Objectives: Loneliness has been associated with unhealthy behavior, poorer health, and increased morbidity. However, the costs of loneliness are poorly understood.Methods: Multiple sources were combined into a dataset containing a nationally representative sample (n = 341,376) of Dutch adults (18+). The association between loneliness and total, general practitioner (GP), specialized, pharmaceutical, and mental healthcare expenditure was tested using Poisson and Zero-inflated negative binomial models, controlling for numerous potential confounders (i.e., demographic, socioeconomic, lifestyle-related factors, self-perceived health, and psychological distress), for four age groups.Results: Controlling for demographic, socioeconomic, and lifestyle-related factors, loneliness was indirectly (via poorer health) associated with higher expenditure in all categories. In fully adjusted models, it showed a direct association with higher expenditure for GP and mental healthcare (0.5 and 11.1%, respectively). The association with mental healthcare expenditure was stronger in younger than in older adults (for ages 19–40, the contribution of loneliness represented 61.8% of the overall association).Conclusion: Loneliness contributes to health expenditure both directly and indirectly, particularly in younger age groups. This implies a strong financial imperative to address this issue.

Loneliness is a growing public health issue. It is more common in disadvantaged groups and has been associated with a range of poor health outcomes. Loneliness may also form an independent pathway between socio-economic disadvantage and poor health. Therefore, the aim of this study was to explore the contribution of loneliness to socio-economic health inequalities. These contributions were studied in a Dutch national sample (n = 445,748 adults (≥19 y.o.)) in Poisson and logistic regression models, controlling for age, gender, marital status, migration background, BMI, alcohol consumption, smoking, and physical activity. Loneliness explained 21% of socioeconomic health inequalities between the lowest and highest socio-economic groups in self-reported chronic disease prevalence, 27% in poorer self-rated health, and 51% in psychological distress. Subgroup analyses revealed that for young adults, loneliness had a larger contribution to socioeconomic gaps in self-rated health (37%) than in 80+-year-olds (16%). Our findings suggest that loneliness may be a social determinant of health, contributing to the socioeconomic health gap independently of well-documented factors such as lifestyles and demographics, in particular for young adults. Public health policies targeting socioeconomic health inequalities could benefit from integrating loneliness into their policies, especially for young adults.

Background Polypharmacy in older patients can lead to potentially inappropriate prescribing. The risk of the latter calls for effective medication review to ensure proper medication usage and safety. Objective Provide insight on the similarities and differences of medication review done in multiple ways that may lead to future possibilities to optimize medication review. Setting This study was conducted in Zuyderland Medical Centre, the second largest teaching hospital in the Netherlands. Method This descriptive study compares the quantity and content of remarks identified by medication review performed by a geriatrician, outpatient pharmacist, and Clinical Decision Support System. The content of remarks is categorized in seven categories of possible pharmacotherapeutic problems: ‘indication without medication’, ‘medication without indication’, ‘contra-indication/interaction/side-effect’, ‘dosage problem’, ‘double medication’, ‘incorrect medication’ and ‘therapeutic drug monitoring’. Main outcome measure Number and content of remarks on medication review. Results The Clinical Decision Support System (1.8 ± 0.8 vs. 0.9 ± 0.9, p < 0.001) and outpatient pharmacist (1.8 ± 0.8 vs. 0.9 ± 0.9, p = 0.045) both noted remarks in significantly more categories than the geriatricians. The Clinical Decision Support System provided more remarks on ‘double medication’, ‘dosage problem’ and ‘contraindication/interaction/side effects’ than the geriatrician (p < 0.050), while the geriatrician did on ‘medication without indication’ (p < 0.001). The Clinical Decision Support System noted significantly more remarks on ‘contraindication/interaction/side effects’ and ‘therapeutic drug monitoring’ than the outpatient pharmacist, whereas the outpatient pharmacist reported more on ‘indication without medication’ and ‘medication without indication’ than the Clinical Decision Support System (p ≤ 0.007). Conclusion Medication review performed by a geriatrician, outpatient pharmacist, and Clinical Decision Support System provides different insights and should be combined to create a more comprehensive report on medication profiles.

Background: Dashboards are an important tool for hospitals to improve quality and safety performance. However, implementing quality and safety dashboards often does not increase performance due to a lack of use by health professionals. Including health professionals in the development process of quality and safety dashboards can improve their use in practice. Yet, it remains unclear how a development process involving health professionals can be executed successfully. Objective: The aim of this study is twofold: (1) to delineate how a process whereby health professionals are included in the development of quality and safety dashboards can be facilitated and (2) to identify the factors that are important to consider in order to make that process successful. Methods: We conducted a qualitative, in-depth exploratory case study in which we analyzed 150 pages of internal documents and interviewed 13 staff members regarding the development of quality and safety dashboards within 2 care pathways of a hospital that has experience in such development. The data were analyzed inductively using the constant comparative method. Results: We found that the development of quality and safety dashboards in collaboration with health professionals was facilitated through a five-stage process: (1) familiarizing participants with dashboards and the development process; (2) brainstorming about potential indicators to be included in the dashboard; (3) prioritizing, defining, and selecting indicators to be included in the dashboard; (4) examining how the indicators can be visualized; and (5) implementing the dashboard and following up on its use. To enhance the success of the process, 3 factors were deemed important. The first is to create and maintain broad involvement, ensuring that various professions are represented and take ownership of the dashboard. Here, potential barriers include gaining engagement from peers not directly involved in the process and maintaining involvement after the initial implementation of the dashboard. Second, unburdening, whereby quality and safety staff facilitate a structured process that has little additional burden for professionals. For this, time management and a lack of collaboration with departments responsible for delivering the data might be an issue. Lastly, focusing on relevance for health professionals, which refers to the inclusion of indicators with value for health professionals. For this factor, a lack of consensus on how indicators should be defined and registered might be a barrier. Conclusions: Health care organizations seeking to develop quality and safety dashboards in collaboration with health professionals can use a 5-stage process. To enhance the success of the process, organizations are advised to focus on 3 key factors. For each of the key factors, potential barriers should be taken into account. Engaging in this process and attaining the key factors could increase the likelihood that the dashboards are used in practice.

Health care's grand challenges, such as continuously increasing costs, challenge the sustainability of health systems. Purpose-oriented networks are considered a favorable mode of organization to address these grand challenges. Therefore, it is crucial that they are effective. While network effectiveness is a heavily theorized, multi-dimensional concept that is often measured as a perception of actors, little is known about how network actors perceive effectiveness in practice and how this influences their behavior. In this study, we explored how network actors perceive network effectiveness using 32 interviews with representatives from network member organizations and regulatory agencies actor, 28 h of network meeting observations, and 1.272 pages of documents such as meeting minutes and media outlets. Our results show that actors primarily see hard outcomes (e.g. changes in cost or quality of care) as effectiveness but given the temporal nature of these goals and difficulties quantifying them, they resort to the collaborative process as a proxy to assess effectiveness. Actors engage in networks to solve grand challenges. However, conforming to expectations and environmental pressures also play a substantial role for actors to (continue to) participate in networks. In the absence of hard outcomes, actors legitimize their continued participation in networks using the collaborative process of networks. Actors therefore take purpose-oriented networks for granted as a legitimate way of organizing. Besides attempting to solve grand challenges, networks thus also seem to be adopted because of powerful institutional rules that function as rationalized myths, to gain legitimacy. Future research should be aware of and further unravel the institutional pressures in networks.