This chapter discusses the efforts of community workers to obtain consent in local communities as a basis for taking action on issues that are affecting local people’s lives. Crucial here is that community workers resist the initial urge to settle for consensus and as a consequencelimit the possibilities for creativity, exploration and interpersonal development. Drawing on two case studies, one from Amsterdam (the Netherlands) and one from Chelsea (US), the requirements and process of acquiring consent are outlined. Consent in general refers to a form of permission to act or take action. In this chapter we consider it as a sense of approval by neighbourhood community members to engage in a collective course of action. Community workers often play a crucial part in the acquisition of community consent as they support the process of recognition of the diversity of interests, opinions and values that characterises local life. Consent is necessary for creatingsustainable local initiatives, incorporating, instead of eliminating, conflicting positions. This acknowledgement of diversity can be seen as an ethical requirement in community development practice, but also as a strategic issue for community workers. After all, without being able to obtain legitimacy for their engagement with local issues, effective community development work is impossible.This chapter focuses on neighbourhood-based community development work in geographical communities. However, similar principles apply in all forms of community development, including work with communities of interest and identity. We use the term‘community worker’ to refer to someone who takes on a facilitating and coordinating role with members of communities to build community capacity and/or bring about social change. Such workers may be paid and professionally qualified, or unpaid volunteers andactivists. They may live in the communities where they work/are active, or reside outside these areas. These circumstances influence the legitimacy of their interventions, as well as how consent is gained and consensus reached.
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Process Mining can roughly be defined as a data-driven approach to process management. The basic idea of process mining is to automatically distill and to visualize business processes using event logs from company IT-systems (e.g. ERP, WMS, CRM etc.) to identify specific areas for improvement at an operational level. An event log can be described as a database entry that signifies a specific action in a software application at a specific time. Simple examples of these actions are customer order entries, scanning an item in a warehouse, and registration of a patient for a hospital check-up.Process mining has gained popularity in the logistics domain in recent years because of three main reasons. Firstly, the logistics IT-systems' large and exponentially growing amounts of event data are being stored and provide detailed information on the history of logistics processes. Secondly, to outperform competitors, most organizations are searching for (new) ways to improve their logistics processes such as reducing costs and lead time. Thirdly, since the 1970s, the power of computers has grown at an astonishing rate. As such, the use of advance algorithms for business purposes, which requires a certain amount of computational power, have become more accessible.Before diving into Process Mining, this course will first discuss some basic concepts, theories, and methods regarding the visualization and improvement of business processes.
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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.
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