Trust in Dutch intensive care networks:the results of a survey

Introduction: Dutch ICUs have been enrolled in network organisations since the Quality Standard of 2016. In networks, intensivists have to cooperate to provide a high quality of care for all patients in their network. Trust is essential to cooperate effectively in a network. It is unknown what the degree of trust is in Dutch ICU networks. Methods: A survey was composed using the questionnaire by Cummings, measuring the experience of trust, and the questionnaire by Currall, measuring the willingness to show behaviour that is consistent with trust. Two overall questions concerning the feeling of being part of the network and the overall level of trust were added. All questions were answered on a 7-point Likert scale. Network managers passed the questionnaire to intensivists in the network. Results: The overall level of trust showed a mean of 5.5 (SD 1.2), similar to the mean of the Cummings questionnaire (5.3; SD 0.9). Academic intensivists had a significantly higher level of trust than intensivists from other hospitals (5.9 vs 5.0 and 5.3; p=0.009). The questions covering `surveillance', which measures the need for control, scored lowest with 3.8 (SD 1.3). Intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. Conclusion: Intensivists experience a reasonable level of trust within their network. However, intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. This suggests that the actual trust is conditional. Academic intensivists showed the highest level of trust

Trust in Dutch intensive care networks:the results of a survey

Introduction: Dutch ICUs have been enrolled in network organisations since the Quality Standard of 2016. In networks, intensivists have to cooperate to provide a high quality of care for all patients in their network. Trust is essential to cooperate effectively in a network. It is unknown what the degree of trust is in Dutch ICU networks. Methods: A survey was composed using the questionnaire by Cummings, measuring the experience of trust, and the questionnaire by Currall, measuring the willingness to show behaviour that is consistent with trust. Two overall questions concerning the feeling of being part of the network and the overall level of trust were added. All questions were answered on a 7-point Likert scale. Network managers passed the questionnaire to intensivists in the network. Results: The overall level of trust showed a mean of 5.5 (SD 1.2), similar to the mean of the Cummings questionnaire (5.3; SD 0.9). Academic intensivists had a significantly higher level of trust than intensivists from other hospitals (5.9 vs 5.0 and 5.3; p=0.009). The questions covering `surveillance', which measures the need for control, scored lowest with 3.8 (SD 1.3). Intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. Conclusion: Intensivists experience a reasonable level of trust within their network. However, intensivists feel the need to make formal agreements and they experience a relatively intense need to control these agreements. This suggests that the actual trust is conditional. Academic intensivists showed the highest level of trust

Network governance of Dutch intensive care units:state of affairs after implementation of the Quality Standard

Objective: To study the current state of affairs concerning Dutch intensive care network governance in relation to known effective governance structures of network organisations. Methods: Six characteristics of intensive care networks were defined to determine the four contingency factors from the Provan & Kenis network governance models. The contingency factors were determined for all Dutch intensive care networks. An overview of the networks and characteristics was created by triangulation, using information from two national intensive care network meetings (November 2017 and June 2018) and semi-structured interviews by telephone with 10 network intensivists and / or network managers. Results: Based on the chosen characteristics, none of the Dutch intensive care networks has a governance structure according to one of the Provan & Kenis successful forms of governance. Each of the present networks has a governance structure with elements from two or three different types. Characteristics of the network administrative organisation and shared governance form overlap in 10 out of 15 networks. All networks have a form of governance in which at least one intensivist is represented. Conclusion: After implementation of the Quality Standard, the presence of networks of intensive care units covering the Netherlands is a fact. The network governance that has developed varies but none of the networks has a governance structure that matches with a proven effective governance structure. Based on theory, the network administrative organisation seems to be the most effective for larger networks, and shared governance for smaller networks

Network governance of Dutch intensive care units:state of affairs after implementation of the Quality Standard

Objective: To study the current state of affairs concerning Dutch intensive care network governance in relation to known effective governance structures of network organisations. Methods: Six characteristics of intensive care networks were defined to determine the four contingency factors from the Provan & Kenis network governance models. The contingency factors were determined for all Dutch intensive care networks. An overview of the networks and characteristics was created by triangulation, using information from two national intensive care network meetings (November 2017 and June 2018) and semi-structured interviews by telephone with 10 network intensivists and / or network managers. Results: Based on the chosen characteristics, none of the Dutch intensive care networks has a governance structure according to one of the Provan & Kenis successful forms of governance. Each of the present networks has a governance structure with elements from two or three different types. Characteristics of the network administrative organisation and shared governance form overlap in 10 out of 15 networks. All networks have a form of governance in which at least one intensivist is represented. Conclusion: After implementation of the Quality Standard, the presence of networks of intensive care units covering the Netherlands is a fact. The network governance that has developed varies but none of the networks has a governance structure that matches with a proven effective governance structure. Based on theory, the network administrative organisation seems to be the most effective for larger networks, and shared governance for smaller networks

Electro-optic techniques for longitudinal electron bunch diagnostics

Electro-optic techniques are becoming increasingly important in ultrafast electron bunch longitudinal diagnostics and have been successfully implemented at various accelerator laboratories. The longitudinal bunch shape is directly obtained from a single-shot, non-intrusive measurement of the temporal electric field profile of the bunch. Further- more, the same electro-optic techniques can be used to measure the temporal profile of terahertz / far-infrared opti- cal pulses generated by a CTR screen, at a bending magnet (CSR), or by an FEL. This contribution summarizes the re- sults obtained at FELIX and FLASH

The Active Recovery Triad (ART) model:A new approach in Dutch long-term mental health care

Unlike developments in short-term clinical and community care, the recovery movement has not yet gained foothold in long-term mental health services. In the Netherlands, approximately 21,000 people are dependent on long-term mental health care and support. To date, these people have benefited little from recovery-oriented care, rather traditional problem-oriented care has remained the dominant approach. Based on the view that recovery is within reach, also for people with complex needs, a new care model for long-term mental health care was developed, the active recovery triad (ART) model. In a period of 2.5 years, several meetings with a large group of stakeholders in the field of Dutch long-term mental health care took place in order to develop the ART model. Stakeholders involved in the development process were mental health workers, policy advisors, managers, directors, researchers, peer workers, and family representatives. The ART model combines an active role for professionals, service users, and significant others, with focus on recovery and cooperation between service users, family, and professionals in the triad. The principles of ART are translated into seven crucial steps in care and a model fidelity scale in order to provide practical guidelines for teams implementing the ART model in practice. The ART model provides guidance for tailored recovery-oriented care and support to this “low-volume high-need” group of service users in long-term mental health care, aiming to alter their perspective and take steps in the recovery process. Further research should investigate the effects of the ART model on quality of care, recovery, and autonomy of service users and cooperation in the triad