Community health diagnosis: the new possibilities of digital resources

Introduction: Intervention in the community promotes the empowerment of populations and the updated and indepth health diagnosis of the population is essential. The Centro de Enfermagem da Catolica, extension service of the School of Nursing - Porto (EE) of the Universidade Catolica Portuguesa collaborates with community partners to empower populations and promote more health. We sought to streamline the diagnostic process and explore current aspects of the data collection instrument. Goals: Describe the process of creating and developing an electronic data collection tool for a charitable and social support institution. Identify strengths, weaknesses, opportunities and threats of the digital version of the form. Methodology: Descriptive methodology was used, reporting to the description a construction of data collection instrument. Results analysis and discussion: In the process under description the following steps were identified: Identification of registration needs by the multidisciplinary team; Identification and suitability of platforms; Testing; Instrument construction; Pre-test and team training; Application of the appeal; Conducted SWOT analysis with all stakeholders. In the analysis carried out, the following stand out as strengths: ease in recording answers, paper saving resource, automatic export to editable digital format, grouped questions, intuitive use, online and offline access. The weaknesses highlighted were the need to perform too much field validations, failures in record unsent information. Threats focus on devices battery failure, impaired user communication and lack of technology mastery. Opportunities focus on creating information flows and ease in identifying and correcting errors. Results: The case under study led to the construction of a multidisciplinary data collection form tailored to the needs of users supported by the partner institution. At the end of the process we should note that it takes a large amount of hours to build the instrument and the subsequent automation of the data analysis process. Data collection automation and analysis can be created with free resources available to any user. Conclusion: This work was essential in identifying the various factors that favour and hinder innovation in the population's health diagnosis phase.