In this context, the Local Health Unit of Salerno’s Department of Mental Health has strategica lly implemented its planning in accordance with the guidelines outlined by the NAPMH. This initia t ive entails enhancing information systems through the integratio n of scientific evidence and research within the field of Mental Health. The overarching objective of this project is to enhance the therapeutic services available, addressing the surge in psychological distress resulting from the ongoing epidemic. The focus is on the Regional Residential Center for Eating Disorders ‘Mariconda’ in Salerno, an integral component of the Regional Network for Eating Disorders in the Campania Region. This concerted effort aims to strengthen the mental health support infrastructure and ensure an effective response to the escalating challenges posed by the current public health situation. This project therefore aims to achieve, among other objectives, the following strategic/operational goals:

● Updated mapping of all services in the territorial network;

● Access functionality to the care-taking archives, providing information on active health services and the status of the individual within their own care setting;

● Management and monitoring dashboard;

● System for receiving and sending notifications integrated with the transitions dashboard;

● Privacy and data security;

● Reporting and flow generation

To achieve these objectives, we have developed, in collaboration with IT.Svil s.r.l., a data-driven ecosystem called the Master Data Platform (MDP). This approach will enable us to utilize an objective decision-making algorithm that is “data-driven” rather than relying on subjective judgments prone to operator-dependent errors. Furthermore, this multimedia platform allows us to access and share real-time patient data. Not only does this platform aim to collect, store, organize, and process valuable data securely across the hospital and university network of the Campania Region regarding EDs, but it also aims to aid through AI to physicians involved in care pathways across different healthcare settings. MDP is designed to be an important resource for patients and their families.

For individuals struggling with AN, MDP will go beyond mere calorie counting, analyzing data on their social anxieties, underlying depression, and exercise preferences, creating a personalized therapy plan that addresses these intertwined factors.The chatbot feature will provide education on healthy eating, body image distortion, and the importance of building a positive relationship with food. Regarding people suffering from BN, MDP will recognize the complex cycle of binging and purging, focusing on developing coping mechanisms for emotional regulation and reducing self-critical thoughts.The platform’s AI capabilities will help identify triggers and suggest tailor-made mindfulness and relaxation techniques. Additionally, the chatbot will offer insights on managing binge urges and developing healthy purging alternatives. For individuals experiencing frequent episodes of binge eating, MDP will prioritize identifying and addressing underlying emotional distress.The platform will use data to personalize nutritional counseling, focusing on creating balanced meal plans and establishing healthy eating patterns.The chatbot will educate on mindful eating practices and provides support for overcoming emotional triggers associated with binging. MDP will go beyond leveraging data and technology by fostering active patient participation. By giving patients and families access to valuable information and resources, MDP will empower them to become active partners in their recovery journey. This collaborative approach enhances engagement, motivation, and the likelihood of achieving sustainable, long-term recovery. MDP recognizes the vital role of human connection in the recovery process, facilitating open communication between patients, families, and healthcare professionals. This supportive network is crucial for promoting healing and preventing relapse. Understanding that EDs are complex, MDP integrates data-driven personalization with a holistic approach that addresses both physical and mental health needs.

The system will be able to integrate with various regional and corporate healthcare systems of interest (e.g., patient registries, hospital admission management systems, etc.).

MDP is also designed to minimize treatment shedding and provide comprehensive coping options through a scalable, flexible architecture that prioritizes interoperability with various healthcare systems.

Interoperability will be integrated with healthcare systems for centralized, accessible patient data, ensuring coordinated care. The Real-Time Data Analysis will allow immediate treatment adjustments based on current patient status. The Personalized Treatment Plans will see a data-driven algorithm to tailor treatment plans to individual needs, enhancing relevance and adherence. The Patient and Family Engagement will provide valuable information and resources via an interactive chatbot, fostering active participation and support. The coping options provided by MDP will include educational resources that guide patients on healthy eating, exercise, coping strategies, and crisis protocols. It facilitates support networks by enhancing communication between patients, families, and healthcare professionals, providing essential emotional and psychological support. MDP takes a holistic approach by integrating mental and physical health needs. It also uses AI-assisted guidance to deliver evidence-based recommendations tailored to individual patient needs. Additionally, the platform includes real-time monitoring and alerts to track patient progress and ensure timely interventions.

This project aims, in a futuristic manner, to develop an MDP platform specifically designed for the management and treatment of eating disorders for the first time in a territorial psychiatric care context. The objectives we aim to achieve include creating a more accessible and welcoming environment for people with ED, thanks to a change in perspective that allows patients to be active participants in dialogues with both the program’s chatbot and various operators. Additionally, a better customization of treatments is expected, as each patient’s data will be available to attending physicians, replacing the paper medical record. Moreover, the program will take into account a range of psychosocial variables that can improve treatment adherence, quality of life, and hopefully patient satisfaction with the service. Another important outcome expected is more effic ie nt management of waiting lists, minimizing delays in accessing care. This will be made possible by a streamlined and responsive system that will ensure timely attention and support to those in need. Another key result is the adaptation of mental health center care plans to individua l needs and the optimal alignment of care intensity with the specific needs of each case.

This project seeks to elevate the quality of mental healthcare for patients with eating disorders. Through meticulous evaluations of admissions and transfers between facilities, we can guarantee care that prioritizes the individual patient’s needs. Robust data governance measures will be established to safeguard sensitive information and set a benchmark for responsible data management within mental health. Integration of artificial intelligence (AI) into clinical processes promises enhanced diagnostic accuracy and overall efficiency. The project strives to achieve high-quality, technology-driven care that empowers both physicians and patients. This collaborative approach will enable patients to feel actively involved in their recovery journey. Additionally, the project aims to raise awareness regarding the significance of implementing a comprehensive range of care options, encompassing outpatient, semi- residential, and residential programs, to best serve patients with eating disorders across the region.

The development of such a platform and the optimiza t ion of care, as well as the involvement and increased ease of data sharing among multiple facilities located in different parts of the territory, would promote expansion of the centralized Hub and consequently a dynamic bidirectional flow of information and resources, facilitating collaboration and resource sharing among healthcare providers. The expected outcome of the departmental Hub is the effective monitoring of user clusters in all Spoke facilities. Regular reports disseminated to the Spoke will mean transparency and a cohesive approach to mental health care.

The project aims to create an MDP platform for managing EDs within territorial psychiatric care. Its benefits include fostering a welcoming environment that enhances patient engagement and satisfaction. Digital medical records will facilitate personalized treatments, strong data governance measures will protect sensitive information, while a collaborative approach empowers patients and healthcare providers. A centralized Hub will promote dynamic information flow, resource sharing and systematic monitoring with regular reporting to maintain cohesive mental health care. However, there are still many challenges: managing digital patient data demands stringent cybersecurity to prevent breach; developing and integrating the platform into existing systems can be complex and resource-intensive. Ensuring access to technology for all patients and facilities, especially in under-resourced areas, could be difficult. There might be resistance to transitioning from traditional methods to a technology-driven approach, necessitating change management efforts. The project’s costs, including setup, maintenance, and upgrades, require sustainable funding. Seamless integration with current health records and care systems may present technical challenges, and staff will need extensive training. Over-reliance on digital solutions could lead to vulnerabilities in case of technology failures or cyberattacks. Ethical considerations around consent, data ownership, and potential misuse of AI and digital data also need to be addressed. The transformative potential of the project to improve the treatment of EDs through innovative, patient-centered technology will overcome these challenges, offering a promising pathway to more effective and integrated mental health services.

FM: Conceptualization, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing. AV: Conceptualization, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing. MP: Investigation, Supervision, Visualization, Writing – review & editing. CP: Conceptualization, Project administration, Resources, Writing – review & editing. CM: Methodology, Project administration, Visualization, Writing – review & editing. LS: Supervision, Validation, Visualization, Writing – review & editing. AM: Writing – review & editing. FF: Writing – review & editing. GP: Conceptualization, Data curation, Methodology, Writing – review & editing. SL: Writing – review & editing. EF: Visualization, Writing – review & editing. SP: Visualization, Writing – review & editing. VM: Supervision, Validation, Writing – review & editing. MS: Supervision, Validation, Visualization, Writing – review & editing. AMM: Supervision, Validation, Visualization, Writing – review & editing. AF: Supervision, Validation, Visualization, Writing – review & editing. GC: Resources, Supervision, Visualization, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.