Exploring the experts’ perceptions of barriers to using internet of things for chronic disease management in Iran

Dadkhah, Mehdi; Mehraeen, Mohammad; Rahimnia, Fariborz; Kimiafar, Khalil

doi:10.1108/jstpm-07-2021-0104

Cited by 13 publications

(11 citation statements)

References 93 publications

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“…RFID and AR technologies are the next priority to be applied in a smart hospital. This research finding is in line with the results of the study done by Arora and Sharma (2022) and Dadkhah et al (2022) who referred to the importance of IoT and AI in the smart hospital. Thus, it is obvious that hospital managers should first think about providing searing devices, sensors and chips related to the IoTs and designing systems based on AI to have a smart hospital.…”

Section: Model For Assessing Smart Hospital Readinesssupporting

confidence: 91%

“…Their model was designed to classify users' perceptions regarding the experience of using Internet of Things (IoT)-based intelligent health systems. Dadkhah et al (2022) examined the barriers to using the IoTs in Iran based on its use for the management of chronic diseases. They revealed that there are four categories of governance, technical, economic and social obstacles according to experts' opinion.…”

Section: Introductionmentioning

confidence: 99%

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Toward a model for assessing smart hospital readiness within the Industry 4.0 paradigm

Ronaghi

2022

JSTPM

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Purpose The fourth industrial revolution and digital transformation have caused paradigm changes in the procedures of goods production and services through disruptive technologies, and they have formed new methods for business models. Health and medicine fields have been under the effect of these technology advancements. The concept of smart hospital is formed according to these technological transformations. The aim of this research, other than explanation of smart hospital components, is to present a model for evaluating a hospital readiness for becoming a smart hospital. Design/methodology/approach This research is an applied one, and has been carried out in three phases and according to design science research. Based on the previous studies, in the first phase, the components and technologies effecting a smart hospital are recognized. In the second phase, the extracted components are prioritized using type-2 fuzzy analytic hierarchical process based on the opinion of experts; later, the readiness model is designed. In the third phase, the presented model would be tested in a hospital. Findings The research results showed that the technologies of internet of things, robotics, artificial intelligence, radio-frequency identification as well as augmented and virtual reality had the most prominence in a smart hospital. Originality/value The innovation and originality of the forthcoming research is to explain the concept of smart hospital, to rank its components and to provide a model for evaluating the readiness of smart hospital. Contribution of this research in terms of theory explains the concept of smart hospital and in terms of application presents a model for assessing the readiness of smart hospitals.

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Section: Model For Assessing Smart Hospital Readinesssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Toward a model for assessing smart hospital readiness within the Industry 4.0 paradigm

Ronaghi

2022

JSTPM

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“…IoT connects the physical world, including the human body, with the internet, and IoT application to healthcare could improve the individuals' quality of life, assist in chronic disease management, danger warning and life-saving interventions remotely [78] and could assist in death prevention and cost reduction due to CVD [79]. The real-time monitoring of CVD patients through the IoT, which is a system of wireless, interrelated, and connected digital devices that could non-invasively collect physiological and environmental data, send, and store data over a network without requiring human-to-human or human-tocomputer interaction, could be realised [80,81].…”

Section: Discussionmentioning

confidence: 99%

Smart Home Technology Solutions for Cardiovascular Diseases: A Systematic Review

Moses

Adibi

Angelova

et al. 2022

ASI

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Cardiovascular diseases (CVD) are the leading cause of mortality globally. Despite improvement in therapies, people with CVD lack support for monitoring and managing their condition at home and out of hospital settings. Smart Home Technologies have potential to monitor health status and support people with CVD in their homes. We explored the Smart Home Technologies available for CVD monitoring and management in people with CVD and acceptance of the available technologies to end-users. We systematically searched four databases, namely Medline, Web of Science, Embase, and IEEE, from 1990 to 2020 (search date 18 March 2020). “Smart-Home” was defined as a system using integrated sensor technologies. We included studies using sensors, such as wearable and non-wearable devices, to capture vital signs relevant to CVD at home settings and to transfer the data using communication systems, including the gateway. We categorised the articles for parameters monitored, communication systems and data sharing, end-user applications, regulations, and user acceptance. The initial search yielded 2462 articles, and the elimination of duplicates resulted in 1760 articles. Of the 36 articles eligible for full-text screening, we selected five Smart Home Technology studies for CVD management with sensor devices connected to a gateway and having a web-based user interface. We observed that the participants of all the studies were people with heart failure. A total of three main categories—Smart Home Technology for CVD management, user acceptance, and the role of regulatory agencies—were developed and discussed. There is an imperative need to monitor CVD patients’ vital parameters regularly. However, limited Smart Home Technology is available to address CVD patients’ needs and monitor health risks. Our review suggests the need to develop and test Smart Home Technology for people with CVD. Our findings provide insights and guidelines into critical issues, including Smart Home Technology for CVD management, user acceptance, and regulatory agency’s role to be followed when designing, developing, and deploying Smart Home Technology for CVD.

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“…They have been reported to feel less supported, less respected, and less concerned about their chronic diseases, and to receive limited social and family support. [24][25][26][27][28] This study showed that the experimental group exhibited higher scores for family support than the control group at 24 weeks of intervention using the smart medication management system and that the difference was statistically significant. This may be explained by the family-involved smart care that enabled the participants to communicate with staff members on the platform, who were then able to offer psychological counseling to the participants.…”

Section: Discussionmentioning

confidence: 99%

Application of family-involved smart medication management system in rural-dwelling middle-aged and older adult participants with chronic diseases: Management of chronic diseases in rural areas

Chen

et al. 2022

Medicine

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Management of patients with chronic diseases in rural areas and the use of medications need to be urgently addressed. Therefore, this study aimed to evaluate the efficacy of a family-involved smart medication management system for rural patients with chronic diseases. Between June and August 2021, 82 patients with chronic diseases were selected using convenience sampling from 2 county towns in Hebei Province, China. They were randomly divided into control (41 participants) and experimental (41 participants) groups. The control group was managed using a routine medication management model for chronic diseases. The experimental group was managed using a family-involved smart medication management system, in addition to the control group interventions. The groups were graded using the 8-item Morisky Medication Adherence Scale (MMAS-8), the Self-efficacy for Appropriate Medication Use Scale (SEAMS), the Medication Knowledge Assessment Questionnaire, and the Family Support Scale before the intervention and at 8 and 24 weeks after the intervention. Pre-intervention group differences were not statistically significant. At 8 weeks after the intervention, the control group showed no statistically significant differences in the MMAS-8, SEAMS, and Medication Knowledge Assessment scores pre-and post-intervention. These scores were higher in the experimental group than in the control group, with the post-intervention scores being higher than the pre-intervention scores. The MMAS-8, SEAMS, and Medication Knowledge Assessment scores for the experimental group were higher at 24 weeks than at 8 weeks; these scores were higher in the experimental group than in the control group. The experimental group also had higher family support scores than the control group; these scores were higher pre-intervention than post-intervention. A family-involved smart medication management system can effectively improve medication adherence, self-efficacy for appropriate medication use, medication knowledge assessment scores, and family support for rural middle-aged and older adult patients with chronic diseases.

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Exploring the experts’ perceptions of barriers to using internet of things for chronic disease management in Iran

Cited by 13 publications

References 93 publications

Toward a model for assessing smart hospital readiness within the Industry 4.0 paradigm

Toward a model for assessing smart hospital readiness within the Industry 4.0 paradigm

Smart Home Technology Solutions for Cardiovascular Diseases: A Systematic Review

Application of family-involved smart medication management system in rural-dwelling middle-aged and older adult participants with chronic diseases: Management of chronic diseases in rural areas

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