The digitization of healthcare services is a major shift in the manner in which healthcare services are offered and managed in the modern era. The COVID-19 pandemic has speeded up the use of digital technologies in the healthcare sector. Healthcare 4.0 (H4.0) is much more than the adoption of digital tools, however; going beyond that, it is the digital transformation of healthcare. The successful implementation of H 4.0 presents a challenge as social and technical factors must be considered. This study, through a systematic literature review, expounds ten critical success factors for the successful implementation of H 4.0. Bibliometric analysis of existing articles is also carried out to understand the development of knowledge in this domain. H 4.0 is rapidly gaining prominence, and a comprehensive review of critical success factors in this area has yet to be conducted. Conducting such a review makes a valuable contribution to the body of knowledge in healthcare operations management. Furthermore, this study will also help healthcare practitioners and policymakers to develop strategies to manage the ten critical success factors while implementing H 4.0.

/pdf/critical-success-factors-for-successful-implementation-of-5tqryznf.pdf

Critical Success Factors for Successful Implementation of Healthcare 4.0: A Literature Review and Future Research Agenda

https://www.mdpi.com/2227-9032/11/6/875/pdf?version=1679024450

Ten Years of TeleHealth and Digital Healthcare: Where Are We?

Digital transformation in healthcare: Assessing the role of digital technologies for managerial support processes

Abstract Healthcare systems around the world are currently witnessing various challenges, including population aging and workforce shortages. As a result, the existing, overworked staff are struggling to meet the ever-increasing demands and provide the desired quality of care. One of the promising technological solutions that could complement the human workforce and alleviate some of their workload, are socially assistive humanoid robots. However, despite their potential, the implementation of socially assistive humanoid robots is often challenging due to low acceptance among key stakeholders, namely, patients and healthcare professionals. Hence, the present study first investigated the extent to which these stakeholders accept the use of socially assistive humanoid robots in nursing and care routine, and second, explored the characteristics that contribute to higher/lower acceptance within these groups, with a particular emphasis on demographic variables, technology expectations, ethical acceptability, and negative attitudes. In study 1, conducted on a sample of 490 healthcare professionals, the results of structural equation modeling showed that acceptance is driven primarily by aspects of ethical acceptability, although education and technology expectations also exert an indirect effect. In study 2, conducted on a sample of 371 patients, expectations regarding capabilities and attitudes towards the social influence of robots emerged as important predictors of acceptance. Moreover, although acceptance rates differed between tasks, both studies show a relatively high acceptance of socially assistive humanoid robots. Despite certain limitations, the study findings provide essential knowledge that enhances our understanding of stakeholders’ perceptions and acceptance of socially assistive humanoid robots in hospital environments, and may guide their deployment. 

Using Structural Equation Modeling to Explore Patients’ and Healthcare Professionals’ Expectations and Attitudes Towards Socially Assistive Humanoid Robots in Nursing and Care Routine

Introduction Assistive and service robots have been increasingly designed and deployed in long-term care (LTC) but little evidence guides their use. This scoping review synthesises existing studies on facilitators and barriers to using artificial intelligence (AI)-enabled robots with older adults in LTC settings. Methods and analysis We will follow the Joanna Briggs Institute’s scoping review methodology for the study, to be conducted from November 2023 to April 2024. We will focus on literature exploring the use of AI-enabled robots with older adults in an LTC setting from healthcare providers’ perspectives. Three steps will be taken: (a) keywords and index terms will be identified from MEDLINE and CINAHL databases; (b) comprehensive searches will be conducted in MEDLINE, CINAHL, Embase, Web of Science, Scopus, AgeLine, PsycINFO, ProQuest and Google, using keywords and index terms identified in step (a); and (c) examining reference lists of the included studies and selecting items in the reference lists which meet the inclusion criteria. Searches for grey literature will also be conducted via Google. The results will be presented in a charting table and a narrative summary will be presented in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Ethics and dissemination Ethics approval and participation consent are not required because the data are publicly available. The results will be presented via a journal article and conference presentations.

Facilitators and barriers to using AI-enabled robots with older adults in long-term care from staff perspective: a scoping review protocol

Introduction Population ageing, the rise of chronic diseases and the emergence of new viruses are some of the factors that contribute to an increasing share of gross domestic product dedicated to health spending. COVID-19 has shown that nursing staff represents the critical part of hospitalisation. Technological developments in robotics and artificial intelligence can significantly reduce costs and lead to improvements in many hospital processes. The proposed study aims to assess expectations, attitudes and ethical acceptability regarding the integration of socially assistive humanoid robots into hospitalised care workflow from patients’ and healthcare professionals’ perspectives and to compare them with the results of similar studies. Methods/design The study is designed as a cross-sectional survey, which will include three previously validated questionnaires, the Technology-Specific Expectation Scale (TSES), the Ethical Acceptability Scale (EAS) and the Negative Attitudes towards Robots Scale (NARS). The employees of a regional clinical centre will be asked to participate via an electronic survey and respond to TSES and EAS questionaries. Patients will respond to TSES and NARS questionaries. The survey will be conducted online. Ethics and dissemination Ethical approval for the study was obtained by the Medical Ethics Commission of the University Medical Center Maribor. Results will be published in a relevant scientific journal and communicated to participants and relevant institutions through dissemination activities and the ecosystem of the Horizon 2020 funded project HosmartAI (grant no. 101016834). Ethical approval date 06 May 2021. Estimated start of the study December 2021.

/pdf/study-protocol-a-survey-exploring-patients-and-healthcare-220eog7q.pdf

Study protocol: a survey exploring patients’ and healthcare professionals’ expectations, attitudes and ethical acceptability regarding the integration of socially assistive humanoid robots in nursing

Although clinical decision support systems (CDSSs) are increasingly emphasized as one of the possible levers for improving care, they are still not widely used due to different barriers, such as doubts about systems’ performance, their complexity and poor design, practitioners’ lack of time to use them, poor computer skills, reluctance to use them in front of patients, and deficient integration into existing workflows. While several studies on CDSS exist, there is a need for additional high-quality studies using large samples and examining the differences between outcomes following a decision based on CDSS support and those following decisions without this kind of information. Even less is known about the effectiveness of a CDSS that is delivered during a grand round routine and with the help of socially assistive humanoid robots (SAHRs). In this study, 200 patients will be randomized into a Control Group (i.e. standard care) and an Intervention Group (i.e. standard care and novel CDSS delivered via a SAHR). Health care quality and Quality of Life measures will be compared between the two groups. Additionally, approximately 22 clinicians, who are also active researchers at the University Clinical Center Maribor, will evaluate the acceptability and clinical usability of the system. The results of the proposed study will provide high-quality evidence on the effectiveness of CDSS systems and SAHR in the grand round routine.

https://doi.org/10.1177/20552076221129068

A randomized controlled trial for evaluating the impact of integrating a computerized clinical decision support system and a socially assistive humanoid robot into grand rounds during pre/post-operative care

Introduction The workforce shortage in the healthcare context is a growing issue that exerts detrimental effects on employees (e.g., higher workload) and patients (e.g., suboptimal patient care). Since traditional approaches alone may not be enough to solve this problem, there is a need for complementary innovative digital health solutions, such as socially assistive robots. Hence, the proposed study aims to investigate the effects of gamified nursing education and physiotherapy delivered by a socially assistive robot on patient- (engagement, perceived quality of care) and employee-related outcomes (perceived self-efficacy, workload). Methods and analysis Approximately 90 vascular and thoracic surgery patients will receive either standard care or standard care with additional robot interactions over the course of 3–5 days. Additionally, approximately 34 nursing and physiotherapeutic employees will fill out self-report questionnaires after weeks of not using a social robot and weeks of using a social robot. The main hypotheses will be tested with mixed-design analyses of variance and paired-samples t-tests. Discussion While the proposed study has some limitations, the results will provide high-quality and comprehensive evidence on the effectiveness of socially assistive robots in healthcare. Ethics and dissemination The study was approved by the Medical Ethics Commission of the University Medical Center and registered in the ISRCTN registry (ISRCTN96689284). The study findings will be summarized in international peer-reviewed scientific journals and meetings and communicated to relevant stakeholders.

https://www.frontiersin.org/articles/10.3389/fmed.2022.989808/pdf

A protocol on the effects of interactive digital assistance on engagement and perceived quality of care of surgery patients and self-efficacy and workload of staff

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Study protocol: a survey exploring patients’ and healthcare professionals’ expectations, attitudes and ethical acceptability regarding the integration of socially assistive humanoid robots in nursing

A randomized controlled trial for evaluating the impact of integrating a computerized clinical decision support system and a socially assistive humanoid robot into grand rounds during pre/post-operative care

A protocol on the effects of interactive digital assistance on engagement and perceived quality of care of surgery patients and self-efficacy and workload of staff