Abstract: The typical structure of the healthcare sector involves (specialist) intertwined practices co-occurring in formal or informal networks. These practices must answer to the concerns and needs of all related stakeholders. Multimorbidity and the need to share knowledge for scientific development are among the driving factors for collaboration in healthcare. To establish and keep up a permanent collaborative link, it takes effort and understanding of the network characteristics that must be governed. It is not hard to find practices of Network Governance (NG) in a variety of industries. Still, there is a lack of insight in this subject, including knowledge on how to establish and maintain an effective healthcare network. Consequently, this study's research question is: How is network governance organized in the healthcare sector? A systematic literature study was performed to select 80 NG articles. Based on these publications the characteristics of NG are made explicit. The findings demonstrate that combinations of governance style (relational versus contractual governance) and governance structure (lead versus shared governance) lead to different network dynamics. Furthermore, the results show that in order to comprehend how networks in the healthcare sector emerge and can be regulated, it is vital to understand the current network type. Additionally, it informs us of the governing factors. Zie https://www.hbo-kennisbank.nl/details/sharekit_han:oai:surfsharekit.nl:e4f8fa3a-4af8-42ef-b2dd-c86d77b4cec6
BACKGROUND: The quality standards of the Dutch Society of Intensive Care require monitoring of the satisfaction of patient's relatives with respect to care. Currently, no suitable instrument is available in the Netherlands to measure this. This study describes the development and psychometric evaluation of the questionnaire-based Consumer Quality Index 'Relatives in Intensive Care Unit' (CQI 'R-ICU'). The CQI 'R-ICU' measures the perceived quality of care from the perspective of patients' relatives, and identifies aspects of care that need improvement.METHODS: The CQI 'R-ICU' was developed using a mixed method design. Items were based on quality of care aspects from earlier studies and from focus group interviews with patients' relatives. The time period for the data collection of the psychometric evaluation was from October 2011 until July 2012. Relatives of adult intensive care patients in one university hospital and five general hospitals in the Netherlands were approached to participate. Psychometric evaluation included item analysis, inter-item analysis, and factor analysis.RESULTS: Twelve aspects were noted as being indicators of quality of care, and were subsequently selected for the questionnaire's vocabulary. The response rate of patients' relatives was 81% (n = 455). Quality of care was represented by two clusters, each showing a high reliability: 'Communication' (α = .80) and 'Participation' (α = .84). Relatives ranked the following aspects for quality of care as most important: no conflicting information, information from doctors and nurses is comprehensive, and health professionals take patients' relatives seriously. The least important care aspects were: need for contact with peers, nuisance, and contact with a spiritual counsellor. Aspects that needed the most urgent improvement (highest quality improvement scores) were: information about how relatives can contribute to the care of the patient, information about the use of meal-facilities in the hospital, and involvement in decision-making on the medical treatment of the patient.CONCLUSIONS: The CQI 'R-ICU' evaluates quality of care from the perspective of relatives of intensive care patients and provides practical information for quality assurance and improvement programs. The development and psychometric evaluation of the CQI 'R-ICU' led to a draft questionnaire, sufficient to justify further research into the reliability, validity, and the discriminative power of the questionnaire.
Abstract from article: The Dutch healthcare system has changed towards a system of regulated competition to contain costs and to improve efficiency and quality of care. This paper provides: (1) a brief as-is overview of the changes for primary care, based on explorative literature reviews; (2) provides noteworthy remarks as for the way primary and secondary healthcare is organised; (3) an example of an E-health portal illustrating implemented processes within the Dutch context and (4) a proposed research agenda on various e-health topics. Noteworthy remarks are: (1) government, insurer, healthcare provider and patient are main actors within the Dutch healthcare system; (2) general practitioners (GP’s) are gatekeepers to secondary and other care providers; (3) the illustrated portal with a patient oriented design, provides access to applications implemented at care providers resulting in increased electronic availability and increased patient satisfaction; (4) a variety of fragmented information systems at health care providers exists, which leaves room for standardisation and increased efficiency. We end with suggestions for future research.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
Over a million people in the Netherlands have type 2 diabetes (T2D), which is strongly related to overweight, and many more people are at-risk. A carbohydrate-rich diet and insufficient physical activity play a crucial role in these developments. It is essential to prevent T2D, because this condition is associated with a reduced quality of life, high healthcare costs and premature death due to cardiovascular diseases. The hormone insulin plays a major role in this. This hormone lowers the blood glucose concentration through uptake in body cells. If an excess of glucose is constantly offered, initially the body maintains blood glucose concentration within normal range by releasing higher concentrations of insulin into the blood, a condition that is described as “prediabetes”. In a process of several years, this compensating mechanism will eventually fail: the blood glucose concentration increases resulting in T2D. In the current healthcare practice, T2D is actually diagnosed by recognizing only elevated blood glucose concentrations, being insufficient for identification of people who have prediabetes and are at-risk to develop T2D. Although the increased insulin concentrations at normal glucose concentrations offer an opportunity for early identification/screening of people with prediabetes, there is a lack of effective and reliable methods/devices to adequately measure insulin concentrations. An integrated approach has been chosen for identification of people at-risk by using a prediabetes screening method based on insulin detection. Users and other stakeholders will be involved in the development and implementation process from the start of the project. A portable and easy-to-use demonstrator will be realised, based on rapid lateral flow tests (LFTs), which is able to measure insulin in clinically relevant samples (serum/blood) quickly and reliably. Furthermore, in collaboration with healthcare professionals, we will investigate how this screening method can be implemented in practice to contribute to a healthier lifestyle and prevent T2D.
English: This living lab aims to support the creation, development and implementation of next generation concepts for sustainable healthcare logistics, with special attention for last mile solutions. Dutch healthcare providers are on the verge of a transition towards (more) sustainable business models, spurred by e.g., increasing healthcare costs, ongoing budget cuts, tight labor market conditions and increasing ecological awareness. Consequently, healthcare providers need to improve and innovate their business model and underlying logistics concept(s). Simultaneously, many cities are struggling with congestion in traffic, air quality and liveability in general. This calls for Last Mile Logistics (LML) concepts that can address challenges like effective and efficient resource planning, scheduling and utilization and, particularly, sustainability goals. LML can reduce environmental and social impact by decreasing emissions, congestion and pollution through effectively consolidating in-flows of goods and providing innovative solutions for care, wellbeing and related services. The research and initiatives in the living lab will address the following challenges: reducing the ecological footprint, reducing (healthcare-related) costs, improving service quality, decreasing loneliness of frail citizens and improving the livability of urban areas (reducing congestion and emissions). Given the scarcity and fragmentation of knowledge on healthcare logistics in organizations the living lab will also act as a learning community for (future) healthcare- and logistics professionals, thereby supporting the development of human capital. By working closely with related stakeholders and using a transdisciplinary research approach it is ensured that the developed knowledge and solutions deliver a contribution to societal challenges and have sound business potential.
