Background: Quality Improvement (QI) is the key for every healthcare organization. QI programs may help healthcare professionals to develop the needed skills for interprofessional collaboration through interprofessional education. Furthermore, the role of diversity in QI teams is not yet fully understood. This evaluation study aimed to obtain in-depth insights into the expectations and experiences of different stakeholders of a hospital-wide interprofessional QI program. Methods: This qualitative study builds upon 20 semi-structured interviews with participants and two focus groups with the coaches and program advisory board members of this QI program. Data were coded and analyzed using thematic analysis. Results: Three themes emerged from the analysis: “interprofessional education”, “networking” and “motivation: presence with pitfalls”. Working within interprofessional project groups was valuable, because participants with different experiences and skills helped to move the QI project forward. It was simultaneously challenging because IPE was new and revealed problems with hierarchy, communication and planning. Networking was also deemed valuable, but a shared space to keep in contact after finalizing the program was missing. The participants were highly motivated to finish their QI project, but they underestimated the challenges. Conclusions: A hospital-wide QI program must explicitly pay attention to interprofessional collaboration and networking. Leaders of the QI program must cherish the motivation of the participants and make sure that the QI projects are realistic.
Background: Quality Improvement (QI) is the key for every healthcare organization. QI programs may help healthcare professionals to develop the needed skills for interprofessional collaboration through interprofessional education. Furthermore, the role of diversity in QI teams is not yet fully understood. This evaluation study aimed to obtain in-depth insights into the expectations and experiences of different stakeholders of a hospital-wide interprofessional QI program. Methods: This qualitative study builds upon 20 semi-structured interviews with participants and two focus groups with the coaches and program advisory board members of this QI program. Data were coded and analyzed using thematic analysis. Results: Three themes emerged from the analysis: “interprofessional education”, “networking” and “motivation: presence with pitfalls”. Working within interprofessional project groups was valuable, because participants with different experiences and skills helped to move the QI project forward. It was simultaneously challenging because IPE was new and revealed problems with hierarchy, communication and planning. Networking was also deemed valuable, but a shared space to keep in contact after finalizing the program was missing. The participants were highly motivated to finish their QI project, but they underestimated the challenges. Conclusions: A hospital-wide QI program must explicitly pay attention to interprofessional collaboration and networking. Leaders of the QI program must cherish the motivation of the participants and make sure that the QI projects are realistic.
Aim: To evaluate healthcare professionals' performance and treatment fidelity in the Cardiac Care Bridge (CCB) nurse-coordinated transitional care intervention in older cardiac patients to understand and interpret the study results. Design: A mixed-methods process evaluation based on the Medical Research Council Process Evaluation framework. Methods: Quantitative data on intervention key elements were collected from 153 logbooks of all intervention patients. Qualitative data were collected using semi-structured interviews with 19 CCB professionals (cardiac nurses, community nurses and primary care physical therapists), from June 2017 until October 2018. Qualitative data-analysis is based on thematic analysis and integrated with quantitative key element outcomes. The analysis was blinded to trial outcomes. Fidelity was defined as the level of intervention adherence. Results: The overall intervention fidelity was 67%, ranging from severely low fidelity in the consultation of in-hospital geriatric teams (17%) to maximum fidelity in the comprehensive geriatric assessment (100%). Main themes of influence in the intervention performance that emerged from the interviews are interdisciplinary collaboration, organizational preconditions, confidence in the programme, time management and patient characteristics. In addition to practical issues, the patient's frailty status and limited motivation were barriers to the intervention. Conclusion: Although involved healthcare professionals expressed their confidence in the intervention, the fidelity rate was suboptimal. This could have influenced the non-significant effect of the CCB intervention on the primary composite outcome of readmission and mortality 6 months after randomization. Feasibility of intervention key elements should be reconsidered in relation to experienced barriers and the population. Impact: In addition to insight in effectiveness, insight in intervention fidelity and performance is necessary to understand the mechanism of impact. This study demonstrates that the suboptimal fidelity was subject to a complex interplay of organizational, professionals' and patients' issues. The results support intervention redesign and inform future development of transitional care interventions in older cardiac patients.
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Effectiveness of Supported Education for students with mental health problems, an experimental study.The onset of mental health problems generally occurs between the ages of 16 and 23 – the years in which young people follow postsecondary education, which is a major channel in ourso ciety to prepare for a career and enhance life goals. Several studies have shown that students with mental health problems have a higher chance of early school leaving. Supported Education services have been developed to support students with mental health to remain at school. The current project aims to study the effect of an individually tailored Supported Education intervention on educational and mental health outcomes of students with mental health problems at a university of applied sciences and a community college. To that end, a mixed methods design will be used. This design combines quantitative research (Randomized Controlled Trial) with qualitative research (focus groups, monitoring, interviews). 100 students recruited from the two educational institutes will be randomly allocated to either the intervention or control group.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
