupanshui City and Southwest Guizhou is very low; the technical efficiency and management efficiency in most regions need to be improved. In order to improve the performance of financial support for agriculture, we need to ensure the scale of input; at the same time, provide appropriate preferential financial policies for agricultural infrastructure, especially the construction of rural water conservancy, development and promotion of agricultural science and technology, and other fields; adopt the way of special check and acceptance of supporting projects to strengthen the use management of the fund for agriculture.

Multimode Process Monitoring Based on the Density-Based Support Vector Data Description

Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the mode.To solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.

Construction and realization of the knowledge base and inference engine of an IDSS model for air-conditioning cooling/heating sources selection

The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.

Intensify standardized therapy for esophageal and stomach cancer in tumor hospitals

INTRODUCTIONCancer treatment situation in tumor hospitals inChina has its own unique characteristics which arenot found in other parts of the world. Because ofthe huge population and high incidence rates ofesophageal and stomach cancer[1-5], the number ofcancer patients waiting for admission isinconceivably large.

Inspiration of the functional localization of a US naval hospital ship on a Chinese hospital ship

Through the experience of being stationed on the USS Mercy hospital ship(T-AH19) and a preliminary comprehension of the personnel and material arrangements,processing and functional formats,and the multi-platform contributions of US Navy hospital ships,we briefly introduce the characteristics of US hospital ships regarding medical support,emergency rescue exercises,communications and training,international humanitarian aid,etc.We discuss the function and responsibility of Chinese hospital ships,focusing on the investigation of the construction mode and positioning in the navy.

Gas-phase dehydrochlorination of 1, 1, 2, 2-tetrachloroethane over the non-metal supported ionic liquid catalyst

Developing of non-metallic catalyst to replace metal catalyst is a meaningful and challenging direction.In this work,the non-metallic catalyst was synthetized successfully by loading ionic liquid onto the silica surface,which was applied for the gas-phase dehydrochlorination of 1,1,2,2-tetrachloroethane.The 12%TPPC/SiO2(wt%)showed the best results with the conversion of 1,1,2,2-tetrachloroethane reaching 100%.The selectivity of 1,1,2-trichloroethylene was 100%,and no deactivation was found during the evaluation period.The catalytic mechanism was investigated and possible reaction route was given,which was a reference for fabricating and design of solid base catalyst.

Mathematical methods for main tenance and operation cost prediction based on transfer learning in State Grid

The electric power enterprise is an important basic energy industry for national development,and it is also the first basic industry of the national economy.With the continuous expansion of State Grid,the progressively complex operating conditions,and the increasing scope and frequency of data collection,how to make reasonable use of electrical big data,improve utilization,and provide a theoretical basis for the reliability of State Grid operation,has become a new research hot spot.Since electrical data has the characteristics of large volume,multiple types,low-value density,and fast processing speed,it is a challenge to mine and analyze it deeply,extract valuable information efficiently,and serve for the actual problem.According to the features of these data,this paper uses artificial intelligence methods such as time series and support vector regression to establish a data mining network model for standard cost prediction through transfer learning.The experimental results show that the model in this paper obtains better prediction results on a small sample data set,which verifies the feasibility of the deep transfer model.Compared with activity-based costing and the traditional prediction method,the average absolute error of the proposed method is reduced by 10%,which is effective and superior.

Representation Form of“Treating Employees as Customers”in the Hospitality Organization:The Case of Hoshino Resorts

“Treating employees as customers”is known as the core concept of internal marketing.In particular,it was born and developed for hospitality organizations.However,no specific method has been represented so far.In the previous research(Hashimoto,2018a;2018b;2019),it was verified the concrete method based on the core concept of internal marketing,“Treating employees as customers”.There are career support,mental support,and dialogue.In this paper,it is verified whether the concepts of these three methods are represented in the hospitality organization through interviewing staff of Japanese hotel company that is continuing to grow rapidly.As a result of the consideration,it is confirmed that the concepts of the three methods are certainly represented in the organization.It will provide new point of view for concrete methods of Internal Marketing that have not been shown so far.Hope that this paper will facilitate research on hospitality organizations such as hotels,which is not so considered in Japan.

Keystroke Dynamics Based Authentication Using Information Sets

This paper presents keystroke dynamics based authentication system using the information set concept. Two types of membership functions (MFs) are computed: one based on the timing features of all the samples and another based on the timing features of a single sample. These MFs lead to two types of information components (spatial and temporal) which are concatenated and modified to produce different feature types. Two Component Information Set (TCIS) is proposed for keystroke dynamics based user authentication. The keystroke features are converted into TCIS features which are then classified by SVM, Random Forest and proposed Convex Entropy Based Hanman Classifier. The TCIS features are capable of representing the spatial and temporal uncertainties. The performance of the proposed features is tested on CMU benchmark dataset in terms of error rates (FAR, FRR, EER) and accuracy of the features. In addition, the proposed features are also tested on Android Touch screen based Mobile Keystroke Dataset. The TCIS features improve the performance and give lower error rates and better accuracy than that of the existing features in literature.

The Concept of Information Support for Bi-oresource and Ecosystem Research in the North-West Pacific: Theory and Practical Implementation

The first part of the article provides an overview of the theoretical evidence, the main provisions, and the implementation strategy of information support for bioresource and ecosystem research in the north-west Pacific, which has been conducted over the past 20 years in the Russian Far East Research Institute TINRO-Center. In short, the concept consists of a combination of the following four assertions: 1) For the steady and sustainable development of the Russian Far East, the entire Russian Federation and the Asia-Pacific Region in general, environmental, food, economic, and other security is required, which cannot be achieved without the rational use of bioresources based on the ecosystem approach to the management of aquatic bioresources. 2) For the inventory, appraisal, monitoring, forecasting of the state of and management the natural water resources when applying this approach, statistically relevant quantitative information is required on the greatest possible number of constituents of marine biocenosis of the north-western Pacific for the longest possible period of time, which is only available at the TINRO-Center. 3) This valuable data should be organized into databases, based on which geo-information and other electronic information systems are prepared, and based on these map atlases and reference books on natural water resources, using automated workplaces created especially for this. 4) The resulting unique information support will be of great value not only for practical purposes, but also for science, both applied and fundamental. Next comes a summary of the many years of work on the practical implementation of this concept and the key achievements in this field obtained by the TINRO-Center by the end of 2015 are reviewed. At the end, some plans for the near future are outlined.

Electronic market models for decision support systems on the Web

With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). We propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS, and the conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS operate efficiently.

Use of Solid-Supported Reagents towards Synthesis of 2-Arylbenzoxazole, 3, 5-Diarylisoxazole and 1, 3, 5-Triarylpyrazole

Herein we report a convenient and efficient synthesis of 2-Arylbenzoxazole from the Schiff’s bases of 2-Aminophenol, 3, 5-Diarylisoxazole from α, β-unsaturated ketoxime and 1,3,5-Triarylpyrazole from 2-pyrazoline and N-Arylhydrazone by using milder, less toxic and less expensive-NBS-SiO2, KMnO4-Al2O3, PCC-SiO2 and ACC-Al2O3 as solid-supported oxidizing agents at room temperature. Within the framework of Green Chemistry, the use of solid supported reagents has many advantages such as 1) they are easy to remove from reactions by filtration 2) excess reagents can be used to drive the reaction without introducing any difficulties in purification 3) such solid-supported reagents react differently, mostly more selectively, than their unbound counterparts and 4) toxic, noxious and explosive chemicals are handled more safely when contained on solid support.