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The authors developed and validated an algorithm using health administrative data to identify patients who are attached or uncertainly attached to a primary care provider (PCP) using patient responses to a survey conducted in Ontario, Canada.

The authors conducted a validation study using as a reference standard respondents to a community-based survey who indicated they did or did not have a PCP. The authors developed and tested health administrative algorithms against this reference standard. The authors calculated the sensitivity, specificity positive predictive value (PPV) and negative predictive value (NPV) on the final patient attachment algorithm. The authors then applied the attachment algorithm to the 2017 Ontario population.

The patient attachment algorithm had an excellent sensitivity (90.5%) and PPV (96.8%), though modest specificity (46.1%) and a low NPV (21.3%). This means that the algorithm assigned survey respondents as being attached to a PCP and when in fact they said they had a PCP, yet a significant proportion of those found to be uncertainly attached had indicated they did have a PCP. In 2017, most people in Ontario, Canada (85.4%) were attached to a PCP but 14.6% were uncertainly attached.

Administrative data for nurse practitioner's encounters and other interprofessional care providers are not currently available. The authors also cannot separately identify primary care visits conducted in walk in clinics using our health administrative data. Finally, the definition of hospital-based healthcare use did not include outpatient specialty care.

Uncertain attachment to a primary health care provider is a recurrent problem that results in inequitable access in health services delivery. Providing annual reports on uncertainly attached patients can help evaluate primary care system changes developed to improve access. This algorithm can be used by health care planners and policy makers to examine the geographic variability and time trends of the uncertainly attached population to inform the development of programs to improve primary care access.

As primary care is an essential component of a person's medical home, identifying regions or high need populations that have higher levels of uncertainly attached patients will help target programs to support their primary care access and needs. Furthermore, this approach will be useful in future research to determine the health impacts of uncertain attachment to primary care, especially in view of a growing body of the literature highlighting the importance of primary care continuity.

This patient attachment algorithm is the first to use existing health administrative data validated with responses from a patient survey. Using patient surveys alone to assess attachment levels is expensive and time consuming to complete. They can also be subject to poor response rates and recall bias. Utilizing existing health administrative data provides more accurate, timely estimates of patient attachment for everyone in the population.

This study aimed to develop the Thai gaming disorder scale (T-GDS) in children and adolescents to serve medical staff and investigate the effectiveness of the scale.

This is a research and development study. In total, 217 participants were children and adolescents between 8–18 years, then classified into four groups according to Children's Global Assessment Scale (CGAS). The T-GDS was developed; its content validity was then investigated by three experts. Mock assessment was conducted on 15 individuals replicating the actual sample group before the assessment was tested on the sample group by two medical staff. The quality of the scale is assessed through reliability, validity and cut-off point analysis.

Exploratory factor analysis (EFA) extracted four components with 18 items meeting the criteria and have Cronbach's alpha of 0.95. The analysis of ROC curve, to determine the cut-off point, associated the mild game addiction group with T-GDS score = 14; moderate group score = 28; and severe group score = 42.

Investigation of cut-off point by practitioners is vital to compare whether it aligns with the point determined by doctors in game addiction diagnosis. Future research should select critical item in order to reduce the number of questions and construct validity should be examined using confirmatory factor analysis.

This paper provides a comprehensive insight regarding severity of game addiction based on related criteria. As a result, treatment appropriate for each type of severity could be enhanced.

With global migration, the number of ethnic minority and migrant women receiving maternity health care in dominantly Anglo-European societies has increased significantly but they consistently have among the worst pregnancy and maternal outcomes. This paper aims to analyse gaps in structural (migration-related inequalities) and cultural (responsiveness to ethno-cultural practices) competencies among maternal health practitioners in Aotearoa New Zealand (NZ).

Using a semi-structured interview guide, in-depth interviews were conducted with 13 maternal health practitioners in NZ. Data were analysed using a thematic analysis framework.

The results highlight significant barriers around language and communication, cultural stereotyping by professionals, ethnic women’s own constraints around family and cultural expectations and their lack of knowledge about reproductive health. In addition, practitioners’ own ethnic differences are inseparable from their approach to structural and cultural competencies; there were instances of ‘over-’ or ‘under-’ reading of culture, practitioner constructions of ideal pregnancies and anti-racism concerns that shaped maternal care practices that were sensitive to, but also marginalised, ethnic migrant women who attended maternity services.

To the best of the authors’ knowledge, this is the only study in NZ that examines the impact of complex dynamics of migration and culture on knowledge, beliefs and values of practitioners, in context of their own personal biographies. Identifying strategies to improve the way diversity is practiced in hospital settings can be transformational in improving maternal outcomes for ethnic migrant women in NZ.

Medical research requires biological material and data collected through biobanks in reliable processes with quality assurance. Medical studies based on data with unknown or questionable quality are useless or even dangerous, as evidenced by recent examples of withdrawn studies. Medical data sets consist of highly sensitive personal data, which has to be protected carefully and is available for research only after the approval of ethics committees. The purpose of this research is to propose an architecture to support researchers to efficiently and effectively identify relevant collections of material and data with documented quality for their research projects while observing strict privacy rules.

Following a design science approach, this paper develops a conceptual model for capturing and relating metadata of medical data in biobanks to support medical research.

This study describes the landscape of biobanks as federated medical data lakes such as the collections of samples and their annotations in the European federation of biobanks (Biobanking and Biomolecular Resources Research Infrastructure – European Research Infrastructure Consortium, BBMRI-ERIC) and develops a conceptual model capturing schema information with quality annotation. This paper discusses the quality dimensions for data sets for medical research in-depth and proposes representations of both the metadata and data quality documentation with the aim to support researchers to effectively and efficiently identify suitable data sets for medical studies.

This novel conceptual model for metadata for medical data lakes has a unique focus on the high privacy requirements of the data sets contained in medical data lakes and also stands out in the detailed representation of data quality and metadata quality of medical data sets.

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.

A range of strategies to improve pharmaceutical care has been implemented by population health management (PHM) initiatives. However, which strategies generate the desired outcomes is largely unknown. The purpose of this paper is to identify guiding principles underlying collaborative strategies to improve pharmaceutical care and the contextual factors and mechanisms through which these principles operate.

The evaluation was informed by a realist methodology examining the links between PHM strategies, their outcomes and the contexts and mechanisms by which these strategies operate. Guiding principles were identified by grouping context-specific strategies with specific outcomes.

In total, ten guiding principles were identified: create agreement and commitment based on a long-term vision; foster cooperation and representation at the board level; use layered governance structures; create awareness at all levels; enable interpersonal links at all levels; create learning environments; organize shared responsibility; adjust financial strategies to market contexts; organize mutual gains; and align regional agreements with national policies and regulations. Contextual factors such as shared savings influenced the effectiveness of the guiding principles. Mechanisms by which these guiding principles operate were, for instance, fostering trust and creating a shared sense of the problem.

The guiding principles highlight how collaboration can be stimulated to improve pharmaceutical care while taking into account local constraints and possibilities. The interdependency of these principles necessitates effectuating them together in order to realize the best possible improvements and outcomes.

This is the first study using a realist approach to understand the guiding principles underlying collaboration to improve pharmaceutical care.

The paper aims to investigate the practices facilitating the transformation of healthcare services, understanding the resulting outcomes in terms of well-being and uplifting changes. a systematic literature review (SLR) focusing on analyzing the healthcare sector under the transformative service research (TSR) theoretical domain is conducted to achieve this goal.

Employing a structured SLR developed based on the PRISMA protocol (Pickering and Byrne, 2014; Pickering et al., 2015) and using Scopus and WoS databases, the study identifies and analyzes 49 papers published between 2021 and 2022. Content analysis is used to classify and analyze the papers.

The SLR reveals four transformative practices (how) within the healthcare sector under the TSR domain, each linked to specific well-being outcomes (what). The analysis shows that both practices and outcomes are mainly patient-related. An integrative framework for transformative healthcare service is presented and critically examined to identify research gaps and define the trajectory for the future development of TSR in healthcare. In addition, managerial implications are provided to guide practitioners.

This research is among the first to analyze TSR literature in the context of healthcare. The study critically examines the TSR’s impact on the sector’s transformation, providing insights for future research and offering a roadmap for healthcare practitioners to facilitate uplifting changes.

Cybersecurity in healthcare has become an urgent matter in recent years due to various malicious attacks on hospitals and other parts of the healthcare infrastructure. The purpose of this paper is to provide an outline of how core values of the health systems, such as the principles of biomedical ethics, are in a supportive or conflicting relation to cybersecurity.

This paper claims that it is possible to map the desiderata relevant to cybersecurity onto the four principles of medical ethics, i.e. beneficence, non-maleficence, autonomy and justice, and explore value conflicts in that way.

With respect to the question of how these principles should be balanced, there are reasons to think that the priority of autonomy relative to beneficence and non-maleficence in contemporary medical ethics could be extended to value conflicts in health-related cybersecurity.

However, the tension between autonomy and justice, which relates to the desideratum of usability of information and communication technology systems, cannot be ignored even if one assumes that respect for autonomy should take priority over other moral concerns.

In terms of value conflicts, most discussions in healthcare deal with the conflict of balancing efficiency and privacy given the sensible nature of health information. In this paper, the authors provide a broader and more detailed outline.

Society is critically dependent on an adequate supply of hospital doctors to ensure optimal health care. Voluntary turnover amongst hospital doctors is, however, an increasing problem for hospitals. The aim of this study was to systematically review the extant academic literature to obtain a comprehensive understanding of the current knowledge base on hospital doctor turnover and retention. In addition to this, we synthesise the most common methodological approaches used before then offering an agenda to guide future research.

Adopting the PRISMA methodology, we conducted a systematic literature search of four databases, namely CINAHL, MEDLINE, PsycINFO and Web of Science.

We identified 51 papers that empirically examined hospital doctor turnover and retention. Most of these papers were quantitative, cross-sectional studies focussed on meso-level predictors of doctor turnover.

Selection criteria concentrated on doctors who worked in hospitals, which limited knowledge of one area of the healthcare environment. The review could disregard relevant articles, such as those that discuss the turnover and retention of doctors in other specialities, including general practitioners. Additionally, being limited to peer-reviewed published journals eliminates grey literature such as dissertations, reports and case studies, which may bring impactful results.

Globally, hospital doctor turnover is a prevalent issue that is influenced by a variety of factors. However, a lack of focus on doctors who remain in their job hinders a comprehensive understanding of the issue. Conducting “stay interviews” with doctors could provide valuable insight into what motivates them to remain and what could be done to enhance their work conditions. In addition, hospital management and recruiters should consider aspects of job embeddedness that occur outside of the workplace, such as facilitating connections outside of work. By resolving these concerns, hospitals can retain physicians more effectively and enhance their overall retention efforts.

Focussing on the reasons why employees remain with an organisation can have significant social repercussions. When organisations invest in gaining an understanding of what motivates their employees to stay in the job, they are better able to establish a positive work environment that likely to promote employee well-being and job satisfaction. This can result in enhanced job performance, increased productivity and higher employee retention rates, all of which are advantageous to the organisation and its employees.

The review concludes that there has been little consideration of the retention, as opposed to the turnover, of hospital doctors. We argue that more expansive methodological approaches would be useful, with more qualitative approaches likely to be particularly useful. We also call on future researchers to consider focussing further on why doctors remain in posts when so many are leaving.

To construct a risk score using both clinical and intra-oral variables and to determine a risk score to screen individuals according to their risk of hyperglycemia.

A cross-sectional study was carried out among 690 Thai dental patients who visited the Special Clinic, Faculty of Dentistry, Mahidol University and a mobile dental unit of His Majesty the King of Thailandss Dental Service Unit. Participants aged ≥25 years without a previous history of type 2 diabetes mellitus were included in the study. Participants diagnosed with severe anemia and polycythemia were excluded. Questionnaires were used to collect demographic data. Point-of-care HbA1c, body mass index (BMI), blood pressure and periodontal status were analyzed.

A total of 690 participants were included in the study. A risk scoring system including five variables was developed. It exhibited fair discrimination (area under the curve = 0.72, 95%CI 0.68–0.71). The risk score value of 9 was used as the cut-off point for increased risk of abnormal HbA1c. Subjects that had a total risk score of 9 or more had a high probability of having abnormal HbA1c and were identified for referral to physicians for further investigation and diagnosis.

A risk score to predict hyperglycemia using a dental parameter was developed for convenient evaluation in dental clinics.