EP PerMed has recently awarded the title of “Best Practice” (BP) in Personalised Medicine to the Regional Healthcare Information Platform in Halland, Sweden.
It’s great that Sweden wants to showcase the work we do in Halland beyond the country’s borders. We have a lot to be proud of. Many healthcare providers face significant challenges today, and it’s important that we share the knowledge and capabilities we have built in Halland while also learning from others.
Markus Lingman, Chief strategy officer, Region Halland
© Region Halland | Nelly Andersson
What is this Best Practice about?
As an integrated healthcare system Region Halland has committed to fact-based provision, development and research supported by the wealth of data continuously generated in digitalised healthcare.
For more than a decade Region Halland has built information driven care where data science expertise has been added to traditional healthcare competences. A data infrastructure and architecture enable analysis of patient trajectories in relation to resource utilisation.
A data platform has been built to harbour data from a large number of source systems and support a comprehensive, patient centred, and integrated view of healthcare data across Region Halland beyond silos and knowledge domains. It includes clinical and administrative data for all publicly funded healthcare users, since 2009. The system supports decision-making, research, and policy development by providing a 360-degree view of healthcare delivery. In addition to its central placement and use, the data is used to create tailor-made and actionable dashboards, and other formats as needed.
For the central data platform, on premise computational power grants sovereignty and integrity while enabling a secure environment for collaboration with external parties. Achievements include integration of data from multiple care units, support for research collaborations, and improved data accessibility. Research on real-world data closes the gap between the research and action based on the new insights.
The data constitutes a ground “truth” that can leverage both one-off analyses as well as continuous monitoring of the healthcare system but also advanced predictive multimodal analytics and training and deployment of AI models. The implementation and deployment of these solutions are underway, yet full establishment as a comprehensive and scaled service across the entire platform will remain a work in progress driven by needs. A novel costing model, “patient encounter costing” (PEC), has been developed to trace the costs across the healthcare system related to a specific outcome.
The current focus is on implementation and exploring the development and use of generative AI. The work is done with highly skilled in-house staff in close collaboration with academia focused on creating new knowledge from real-world data.
Collaboration for Implementation
The platform was developed by Region Halland with inspiration from Brigham and Women’s Hospital (currently Massachusetts General Brigham), experts from Harvard Medical School and Harvard Business School. Development involved clinicians, data scientists, economists, and administrators. Collaboration across sectors (internal and external to Region Halland) ensures relevance and utility in clinical practice, innovation and policy. Since its creation the Region Halland infrastructure has brought value to collaborations with a number of care providers, academia and the private sector nationally and has inspired other Swedish regions in their development and roles as health care providers.
Regulatory, Ethical, Legal, Social, Economic Considerations
The platform is compatible with legal and ethical requirements related to data access and privacy including GDPR and is preparing for European Health Data Space (EHDS) as well as the AI Act. It operates within RH’s firewalls and follows strict data governance protocols including a focus on the ethics of insight generation following the data analysis. Data safety and cyber security are continuously monitored by designated legal and IT teams. Research is conducted in line with national and international ethics guidelines and regulations including the Helsinki Declaration. Social and socioeconomic aspects of health care provision are available for investigation. The role of being a public provider ensures transparency and democratic insight. Economic analyses are supported to evaluate cost-efficiency of activities within the health care system.
Equity, Diversity and Gender Considerations
The platform includes demographic data and supports analyses of healthcare access and health utilisation across age, gender, and other social factors. It takes a global approach which enables equity-focused research and policy development. It covers a geographic population of Halland fully i.e. all aspects of equity, diversity or gender (without selection bias). Development of AI applications and modelling considers the FAIR principles.
A National and International Initiative
The platform contributes to global discussions on healthcare data infrastructure, resource utilisation including work force planning, and precision medicine. There are ongoing national and international cross-sectorial collaborations with academic partners, pharma industry, Swedish regions and authorities, parties in Canada and U.S., as well as and The World Health Organisation.
Scalability and Transferability
The non-proprietary architecture is scalable to other regions and adaptable to different healthcare systems. Its modular design and emphasis on interoperability makes it transferable.
What is the Impact of this BP?
Using holistic data to inform decisions on the individual as well as system´s level assists in prioritising initiatives. Providing a deep fact-based understanding of a complex integrated care ecosystem leads to improved collaboration and have faith in choices and decisions made.
The platform enables better-informed decisions for clinicians and policymakers, leading to more effective and cost-efficient care. Informed decisions empower the organisation towards proactivity with the help of prediction models.
The platform supports research on disease patterns, healthcare utilisation and treatment outcomes.
For patients, it contributes to safer, more personalised care. Of benefit for the organisation, it provides direction for improved resource utilisation and improved work force planning.
For personalised medicine, it provides infrastructure for data-driven insights, innovation and downstream applications in multiple medical fields
What next?
Future plans involve expanding interoperability, enhancing analytical and translational capabilities, to continuously support downstream personalised medicine initiatives.