The Internet of Things in Geriatric Healthcare

Initial evaluation of a technologyenabled change in delivery of the dementia service during COVID-19 in North Warwickshire

BACKGROUND

Remote monitoring technologies show potential to help health professionals deliver preventative interventions which can avoid hospital admissions and allow patients to remain in a home setting.

AIMS

To assess whether an Internet of Things (IoT) driven remote monitoring technology, used in the care pathway of community dementia patients in North Warwickshire improved access to care for patients and cost effectiveness.

METHOD

Patient level changes to anonymised retrospective healthcare utilisation data were analysed alongside costs.

RESULTS

Urgent care decreased following use of an IoT driven remote monitoring technology; one preventative intervention avoided an average of three urgent interventions. A Chi-Square test showing this change as significant. Estimates show annualised service activity avoidance of £201,583 for the cohort; £8764 per patient.

CONCLUSIONS

IoT driven remote monitoring had a positive impact on health utilisation and cost avoidance. Future expansion of the cohort will allow for validation of the results and consider the impact of the technology on patient health outcomes and staff workflows.

Evaluation of health factors on artificial intelligence and the internet of things-based older adults healthcare programmes

Objective

This study evaluates Artificial intelligence and the Internet of Things-based older adults' healthcare programmes (AI·IoT-OAHPs), which offer non-face-to-face and face-to-face health management to older adults for health promotion.

Methods

The study involved 146 participants, adults over 60 who had registered in AI·IoT-OAHPs. This study assessed the health factors as the outcome of pre- and post-health screening and health management through AI·IoT-OAHPs for six months.

Results

Preand post-health screening and management through AI·IoT-OAHPs were evaluated as significant outcomes in 14 health factors. Notably, the benefits of post-cognitive function showed a twofold increase in older female adults through AI·IoT-OAHPs. Adults over 70 showed a fourfold increase in post-walking days, a threefold in post-dietary practice, and a twofold in post-cognitive function in the post-effects compared with pre via AI·IoT-OAHPs.

Conclusions

AI·IoT-OAHPs seem to be an effective program in the realm of face-to-face and non-face-to-face AI·IoT-based older adults' healthcare initiatives in the era of COVID-19. Consequently, the study suggests that AI·IoT-OAHPs contribute to the upgrade in health promotion of older adults. In future studies, the effectiveness of AI·IoT-OAHPs can be evaluated as a continuous project every year in the short term and every two years in the long term.

Virtual Pain Unit Is Associated with Improvement of Postoperative Analgesia Quality: A Retrospective Single-Center Clinical Study

INTRODUCTION

Acute postoperative pain is a major concern among surgical patients. Thus, this study established a new acute pain management model and compared the effects of the acute pain service (APS) model in 2020 and the virtual pain unit (VPU) model in 2021 on postoperative analgesia quality.

METHODS

This retrospective, single-center clinical study involved 21,281 patients from 2020 to 2021. First, the patients were grouped on the basis of their pain management model (APS and VPU). The incidence of moderate to severe postoperative pain (MSPP) [numeric rating scale (NRS) score ≥ 5], postoperative nausea and vomiting (PONV), and postoperative dizziness were recorded.

RESULTS

The VPU group recorded significantly lower MSPP incidence (1-12 months), PONV, and postoperative dizziness (1-10 months and 12 months) compared with the APS group. In addition, the annual average incidence of MSPP, PONV, and postoperative dizziness in the VPU group was significantly lower than in the APS group.

CONCLUSIONS

The VPU model reduces the incidence of moderate to severe postoperative pain, nausea, vomiting, and dizziness; hence, it is a promising acute pain management model.

The metaverse in medicine

The metaverse is an alternative digital world, accessed by means of dedicated audiovisual devices. In this parallel world, various forms of artificial intelligence meet, including individuals in the form of digital copies of real people (avatars), able to interact socially. Metaverse in medicine may be used in many different ways. The possibility to perform surgery at a distance of thousands of miles separating the patient from the surgeon, who could have also the possibility to visualize in real-time patient's clinical data, including diagnostic images, obviously is very appealing. It would be also possible to perform medical treatments and to adopt pharmacological protocols on human avatars clinically similar to the patients, thus observing treatment effects in advance and significantly reducing the clinical trials duration. Metaverse may reveal an exceptional educational tool, offering the possibility of interactive digital lessons, allowing to dissect and to study an anatomical apparatus in detail, to navigate within it, not only to study, but also to see the evolution of the pathological process, and to simulate in advance surgical or medical procedures on virtual patients. However, while artificial intelligence is now an established reality in the clinical practice, the metaverse is still in its initial stages, and to figure out its potential usefulness and reliability, further developments are expected.

Cross-disciplinary training of nursing informatics and nursing engineering at the postgraduate level: A feasibility analysis based on the qualitative method

BACKGROUND

The trend of interdisciplinary education is becoming increasingly prominent. Nursing informatics and nursing engineering have received much attention and development at different levels of nursing education in many Western countries. Meanwhile, in China, the cultivation of interdisciplinary nursing talents has either not been initiated or has only entered an initial stage.

OBJECTIVES

This study aims to explore experts' opinions from nursing, informatics and engineering on the feasibility of interdisciplinary education at graduate master's level in nursing through interview.

DESIGN

This was a descriptive qualitative study.

SETTING

Interviews were conducted online or face to face.

PARTICIPANTS

Experts in the fields of nursing, informatics, and engineering who met the study qualifications were enrolled.

METHODS

This study used a purposive sampling method and collected data via semi-structured interviews. A total of 14 experts were involved based on data saturation, which eight were interviewed face-to-face and six were interviewed online. A content analysis method was used to summarize and analyze the attitudes, opinions, and suggestions of experts.

RESULTS

A total of 579 min of interviews with 66,387 words were transcribed and analyzed after 30-50 min time range of each interview, and 4 themes were established. A consensus was obtained on the necessity and importance of interdisciplinary education. Policy guidance, financial support, and mutual recognition were the prerequisites for the cultivation. Moreover, feasibility of interdisciplinary education depends on multi-cooperation, including society, university, and hospital. Finally, a linkage mechanism among relevant stakeholders was required.

CONCLUSION

The necessity and feasibility of such integrated training was concluded. Learning from the experience of relevant countries, China should launch an interdisciplinary training model suitable for its national condition.

[Keyword Network Analysis and Topic Modeling of News Articles Related to Artificial Intelligence and Nursing]

PURPOSE

The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing.

METHODS

After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4.

RESULTS

As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were 'education,' 'medical robot,' and 'fourth industry.' Five topics were derived from news articles related to artificial intelligence and nursing: 'Artificial intelligence nursing research and development in the health and medical field,' 'Education using artificial intelligence for children and youth care,' 'Nursing robot for older adults care,' 'Community care policy and artificial intelligence,' and 'Smart care technology in an aging society.'

CONCLUSION

The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.

Implementation of an integrated home internet of things system for vulnerable older adults using a frailty-centered approach

Although integrated home internet of things (IoT) services can be beneficial, especially for vulnerable older adults, the hurdle of usability hinders implementation of the technology. This study aimed to evaluate the practical usability of home IoT services in older adults, by frailty status, and to determine the potential obstacles. From August 2019 to July 2020, we randomly selected 20 vulnerable older adults (prefrailty group [n = 11], and frailty group [n = 9]) who had already been identified as needing home IoT services in a community-based prospective cohort study, the Aging Study of the Pyeongchang Rural Area. Integrated home IoT services were provided for 1 year, and a face-to-face survey evaluating usability and satisfaction of each service was conducted. The usability of the integrated home IoT services declined gradually throughout the study. However, prefrail participants showed higher usability than frail older adults (difference-in-difference = - 19.431, p = 0.012). According to the frailty status, the change in usability for each service type also showed a different pattern. During the 12-month study period, the service with the highest satisfaction converged from various service needs to light control by remote control (77.8%) in the prefrailty group and automatic gas circuit breaker (72.7%) in the frailty group. For wider implementation of home IoT services, organizing services expected to have high usability and satisfaction based on user's frailty status is crucial. Also, providing education before service implementation might help older adults coping with digital literacy.