The main objective of this report is to analyse and inform about international labour mobility, particularly within Europe, from the perspective of the Dutch Health and Social Care Sector. The report starts by describing the introduction of a new care system in The Netherlands. The government does not participate directly in the actual provision of care. This is a task principally for private care suppliers. Furthermore, the legal position of the Health and Social Care professions, regulated through the Individual Health Care Professions Act, and questions like the international recognition of degrees and the evaluation of foreign diplomas are discussed. This is followed by a clarification of the Dutch education system, particularly, relating to the study of medicine, nursing education and social work education. Subsequently, some core data on the ageing Dutch population are presented. The grey pressure increases and this will have an impact on health spending, health support and the future labour market. Then what follows is a description of the development of employment in the Dutch Health and Social Care Sector, per branch as well as the professions that are engaged in it. The general picture, at this moment, is that the Health and Social Care labour market is reasonably in balance. This trend will continue in the near future; shortages are expected only in the long term. All research done on the subject indicates that international mobility of medical and social professionals is still low in the Netherlands. The question remains whether a more active recruitment policy would be a solution for the expected long term shortages. The report concludes with a look at recruitment policy and some of its developments at the global, national and local level.
BACKGROUND: Observation of movement quality (MQ) is an indelible element in the process of clinical reasoning for patients with non-specific low back pain (NS-LBP). However, the observation and evaluation of MQ in common daily activities are not standardized within allied health care. This study aims to describe how Dutch allied health care professionals (AHCPs) observe and assess MQ in patients with NS-LBP and whether AHCPs feel the need to have a specific outcome measure for assessing MQ in patients with NS-LBP.METHODS: In this cross-sectional digital survey study, Dutch primary care AHCPs (n = 114) answered one open and three closed questions about MQ in NS-LBP management. Qualitative and quantitative analyses were applied.RESULTS: Qualitative analyses of the answers to the open questions revealed four main themes: 1) movement pattern features, 2) motor control features, 3) environmental influences and 4) non-verbal expressions of pain and exertion. Quantitative analyses clearly indicated that AHCPs observe MQ in the diagnostic (92%), therapeutic (91%) and evaluation phases (86%), that they do not apply any objective measurement of MQ and that 63% of the AHCPs consider it important to have a specific outcome measure to assess MQ. The AHCPs expressed added benefits and critical notes regarding clinical reasoning and quality of care.CONCLUSION: AHCPs recognize the importance of observing MQ in the assessment and management of LBP in a standardized way. However, there is no consensus amongst AHCPs how MQ should be standardized. Prior to standardization, it will be important to develop a theoretical framework to determine which observable and measurable dimensions of MQ are most valid and relevant for patients with NS-LBP to include in the assessment.
Background: The substitution of healthcare is a way to control rising healthcare costs. The Primary Care Plus (PC+) intervention of the Dutch ‘Blue Care’ pioneer site aims to achieve this feat by facilitating consultations with medical specialists in the primary care setting. One of the specialties involved is dermatology. This study explores referral decisions following dermatology care in PC+ and the influence of predictive patient and consultation characteristics on this decision. Methods: This retrospective study used clinical data of patients who received dermatology care in PC+ between January 2015 and March 2017. The referral decision following PC+, (i.e., referral back to the general practitioner (GP) or referral to outpatient hospital care) was the primary outcome. Stepwise logistic regression modelling was used to describe variations in the referral decisions following PC+, with patient age and gender, number of PC+ consultations, patient diagnosis and treatment specialist as the predicting factors. Results: A total of 2952 patients visited PC+ for dermatology care. Of those patients with a registered referral, 80.2% (N = 2254) were referred back to the GP, and 19.8% (N = 558) were referred to outpatient hospital care. In the multivariable model, only the treating specialist and patient’s diagnosis independently influenced the referral decisions following PC+. Conclusion: The aim of PC+ is to reduce the number of referrals to outpatient hospital care. According to the results, the treating specialist and patient diagnosis influence referral decisions. Therefore, the results of this study can be used to discuss and improve specialist and patient profiles for PC+ to further optimise the effectiveness of the initiative.
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.
-Chatbots are being used at an increasing rate, for instance, for simple Q&A conversations, flight reservations, online shopping and news aggregation. However, users expect to be served as effective and reliable as they were with human-based systems and are unforgiving once the system fails to understand them, engage them or show them human empathy. This problem is more prominent when the technology is used in domains such as health care, where empathy and the ability to give emotional support are most essential during interaction with the person. Empathy, however, is a unique human skill, and conversational agents such as chatbots cannot yet express empathy in nuanced ways to account for its complex nature and quality. This project focuses on designing emotionally supportive conversational agents within the mental health domain. We take a user-centered co-creation approach to focus on the mental health problems of sexual assault victims. This group is chosen specifically, because of the high rate of the sexual assault incidents and its lifetime destructive effects on the victim and the fact that although early intervention and treatment is necessary to prevent future mental health problems, these incidents largely go unreported due to the stigma attached to sexual assault. On the other hand, research shows that people feel more comfortable talking to chatbots about intimate topics since they feel no fear of judgment. We think an emotionally supportive and empathic chatbot specifically designed to encourage self-disclosure among sexual assault victims could help those who remain silent in fear of negative evaluation and empower them to process their experience better and take the necessary steps towards treatment early on.
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.
