Health Systems最新文献

Data science, machine learning and artificial intelligence applications impact clinicians, informaticians, science journalists, and researchers. Most biomedical data science training focuses on learning a programming language in addition to higher mathematics and advanced statistics. This approach is appropriate for graduate students but greatly reduces the number of individuals in healthcare who can be involved in data science. To serve these four stakeholder audiences, we describe several curricular strategies focusing on solving real problems of interest to these audiences. Relevant competencies for these audiences include using intuitive programming tools that facilitate data exploration with minimal programming background, creating data models, evaluating results of data analyses, and assessing data science research reports, among others. Offering the curricula described here more broadly could broaden the stakeholder groups knowledgeable about and engaged in data science.

Participatory systems approaches are readily used in multi- and inter-disciplinary exploration of shared processes, but are less-commonly applied in trans-disciplinary efforts eliciting principles that generalise across contexts. The authors were charged with developing a transdisciplinary framework for prospectively or retrospectively assessing initiatives to improve education and training within a multifaceted organisation. A common System Impact Model (SIM) was developed in a series of workshops involving thirty participants from different disciplines, clinical specialisms, and organisations. The model provided a greater understanding of the interrelationships between factors influencing the benefits of education and training and development as seen from various stakeholder perspectives. It was used to create a system for assessing the impact of initiatives on service-users/patients, trainees, and organisations. It was shown to enable a range of participants to connect on common challenges, to maximise cross-, multi-, and inter-disciplinary learning, and to uncover new strategies for delivering value, as system designers.

The growing demand for better quality of care, together with an increasing awareness of limited resources, is bringing attention to the need for design in healthcare. In mental health, considered the largest single cause of disability in the UK, the need is great. Existing services often fail to meet current levels of demand and do not consistently deliver good quality care for all service users. The design of better delivery systems has the potential to improve service user experience and care outcomes. This paper reports how through the interactive and participatory method of storytelling, the key components of a mental health delivery system were identified. We explain each of the ten components and discuss their implications for system understanding and service design. A model of a mental health delivery system has also been proposed.

Cancer is a leading cause of mortality, with 10 million deaths in 2020. With the number of people impacted by cancer projected to increase, a better-integrated cancer care is needed. Evidence suggests that Hospital-Based Cancer Registries (HBCRs) that collect administrative and clinical data could improve integrated and equitable evidence-based care. However, the state and HBCR's role in the delivery of integrated cancer care for improved health outcomes, particularly in low- and middle-income countries (LMICs), is poorly understood and is assessed in this scoping review. A systematic search was conducted in April 2020. Thirty articles were included. This review found that while HBCRs have been implemented in several countries, few studies have evaluated the quality and effectiveness of registries, especially in LMICs. HBCRs in LMICs function more as data collection tools than information systems to influence clinical care decisions and monitoring, missing the opportunity to guide cancer care priorities and policies.

The widespread use of Blockchain technology (BT) in nations that are developing remains in its early stages, necessitating a more comprehensive evaluation using efficient and adaptable approaches. The need for digitalization to boost operational effectiveness is growing in the healthcare sector. Despite BT's potential as a competitive option for the healthcare sector, insufficient research has prevented it being fully utilised. This study intends to identify the main sociological, economical, and infrastructure obstacles to BT adoption in developing nations' public health systems. To accomplish this goal, the study employs a multi-level analysis of blockchain hurdles using hybrid approach. The study's findings provide decision- makers with guidance on how to proceed, as well as insight into implementation challenges.