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Patient safety focuses on minimizing risks that might occur to patients during provision of healthcare. The purpose of this study was to explore healthcare practitioners’ attitudes towards patient safety inside different hospital settings in Jeddah, Kingdom of Saudi Arabia.

A descriptive, cross-sectional study was conducted on a sample of healthcare practitioners in main hospitals in Jeddah. Two main hospitals (one governmental and one private) were selected from each region of Jeddah (east, west, north and south), with a total number of eight out of thirty hospitals. Data were collected through the Attitudes to Patient Safety Questionnaire III that was distributed online. The questionnaire used a 5-point scale. Descriptive statistics were used. Comparisons were made by independent t-test and ANOVA. The statistical significance level was set at p < 0.05.

The study included 341 healthcare practitioners of different sexes and specialties in eight major governmental and private hospitals in Jeddah. “Working hours as error cause” subscale had the highest mean score (4.03 ± 0.89), while “Professional incompetence as error cause” had the lowest mean score (3.49 ± 0.97). The total questionnaire had a moderate average score (3.74 ± 0.63). Weak correlations between the average score of the questionnaire and sex, occupation and workplace were found (−0.119, −0.018 and −0.088, respectively).

Hospitals need to develop targeted interventions, including continuing professional development programs, to enhance patient safety culture and practices. Moreover, patient safety training is required at the undergraduate education level, which necessitates health professions education institutions to give more attention to patient safety education in their curricula.

The study contributed to the existing literature on patient safety culture in hospital settings in Jeddah, Saudi Arabia. The insights generated by the study can inform targeted interventions to enhance patient safety culture in hospitals and improve patient outcomes.

Value creation based on artificial intelligence (AI) can significantly change global healthcare. Diagnostics, therapy and drug discovery start-ups are some key forces behind this change. This article aims to study the process of start-ups' value creation within healthcare.

A multiple case study method and a business model design approach were used to study nine European start-ups developing AI healthcare solutions. Obtained information was performed using within and cross-case analysis.

Three unique design elements were established, with 16 unique frames and three unifying design themes based on business models for AI healthcare start-ups.

Our in-depth framework focuses on the features of AI start-up business models in the healthcare industry. We contribute to the business model and business model innovation by systematically analyzing value creation, how it is delivered to customers, and communication with market participants, as well as design themes that combine start-ups and categorize them by specialization.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

This study aims to summarize the critical issues in medical federated learning and applicable solutions. Also, detailed explanations of how federated learning techniques can be applied to the medical field are presented. About 80 reference studies described in the field were reviewed, and the federated learning framework currently being developed by the research team is provided. This paper will help researchers to build an actual medical federated learning environment.

Since machine learning techniques emerged, more efficient analysis was possible with a large amount of data. However, data regulations have been tightened worldwide, and the usage of centralized machine learning methods has become almost infeasible. Federated learning techniques have been introduced as a solution. Even with its powerful structural advantages, there still exist unsolved challenges in federated learning in a real medical data environment. This paper aims to summarize those by category and presents possible solutions.

This paper provides four critical categorized issues to be aware of when applying the federated learning technique to the actual medical data environment, then provides general guidelines for building a federated learning environment as a solution.

Existing studies have dealt with issues such as heterogeneity problems in the federated learning environment itself, but those were lacking on how these issues incur problems in actual working tasks. Therefore, this paper helps researchers understand the federated learning issues through examples of actual medical machine learning environments.

The purpose of this paper is to investigate the medical incident responses from two public hospitals in Hong Kong, namely, Kowloon Hospital and Caritas Medical Centre, in order to improve the strategic preparation for crisis management in hospitals.

The paper analyses two medical incidents using Situational Crisis Communication Theory by Coombs (2007). The two case studies presented herein demonstrate the importance of consistency in terms of crisis responses.

For the first case, the crisis responses from different parties after the incident, including Hospital Authority, the doctor and the nurses from Kowloon Hospital, are contradicting to each other. First, Hospital Authority confirmed that the incident is solely an accident which is a denial response. Second, the doctor passed the responsibility to the nurses which is a scapegoating response. Third, the nurses tend to reduce the responsibility for the death of patient by excusing strategy. As a whole, their responses are inconsistent to each other. For the second case, Caritas had initially denied the responsibilities, but finally had given partial apology under public pressure. That makes people think that Caritas does not really regret.

Rebuilding posture should be used instead of denial and diminishment posture. However, public organization and civil servants are reluctant to use a full apology due to possible legal consequences. The apology ordinance would ease the pressure to express regret and sympathy.

The purpose of this paper is to perform and report a systematic review of published research on patient safety attitudes of health staff employed in hospital emergency departments (EDs).

An electronic search was conducted of PsychINFO, ProQuest, MEDLINE, EMBASE, PubMed and CINAHL databases. The review included all studies that focussed on the safety attitudes of professional hospital staff employed in EDs.

Overall, the review revealed that the safety attitudes of ED health staff are generally low, especially on teamwork and management support and among nurses when compared to doctors. Conversely, two intervention studies showed the effectiveness of team building interventions on improving the safety attitudes of health staff employed in EDs.

Six studies met the inclusion criteria, however, most of the studies demonstrated low to moderate methodological quality.

Teamwork, communication and management support are central to positive safety attitudes. Teamwork training can improve safety attitudes. Given that EDs are the “front-line” of hospital care and patients within EDs are especially vulnerable to medical errors, future research should focus on the safety attitudes of medical staff employed in EDs and its relationship to medical errors.

Quantifying the performance level of surgeons with digital virtual reality (VR) simulators can help ensure that quality requirements in healthcare are met. In order to better understand integration amongst quality principles, practices and technologies in the adoption and diffusion of VR simulators, the authors applied a technological innovation system (TIS) framework. The purpose of this study is to understand how the adoption and diffusion of VR surgical simulators in a Swedish healthcare context is influenced by various system factors.

In this study, single-case holistic design based on innovation system theory was used to analyse the adoption of digital quality technologies related to surgical performance in Swedish hospitals. The case employs a mixed methods approach triangulating data longitudinally from published documents and expert interviews.

Adoption of digital technologies regarding surgical performance is restricted by system factors relating to inconsistent normative and regulatory requirements for quantified performance criteria to judge surgical expertise. Addressing these systems' weaknesses with evidence-based training programmes can have a significant impact on the further development of the innovation system and can ultimately affect healthcare reliability and quality.

This paper explores quality management (QM) challenges in the context of digital transformation in healthcare. The paper attempts to fill the gap for TIS studies in a healthcare context and highlight the role of innovation function strength along the value chain and in relation to technology cycles to increase the understanding of adoption of digital technologies relating to surgical performance.

The purpose of this paper is to empirically explore and conceptualize how healthcare professionals and managers give shape to the increasing call for compassionate care as an alternative for system-based quality management systems. The research demonstrates how quality rebels craft deviant practices of good care and how they account for them.

Ethnographic research was conducted in three Dutch hospitals, studying clinical groups that were identified as deviant: a nursing ward for infectious diseases, a mother–child department and a dialysis department. The research includes over 120 h of observation, 41 semi-structured interviews and 2 focus groups.

The research shows that rebels’ quality practices are an emerging set of collaborative activities to improving healthcare and meeting (individual) patient needs. They conduct “contexting work” to achieve their quality aims by expanding their normative work to outside domains. As rebels deviate from hospital policies, they are sometimes forced to act “under the radar” causing the risk of groupthink and may undermine the aim of public accounting.

The research shows that in order to come to more compassionate forms of care, organizations should allow for more heterogeneity accompanied with ongoing dialogue(s) on what good care yields as this may differ between specific fields or locations.

This is the first study introducing quality rebels as a concept to understanding social deviance in the everyday practices of doing compassionate and good care.

After knee replacement surgery, rehabilitation is needed to recover to normal levels of mobility. A continuous passive motion (CPM) machine is usually introduced at this stage to aid rehabilitation. However, the redundant structure and complex mechanism of the existing machine has resulted in irregular use. The purpose of this paper is to redesign the current machine.

The mechanical and electrical systems of the current machine were studied alongside interviews with stakeholders. Problems with the existing machine were identified. Related information was gathered in both the engineering and medical aspects. The redesign concept of the equipment was specified following engineering analyses to develop the final model. Finite element analysis was performed to ensure the appropriate size and dimension of the equipment. The prototype of the redesigned CPM was manufactured in-house. Product testing was conducted with 40 volunteers including experienced therapists, nurses, university students and working-age people.

Compared to the previous machine, the newly designed model was improved in both functioning and manufacturing costs. The redesigned machine is more durable and consists of a less complex structure.

The redesigned machine introduces some new features and removes unnecessary functions. As a result, the model costs less and hence, is considered beneficial to the general public. More utilization is expected which could eventually reduce the therapists’ workload at the hospital. This research provides well-defined processes of the product development starting from the users’ requirement analysis to the prototype testing stage.

The purpose of this paper is to make the case for bringing compassion to students in educational settings, preschool through graduate school (PK-20).

First, the author defines what is meant by “compassion” and differentiates it from the related constructs. Next, the author discusses the importance of bringing compassion into education, thinking specifically about preschool, K-12 (elementary and middle school/junior high/high school), college students, and graduate students (e.g. law, medical, nurses, counselors and therapists-in-training). The author then reviews the scant empirical literature on compassion in education and makes recommendations for future research. In the final section, the author makes specific and practical recommendations for the classroom (e.g. how to teach and evaluate compassion in PK-20).

While there is a fair amount of research on compassion with college students, and specifically regarding compassion for oneself, as the author reviews in this paper, the field is wide open in terms of empirical research with other students and examining other forms of compassion.

This is not a formal review or meta-analysis.

This paper will be a useful resource for teachers and those interested in PK-20 education.

This paper highlights the problems and opportunities for bringing compassion into education settings.

To date, no review of compassion in PK-20 exists.