56 research outputs found

    The Uptake and Impact of a Personal Health Record for Patients with Type 2 Diabetes Mellitus in Primary Care: a research protocol for a backward and forward evaluation

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    A Personal Health Record (PHR) is a promising technology for improving the quality of chronic disease management. Despite the efforts that have been made in a research project to develop a PHR for patients with type 2 diabetes mellitus in primary care (e-Vita), differences have been reported between the number of registered users in the participating primary practices. To gain insight into the factors that influence the implementation of the PHR into daily health care processes and into the possibilities to improve the content, interviews have been conducted with participating primary practice nurses and other stakeholders in the research project. A first impression of the interviews indicated that in many cases, the low impact of the PHR is due to a lack of information about the purpose, content and use of the syste

    Personas for Better Targeted eHealth Technologies:User-Centered Design Approach

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    BACKGROUND: The full potential of eHealth technologies to support self-management and disease management for patients with chronic diseases is not being reached. A possible explanation for these lacking results is that during the development process, insufficient attention is paid to the needs, wishes, and context of the prospective end users. To overcome such issues, the user-centered design practice of creating personas is widely accepted to ensure the fit between a technology and the target group or end users throughout all phases of development. OBJECTIVE: In this study, we integrate several approaches to persona development into the Persona Approach Twente to attain a more holistic and structured approach that aligns with the iterative process of eHealth development. METHODS: In 3 steps, a secondary analysis was carried out on different parts of the data set using the Partitioning Around Medoids clustering method. First, we used health-related electronic patient record data only. Second, we added person-related data that were gathered through interviews and questionnaires. Third, we added log data. RESULTS: In the first step, 2 clusters were found, with average silhouette widths of 0.12 and 0.27. In the second step, again 2 clusters were found, with average silhouette widths of 0.08 and 0.12. In the third step, 3 clusters were identified, with average silhouette widths of 0.09, 0.12, and 0.04. CONCLUSIONS: The Persona Approach Twente is applicable for mixed types of data and allows alignment of this user-centered design method to the iterative approach of eHealth development. A variety of characteristics can be used that stretches beyond (standardized) medical and demographic measurements. Challenges lie in data quality and fitness for (quantitative) clustering
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