Case study
Intelligent Data Ecosystem of the Madrid Health Service (SERMAS)
New technologies are transforming how the healthcare sector manages crises such as pandemics. The need to integrate disparate data is forcing the optimization of analysis and decision-making based on artificial intelligence.
The COVID-19 pandemic in the Community of Madrid has highlighted the importance of unifying clinical information from multiple sources to effectively combat the virus. Virtual Desk has implemented its Big Data on Cloud Platform solution in the Madrid Health Service (SERMAS), integrating data from primary care, specialized care, public health, and pharmacy, improving pandemic management and enabling the development of use cases with advanced analytics to focus on what matters most: the health of citizens.
Case studies
Integrating heterogeneous information from multiple systems was a critical challenge in combating the pandemic
+ 5M €
In annual costs
90%
Prolonged delays
100%
Lack of interoperability
Integrating heterogeneous information from multiple systems was a critical challenge in combating the pandemic
- Inefficient processes: Data scattered across different systems caused delays in analysis and difficulties in obtaining real-time insights.
- Lack of integration: Existing systems did not allow for the agile unification of clinical information, limiting the response to the crisis.
- Growing demand: The pandemic required a rapid analysis of contagion patterns, comorbidities, and external factors for effective management.
- Operational complexity: Handling massive volumes of heterogeneous data, with millions of variables, represented a challenge for applied artificial intelligence.
Virtual Desk developed and implemented a Big Data on Cloud Platform, based on IBM's Cloud Pak for Data (CP4D) solution, which includes:
- Total integration: Unification of primary care data, hospital GIS systems, Public Health alerts and pharmacy to form the RCPC (COVID Patient Clinical Registry).
- Advanced analytics: Tools to develop use cases related to COVID, applying artificial intelligence.
- Cloud infrastructure: Scalable deployment that allows for the efficient ingestion and processing of heterogeneous data.
- Regulatory compliance: Security measures aligned with regulations such as the GDPR to protect sensitive patient data.
- Flexibility and adaptability: Designed to evolve with new analytical needs and changes in the pandemic
Our platform guarantees accurate, real-time data exchange between institutions, improving reliability and providing a more efficient service for dependent individuals.
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