Intelligent CIO Middle East Issue 23 - Page 93

INTELLIGENT HEALTH “Empowered patients are also asking for faster access to services, personalised experiences, 24/7 access and connectivity, and access on more devices.” But, today’s traditional IT infrastructures often lack the scalability, performance, and analytic capability to support the business strategy and to make timely and targeted care interventions at the point of care. How do healthcare organisations take analytics to the next level to achieve organisational goals for operational efficiencies, predictive care, clinical research, and population health management? The answer is data lakes. discoveries that can impact integrated patient care. into data warehouses purpose-built for historical business intelligence. Data lakes also open up possibilities for integrating information from wearables, fitness devices, appliances built on the Internet of Things (IoT) such as heart monitoring implants, for personalised, real-time care delivery. Adopting a data lake strategy builds on current investments for business intelligence and helps simplify storage, management and analysis of big data through integration of data in real-time, near real-time, or in batch from disparate sources, without impacting day-to-day operations or access to data. Analytics can now become forward-looking and predictive, and complement the business intelligence rear-view mirror. Caregivers can employ advanced analytics to use data generated by these devices to help reduce in-hospital complications and unnecessary readmissions, deliver personalised medicine, identify genetic markers, improve clinical trial safety, and much more. This flexible and reliable platform offers a myriad of new opportunities to find trends and correlations, helping providers to create a data-driven, continuous learning environment. Data Lake platforms provide massive scalability, simple management and operational flexibility – and can be expanded beyond the core data centre experience to extend aggregation and accessibility benefits to both the edge and cloud. Traditionally, healthcare providers have invested substantial time and effort into extracting, transforming, and loading (ETL) data from its original format Moving forward, the use of advanced analytics for next-generation care delivery will become a key differentiator for healthcare providers in this highly competitive marketplace, particularly with the demands of the Information Generation. Transforming into an information-driven and data-focused organisation will be critical to achieve and maintain a competitive advantage. Ultimately, a data lake helps healthcare organisations run their operations as a business. Real-time insights and predictive models mean fewer complications, fewer unnecessary emergency room interventions, and higher levels of wellness across the population; all at a reduced cost. n A data lake provides a powerful data architecture with a unified location to help reduce silos across the healthcare enterprise. Data can also be connected from trusted outside sources including payers, genomic research centres, public health databases, biobanks and social media feeds. The data lake allows for effective cross data analysis and incorporates all internal data sources and trusted external sources for mining and analysis by clinical departments, business analysts, and data science teams. With such future-focused insights, healthcare providers can further advance accountable care initiatives, creating a new realm of data science for uncovering trends, patterns, relationships, correlations, and INTELLIGENTCIO 93