Informatics for Health & Social Care最新文献

This paper presents a model of a smart healthcare service for stress management in dental patients during the interventions. The main goal is to provide dental clinics with a model that enables introducing a stress management service into everyday practice and provides patients with a better experience in a typically stressful situation. The approach is based on employing wearable sensors for monitoring physiological parameters, and a mobile application for progressive muscle relaxation therapy. Dental patients were divided into experimental and control groups. Participants from the experimental group were treated with progressive muscle relaxation through mobile health application with audio content, and patients from the control group were not exposed to any relaxation method. Heart rate was measured in both groups through three test phases: pre-intervention, intervention, and post-intervention. Evaluation of the anxiety level was performed using the STAI test. Results show that the measured heart rate in the post-intervention phase is lower than in the intervention phase in both testing groups, as well as in the pre-intervention phase. STAI scores were significantly higher in the control group through all test phases. The research found that the proposed system applied to dentist patients may relieve their anxiety symptoms and decrease stress level, which improves the patients' experience and leads to higher patients' satisfaction.

The mortality rate of heart disease continues to rise each year: developing mechanisms to reduce mortality from heart disease is a top concern in today's society. Heart sound auscultation is a crucial skill used to detect and diagnose heart disease. In this study, we propose a heart sound signal classification algorithm based on a convolutional neural network. The algorithm is based on heart sound data collected in the clinic and from medical books. The heart sound signals were first preprocessed into a grayscale image of 5 seconds. The training samples were then used to train and optimize the convolutional neural network; obtaining a training result with an accuracy of 95.17% and a loss value of 0.23. Finally, the convolutional neural network was used to test the test set samples. The results showed an accuracy of 94.80%, sensitivity of 94.29%, specificity of 95.54%, precision of 93.44%, F1_score of 93.84%, and an AUC of 0.943. Compared with other algorithms, the accuracy and sensitivity of the algorithms were improved. This shows that the method used in this study can effectively classify heart sound signals and could prove useful in assisting heart sound auscultation.

The main objective of this work is to define a common shared conceptual model that describes the health care environment using the ContSys standard, harmonizing it with the social care and assistive domotics concepts. The development of this model supports the integration of services, the interoperability among systems and the continuity of care across domains.Starting from the identification and extraction of the portion of the ContSys model suitable for the healthcare part, the article provides the methodology adopted to extend it with social and home automation concepts and to integrate them in a unique framework that supports the continuity of care.The integrated model defined in this paper has been adopted in the design phase of an interoperable open platform, called Health@Home, that organizes the provision of a set of health, social and home automation integrated services provided at home.Our model is a starting point to analyze the various determinants of wellbeing able to guarantee a high-level individual's quality of life. At the moment the Health@Home system is at the implementation phase.

The intensive care unit (ICU) is a stressful and complex environment in due to its dynamic nature and severity of admitted patients. EHR interface design can be cumbersome and lead to prolonged times to complete tasks. This paper investigated the relationship between a prominent EHR interface design and interruptions with physician's efficiency during patient chart review at ICU Pre-Rounds. We conducted a live observation of ICU physicians in a 30-bed MICU at a tertiary, southeastern medical center. Directly after the observation sessions, the physicians completed a modified System Usability Scale (SUS) survey. A total of 52 EHR patient chart reviews were observed at the MICU Pre-rounds. There was statistically significant positive correlation between time spent to review patient EHR with both number of scrolling(p-value<0.0001) across EHR interface; and with number of visited EHR  screens (p-value=0.0444). There was positive correlation between number of interruptions with time spent to review patient EHR during ICU prerounds. EHR design and the occurrence of interruptions lead to reduced physician-EHR efficiency levels. We report that the number of scrolling and visited screens executed by physicians to gather the required information was associated with increased screen time and consequently decreased physician efficiency.

To survey the health-seeking behaviors and perspectives of the Egyptian population toward the COVID-19 pandemic. A descriptive survey was designed and disseminated via social media platforms. The survey consisted of 32 questions addressing respondent's demographics, knowledge, practice, and attitude toward the COVID-19 pandemic. A total of 25,994 Egyptians participated in the survey from the 29 Egyptian governorates. More than 99% of the respondents were aware of the COVID-19 pandemic. Responses showed split opinions regarding whether people should wear gloves or masks to prevent COVID-19 infection (47.7% and 49.5% replied with "False", respectively). Almost one-quarter (23.1%) of the respondents went to crowded places during the last 14 days. Calling the emergency hotline and self-isolation at home were the most frequent practices to deal with COVID-19 symptoms (34.1% and 44.5%, respectively). A total of 85% of respondents reported their confidence in the Egyptian healthcare system to win the battle against COVID-19 despite the challenges. A vast majority of this large population sample reported reasonable knowledge levels and potentially appropriate practices toward COVID-19.

The COVID-19 pandemic requires an urgent action to transform health-care delivery and to promote research and capacity-building nursing programs. Specifically, many countries at the global level have described nursing informatics as an essential competence for nurse professionals. In Peru, nursing personnel represents the largest health workforce group and nursing informatics is still emerging, but the field appear to hold much promise. In this sense, the Peruvian Ministry of Health (MoH) defined in 2020 the core nursing competences, which included a technology and innovation domain. The competence established to apply scientifically based technology and innovation to improve the processes or health service resources. The minimum competencies established by the MoH were as follows: to carry out innovations in processes or resources in their different professional performance areas, to creatively adapt technology in different areas of professional performance, to make rational and ethical use of health technologies with focus on new developments that will be evaluated and applied critically, and to manage information and communication technologies, and health information systems, with emphasis on telehealth (i.e. telemedicine, telecare management, tele-education, and tele-training). Besides the nursing competences defined by the MoH is a good starting point, this special contribution discusses the urgent need to strengthen nursing informatics competencies in Peru.

Examining the feasibility of developing an index measure for the social determinants of health using public data is needed. We examined these characteristics at the ZIP code in California and New York using public data extracted from the US Census, American Community Survey, the USDA Food Research Access Atlas, and the Dartmouth Atlas. We conducted a retrospective study from 2000 to 2017. The main outcome was a novel index measure representing six domains (economic stability, neighborhood and physical environment, education, community and social context, food access, and health care) and encompassing 13 items. The index measure at the ZIP code was created using principal component analysis, normalized to "0" worse and "1" better in California (ZIP codes n = 1,447 to 1,515) and New York (ZIP codes n = 1,211 to 1,298). We assessed the reliability and conducted a nonparametric comparison to the Robert Wood Johnson Foundation County Health Rankings, Area Deprivation Index, Social Deprivation Index, and GINI Index. These measures shared similarities and differences with the novel measure. Mapping of this novel measure showed regional variation. As a result, developing a universal social determinants of health measure is feasible and more research is needed to link it to health outcomes.

An early integration of users and stakeholders is needed for a successful innovation process. Nonetheless, the integration of users is often hard to realize - especially when dealing with persons with chronic diseases. In addition, patients or users in general often are not able to formulate the requirements in a technical manner. Therefore, even if user requirements are collected, it is not certain that the developers know or understand 'what is really wanted'. To overcome these 'gaps', we have developed so-called Action Sheets (AS). This article presents the use of AS in two projects: the development of health technologies for people with cancer (INFOPAT) and dementia (QuartrBack). Depending on the project context, group sessions were conducted with different stakeholders to identify the needs of (potential) users. Within the INFOPAT project, ten focus groups were conducted with patients, physicians and other healthcare professionals. In QuartrBack stakeholders like e.g. care professionals, technical assistance organizations and citizens participated in two focus groups and three world cafés. Their requirements were then 'fed' into the technology development by the use of AS. AS appear to be a promising tool to make user needs based on social values more tangible and implementable into technology development processes. In addition, it shows up that four phases seem to be necessary for transferring identified user and stakeholder needs into AS, which can therefore be seen as essential to translate non-technically formulated requirements into technically feasible ones. The case study shows as lessons learned that despite the successful integration of user needs, context-sensitive adjustments are still necessary.

Most maternal and newborn deaths in low-income countries, including Rwanda, are attributable to preventable causes. Timely access to Basic Emergency Obstetric and Newborn Care (BEmONC) guidelines to support clinical decisions could lead to better obstetric care thus reduction of maternal and newborn deaths. Besides, innovative methods such as the usage and reference to healthcare guidelines using mobile devices (mhealth) may support clinical decision making. However, there is little evidence about mhealth that focuses on the clinical decision support process. This proposal aims to investigate the effect of the Safe Delivery mhealth Application(SDA) on nurses' and midwives' clinical decision making, so as to inform mhealth interventions for work in specific contexts. The study adopts a quasi-experimental design. Convergent parallel mixed - methods will be used to collect, analyze and interpret data. A pre-intervention assessment of the BEmONC outcomes: Apgar score and PPH progressions, and related knowledge, skills, and perceptions of nurses and midwives will be conducted. The intervention will take place in two district hospitals in Rwanda and entails the implementation of the SDA for six months. Six months' post-intervention, the effect of the SDA on BEmONC outcomes and the nurses' and midwives' knowledge and skills will be evaluated.