Abstract
Background: The integration of digital solutions is a cornerstone of modern integrated care, enabling enhanced coordination, communication, and personalized care across health systems. Digital health innovations are increasingly recognized as crucial for improving the efficiency and quality of care delivery, reducing fragmentation, and empowering patients to take an active role in managing their health (1). The International Foundation for Integrated Care (IFIC) emphasizes the significance of digital solutions in pillar 7 of the nine pillars of integrated care.
The need for structured, effective data management frameworks is underscored by the complexity of modern health systems, where digital solutions must comply with evolving data protection laws such as the General Data Protection Regulation (GDPR) and emerging requirements like the AI Act. Without robust data governance, these systems face challenges in ensuring privacy, security, and ethical data use while striving to achieve integrated care goals.
Approach: The "Integrating Data in Integrated Care" (IDIC) methodology, developed during the EU funded ValueCare Project (https://projectvaluecare.eu/), responds to these challenges, offering a structured reference model for data governance that aligns with European legislation.
The IDIC methodology is organized around the data life cycle of digital health projects, addressing the specific data management needs of Integrated Healthcare systems (IHC).
The IDIC methodology responds to two major challenges:
1.Privacy, ethical, and legal requirements: Ensuring GDPR compliance, defining clear roles for data governance, safeguarding against bias, and implementing privacy-by-design principles.
2.Patient and technology-centered challenges: Addressing data fragmentation, enhancing data quality, and empowering patients by giving them control over their data, all of which are critical to the success of digital health solutions.
IDIC organizes data management into two core categories:
1.Project Design, Dissemination, and Knowledge Data: Including co-design data from focus groups; dissemination and communication data, including databases with stakeholders’ details and knowledge produced during the project (i.e. intervention models, algorithms).
2.Patient Data in IHC Pilots: Including patient personal data (i.e demographic data gathered during recruiting phases), medical devices data (collected from monitoring devices), wellbeing data from personal devices (pedometers, apps, etc.)., interaction data (self-input data, interactions with chatbots, preferences, etc.), implementation data (record keeping, appointments, coordination meetings, etc).
For each category, the methodology emphasizes:
- Data size and format;
- Storage and backup strategies;
- Retrospective or prospective datasets organisation;
- Different roles of individuals and organisations involved in data management;
- Compliance with the FAIR (Findable, Accessible, Interoperable, Reusable) principles;
- Strategies for consent, data sharing and multi-center pilot implementation;
- Ethical and legal issues;
- Long term preservation of data;
Results and implications: The IDIC framework provides a replicable, GDPR-compliant approach for data management in IHC projects. IDIC ensures that patient rights are preserved while supporting the deployment of digital solutions, while promoting the IHC agenda. IDIC offers a valuable tool for the digital transformation of health systems, aligning with the broader goal of integrating care through advanced data governance practices.
References:
1.Colnar S, et al. Digital transformation of integrated care: Literature review and research agenda. IFAC-PapersOnLine. 2020;53(2):16890-5.