Healthcare


Data Management, Data Warehousing and Data Lakes—Key Trends and Emerging Strategies amongst Healthcare Providers

Future Healthcare Paradigms like Precision Medicine, Predictive Analytics and Population Health Demand Investment in Big Data, Data Lakes and Platforms that Support Artificial Intelligence
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Published: 18 Jul 2018

Healthcare is an information intensive industry and healthcare data is increasingly being seen as an asset which needs to be invested in for organizations to be able to reap returns. Healthcare providers have started developing data management strategies that revolve around current and future data sources, users and applications. There is a need for healthcare providers to invest across all three domains that would contribute to generating value from data – latest data management and warehousing technologies; skilled human resources for back-end management as well as front-end applications, and innovative workflows and processes. Data management strategies and their implementation require the buy-in of multiple stakeholders who have very diverse goals. Aligning them into a single implementation plan and executing it is a challenge. Such conversations almost always touch upon issues like IT budgets; time spent by clinical resources on technology initiatives and the measurable impact of IT pilots on clinical care and the patient. Data management and data warehousing architecture amongst healthcare service providers is fraught with legacy systems. Modernizing this mammoth is an expensive, time-consuming and laborious exercise. Yet, emerging healthcare paradigms are coercing providers to relook at their data architecture and question whether their existing systems are sufficient to meet the demands of the future or not. Healthcare mega trends, such as, the move towards value-based care; increasing focus on prevention and wellness versus treatment, and evolving regulatory reporting and compliance needs are making solutions that leverage analytics, artificial intelligence (AI), mobile platforms and Internet-of-Things a necessity. Legacy data management systems are built using a piece-meal approach leading to punishing data silos between applications and warehouses. Moreover, quality of data within the organization is often questionable with large pockets of missing, incomprehensible or dark data. Integrating data across the healthcare care continuum is the single most important differentiator between futuristic and stagnant healthcare providers. Emerging technologies like Big Data tools, data lakes and AI-enabled data management platforms address some of these issues and most have common goals, like breaking data silos and making data ready and available for AI. Simultaneously, data governance is of prime import so that organizational data is reliable, accurate and appropriately available to the users based on their roles in the organization. Future of data management strategies lies in enabling a truly patient-centric organization wherein the patient forms the core of the data architecture and all workflows related to data aggregation, storage and application are tied to the patient. In this research, Frost & Sullivan discusses: • The current state and future evolution of data management and data warehousing technologies amongst healthcare providers • Challenges and unmet market needs with respective to provider data management • Emerging technologies and service models in healthcare data management • Strategic imperatives for providers with respect to data management strategies

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      Key Trends and Emerging Strategies amongst Healthcare Providers

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