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This study aimed to adapt existing text-mining techniques and propose a novel topic recognition approach for textual patient reviews.

The authors first transformed multilabel samples for adapting model training forms. Then, an improved method was proposed based on dynamic mixed sampling and transfer learning to improve the learning problem caused by imbalanced samples. Specifically, the training of our model was based on the framework of a convolutional neural network and self-trained Word2Vector on large-scale corpora.

Compared with the SVM and other CNN-based models, the CNN+ DMS + TL model proposed in this study has made significant improvement in F1 score.

The improved methods based on dynamic mixed sampling and transfer learning can adequately manage the learning problem caused by the skewed distribution of samples and achieve the effective and automatic topic recognition of textual patient reviews.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2021-0059.

Although it is widely acknowledged that health care delivery systems are complex adaptive systems, there are gaps in understanding the application of systems engineering approaches to systems analysis and redesign in the health care domain. Commonly employed methods, such as statistical analysis of risk factors and outcomes, are simply not adequate to robustly characterize all system requirements and facilitate reliable design of complex care delivery systems. This is especially apparent in institutional-level systems, such as patient safety programs that must mitigate the risk of infections and other complications that can occur in virtually any setting providing direct and indirect patient care. The case example presented here illustrates the application of various system engineering methods to identify requirements and intervention candidates for a critical patient safety problem known as failure to rescue. Detailed descriptions of the analysis methods and their application are presented along with specific analysis artifacts related to the failure to rescue case study. Given the prevalence of complex systems in health care, this practical and effective approach provides an important example of how systems engineering methods can effectively address the shortcomings in current health care analysis and design, where complex systems are increasingly prevalent.

This paper aims to explore and review the potential of robotic rehabilitation as a treatment approach for Alzheimer’s disease (AD) and its impact on the health and quality of life of AD patients.

The present discourse endeavors to provide a comprehensive overview of extant scholarly inquiries that have examined the salience of inhibitory mechanisms vis-à-vis robotic interventions and their impact on patients with AD. Specifically, this review aims to explicate the contemporary state of affairs in this realm by furnishing a detailed explication of ongoing research endeavors. With the objective of elucidating the significance of inhibitory processes in robotic therapies for individuals with AD, this analysis offers a critical appraisal of extant literature that probes the intersection of cognitive mechanisms and assistive technologies. Through a meticulous analysis of diverse scholarly contributions, this review advances a nuanced understanding of the intricate interplay between inhibitory processes and robotic interventions in the context of AD.

According to the review papers, it appears that implementing robot-assisted rehabilitation can serve as a pragmatic and effective solution for enhancing the well-being and overall quality of life of patients and families engaged with AD. Besides, this new feature in the robotic area is anticipated to have a critical role in the success of this innovative approach.

Due to the nascent nature of this cutting-edge technology and the constrained configuration of the mechanized entity in question, further protracted analysis is imperative to ascertain the advantages and drawbacks of robotic rehabilitation vis-à-vis individuals afflicted with Alzheimer’s ailment.

The potential for robots to serve as indispensable assets in the provision of care for individuals afflicted with AD is significant; however, their efficacy and appropriateness for utilization by caregivers of AD patients must be subjected to further rigorous scrutiny.

This paper reviews the current robotic method and compares the current state of the art for the AD patient.

Failure to rescue events, or events involving preventable deaths from complications, are a significant contributor to inpatient mortality. While many interventions have been designed and implemented over several decades, this patient safety issue remains at the forefront of concern for most hospitals. In the first part of this study, the development and implementation of one type of highly studied and widely adopted rescue intervention, algorithm-based patient assessment tools, is examined. The analysis summarizes how a lack of systems-oriented approaches in the design and implementation of these tools has resulted in suboptimal understanding of patient risk of mortality and complications and the early recognition of patient deterioration. The gaps identified impact several critical aspects of excellent patient care, including information-sharing across care settings, support for the development of shared mental models within care teams, and access to timely and accurate patient information.

This chapter describes the use of several system-oriented design and implementation activities to establish design objectives, model clinical processes and workflows, and create an extensible information system model to maximize the benefits of patient state and risk assessment tools in the inpatient setting. A prototype based on the product of the design activities is discussed along with system-level considerations for implementation. This study also demonstrates the effectiveness and impact of applying systems design principles and practices to real-world clinical applications.

Background: Compliance of patients with self-care practices is the mainstay of measures to manage diabetes. This study explored self-care practices of type 2 diabetes patients receiving insulin treatment in North-East Ethiopia.

Methods: The study employed an interpretive phenomenological approach using purposive sampling. The data were collected from 24 (11 males and 13 females) participants (July 2019 to January 2020) using in-depth interviews till theoretical saturation. The data were analyzed thematically and organized using QDA Miner Lite v2.0.8.

Results: The findings were categorized into: labeling diabetes, self-care maintenance experiences, recognition of symptoms, and mitigating mechanisms. The self-care maintenance practice of patients was linked with diet input preferences and the effectiveness level of insulin. What guides the self-care behavior was the patients’ preferentiality of strictly adhering to their preferred dietary inputs. Barley and wheat were the most common preferential and non-preferential inputs, respectively. The patients strictly adhered to insulin treatment because they found it effective. The most common hyperglycemia symptoms to be managed by taking an additional dose of insulin, were frequent urination, increased thirst, and their consequence (dehydration). Excessive sweating (initial), shivering (middle), and falling (final), respectively in severity, were the most common symptoms of hypoglycemia which were perceived to be treated with sweet snacks.

Originality: To our knowledge, this is the first research in Ethiopia to investigate the self-care experiences of type 2 diabetes patients receiving insulin using an interpretive phenomenological approach.

The changing clinical landscape in psychiatry, both before and after the pandemic, has impacted students’ direct contact with psychiatric patients. It is imperative, therefore, that medical education keeps pace with evolving clinical pathways to ensure that clinicians are always appropriately trained not just for common presentations but also for low-prevalence, high-risk situations. Simulated-based training is well established. However, it is not without its limitations, many of which could be overcome with the use of virtual simulation. This study aims to analyse the use of virtual simulation within medical education to train clinicians in psychiatric assessments.

A scoping review was undertaken with a comprehensive literature search of the six most relevant online peer-reviewed databases, including PubMed, PsycINFO, CINAHL, Medline, EMBASE and Cochrane. All published papers in English that discussed simulation in teaching psychiatric assessments were included.

Virtual patients can be used for educational, diagnostic and therapy purposes attributable to advances in speech-recognition technology. Virtual simulations are well received and positively affect clinicians’ knowledge and skill development. Educational faculties should consider using virtual simulation technologies to improve learning outcomes. Further studies should enhance the fidelity and quality of virtual assessment simulation situations, mainly focusing on the virtual patient’s empathy, gesturing and body language to enable this evidence-based tool to be used effectively and efficiently for the benefit of future patient care.

The changing clinical landscape in psychiatry, both before and after the pandemic, has impacted students’ direct contact with psychiatric patients. This scoping review has reviewed the use of virtual simulation-based education to train clinicians for psychiatric assessments. To the best of the authors’ knowledge, this work has not been conducted before.

The purpose of this chapter is to use sociological theory and research to develop an explanation for how chronic illnesses are managed at home and to thereby suggest some ways in which a sociological perspective can be applied to improve health care for persons with chronic illnesses. Self-care illness management is crucial to the prevention of and reduction of morbidity and mortality from chronic illness.

Review and synthesis of research literature.

Sociological research and theory suggest two important insights that should inform health care services aimed at improving self-care; chronic illness care occurs in the context of the household, neighborhood, and community and, therefore, the “patient” (i.e., the object of health services) is really the caregiving social network around the patient, and because the risk of chronic illness and the resources available to deal with it are socially (and unequally) distributed, “health care” interventions need to take account of disparities in risks and resources that will affect the patient’s ability to successfully comply with self-care regimens.

The review does not include an examination of the clinical research literature. It does, however, suggest that sociologists need to explicitly study chronic illness and health care related to it.

The chapter links the long history of research on family caregiving to the concern with the success of self-management of chronic illness. It also links concerns about that success to social disparities in the distribution of social resources and hence to morbidity and mortality disparities.

In order to succeed in an action under the Equal Pay Act 1970, should the woman and the man be employed by the same employer on like work at the same time or would the woman still be covered by the Act if she were employed on like work in succession to the man? This is the question which had to be solved in Macarthys Ltd v. Smith. Unfortunately it was not. Their Lordships interpreted the relevant section in different ways and since Article 119 of the Treaty of Rome was also subject to different interpretations, the case has been referred to the European Court of Justice.

This paper proposes an integrated approach to examining and dealing with the complex issue of nurse recruitment, retention, healthcare quality and patient satisfaction. The paper depicts and describes a generic conceptual framework or chain derived from a review of the literature on nurse recruitment and retention, service quality and human resource management. The chain is made up of the following components: NHS and Trust conditions and environment (internal quality) –service capability – nurse satisfaction –nurse retention – quality of patient care – patient satisfaction. The value of the chain is derived from its synthesis and display of the prime constituents or drivers of nurse satisfaction, quality of patient care and satisfaction. From this holistic picture it is possible for both national and local initiatives to be integrated in a mutually reinforcing way in order to achieve improvements in nurse recruitment, retention, quality of care and patient satisfaction.