###### Abstract  
Electronic health records are playing an important role in todays' clinical research, with the possibility to collect a wide amount of data from different sources, not only within a structured clinical setting, but also making best use of new portable technologies, such as smartphones, sensors and Internet-of-Things, as an unprecedented spring of data. In this way, even in small clinical centers, often featuring limited financial availabilities, not only clinicians can have a complete, timely outlook on patients' health, but also data scientists could use such information to build and train tailored models in the broader perspective of \"p4 medicine\". However, all this should align with the strict regulations and needs concerning data privacy and security, safeguarding the rights of the individual and the confidentiality of information related to their healthcare status. Here, we present a case study dealing with Health360, a platform designed to fill in this gap, representing the ideal solution for small clinical centers, where usability and cost-affordability are key characteristics for such a system, to collect multimodal data from various sources actually employed in the framework of neuromuscular conditions. The platform, designed under the Software-as-a-Service paradigm, actually collects data from different clinical centers active in the field of neuromuscular diseases, and therefore was designed to grant access to the data to specific professionals depending on their roles. At the same time, to the benefit of data scientists, Health360 enables joint data processing, with the management of authorization principles for various health professionals from different clinical centers, which is regulated by the data minimization principle, based on the accessing profile. Under such premises, we present here the approach followed for the implementation of the platform, managing the trade-off between the need from various professionals for accessing the complete dataset and the privacy requirements, as well as confidentiality maintenance for sensitive data of patients enrolled on the project. access; data protection; electronic health record; GDPR; healthcare; minimization; privacy; SaaS; security +
Footnote †: journal: Applied Soft  
This leads to a noteworthy asset for the data scientist that should be treated with care, taking into account the authorizations and limitations concerned with the privacy of data and the safeguarding of patients and individuals whose data are being treated [5; 6]. Within such an, often narrow, edge, the software developers operating within the healthcare universe should play their efforts, with attention devoted to patients' data protection and privacy, and at the same time to the optimization of benefits for the clinician, the data scientist and the scientific community at large. At the same time, there is an increasing need, from the clinical centers, to use ICT-based solutions for the agile collection of personal and clinical data. Indeed, several clinical centers, even in technologically advanced countries, still make large use of pen-and-paper clinical data reports, thus resulting in high costs and burden to clinical personnel, especially when dealing with longitudinal data [7]. As such, there is mounting evidence about the advantages of technological support for collecting data [8], driving clinicians to ask for new approaches to their everyday practice. However, not all clinical centers have the possibility to take advantage of complex, exhaustive, well-grounded electronic health records, developed by main international players in the specific sector. This drives many of them to adopt simplified tools, often specifically tailored to one or to a limited group of functionalities, combining ease of use and cost-affordability [9]. The solution presented here, named \"Health360\", able to collect data from a patient or an individual concerning their health at 360 degrees, was developed to fill in this gap.