In today's healthcare landscape, data is ubiquitous, encompassing patient records, clinical information, and device-generated intelligence. Yet, harnessing this data for actionable insights remains a formidable challenge. HealthTech companies and healthcare providers, such as the NHS, often struggle to move beyond basic metric reporting to fully leverage the potential of their data. This limited approach has hindered operational efficiencies and innovations in patient care.
Historically, healthcare providers have focused on developing data warehouses for regulatory reporting. This emphasis on compliance has confined the use of data to reporting metrics like emergency wait times, rather than using it to drive efficiencies and improve patient outcomes. Additionally, the healthcare research landscape is fragmented, with data silos in biomedical research centres stalling comprehensive analytics and hampering efforts to enhance research capabilities and outcomes for rare diseases.
The future of healthcare, however, is driven by digitally enabling health and care services around the needs of patients, public and health and care professionals. To truly unlock the power of healthcare data, a shift in perspective and approach is necessary. Integrated Care Systems (ICSs) have been introduced to join-up care across multiple care settings and create improved services which leads to better outcomes for people. Key to the vision of ICSs is ensuring data is joined up across multiple systems to deliver actionable insights, ultimately driving improved outcomes for the population.
A modern data platform can address these challenges by enabling a patient-centric approach. Such a platform integrates disparate data streams to form a single source of truth, allowing analytics tools to uncover relationships that are invisible when data is siloed. This provides healthcare providers with a longitudinal view of each patient's journey, from wellness to acute care. For example, combining device vitals with diagnosis codes can reveal previously hidden comorbidities, facilitating proactive management of chronic conditions and supporting timely clinical interventions.
Operationally, unified real-time analytics can optimise resource utilisation. A comprehensive view of combined capacity across the ICS in real time can help reduce local backlogs and drive down waiting lists. Dashboards that compare units or specialties can identify best practices, while metrics assessing readmission rates or length of stay can highlight areas for quality improvement.
Similarly, a robust analytics strategy with potential to support Machine Learning (ML) and Artificial Intelligence (AI) can help introduce predictive analytics to move from a model of retrospective reporting to actionable insights by providing the necessary foresight.
InterSystems IRIS for Health data provides comprehensive analytics capabilities which embeds four key capabilities – multi-model database, interoperability, real-time and predictive analytics in a single unified data platform. Whether it is integration of device data with patient records for better patient outcomes or integration of disparate diagnostic systems/services for creating a comprehensive view of combined capacity or using healthcare data from electronic health record (HER) systems for research or applying ML/AI on data to identify demand hotspots, InterSystems IRIS for Health can accelerate all these outcomes with its simplicity and scalability.
The key to unlocking population health insights lies in the ability to collect or connect data from different healthcare systems in standardised healthcare formats like HL7v2, HL7 FHIR, DICOM, OMOP etc. and provide a comprehensive view of data in real-time. Also, it integrates analytics seamlessly into clinical and research workflows empowering healthcare organisations to deliver better care both now and in the future.
For clinical research, InterSystems IRIS for Health is a platform that supports both i2b2 tools and the Observation Medical Outcomes Partnership (OMOP) Common Data Model (CDM), and is fully compatible with Observational Health Data Sciences and Informatics ( OHDSI) collaborative open-source tools. It also includes bulk FHIR ingestion capabilities from EHRs and out-of-the-box transformation from FHIR to OMOP, further accelerating the path for researchers to collaborate using data from multiple EHR systems within a region.
In summary, the digital transformation of healthcare demands a reimagining of how data is harnessed. By shifting from mere data collection to meaningful utilisation, healthcare organisations can unlock the full potential of their data. InterSystems' comprehensive analytics solutions offer a robust, integrated approach to overcoming the challenges of healthcare data, paving the way for improved patient care and operational efficiency.
