Modern Data Platforms: Enhancing Healthcare's Agility Through Advanced Data Management Solutions
In the rapidly evolving landscape of healthcare, the importance of effective data governance cannot be overstated. Data governance serves as the bedrock for modern healthcare data platforms, ensuring that clinical and organizational data are accurate, complete, consistent, secure, and used appropriately throughout their lifecycle.
According to Keith Olenik, chief health information officer of the American Health Information Management Association, the modern data platform should eliminate barriers to access, especially for external data sources. This is crucial as up to 97% of hospital data goes unused due to proprietary systems or silos.
Modern healthcare data platforms, such as electronic health records (EHRs), clinical data warehouses, and AI-enabled systems, depend heavily on strong data governance to function optimally. Data governance provides the foundation for managing vast and diverse datasets collected by these platforms.
Data quality and accuracy are paramount in patient care and research. Governance ensures that the data used in both care and research is trustworthy. It also enables interoperability and integration among disparate healthcare systems by setting standards for data formatting, terminologies, and exchange protocols.
Moreover, data governance is essential for preventing issues like duplicate records, billing errors, and care coordination problems. It also supports data-driven decision-making, clinical research, and performance monitoring. Compliance with regulations such as HIPAA is also ensured through effective data governance.
Data governance also oversees data stewardship—assigning experts to maintain quality in specialized data domains (clinical, administrative, etc.). It also supports secondary uses of data for research and innovation, including AI model development.
In summary, data governance acts as the bedrock for modern healthcare data platforms, enabling them to leverage data securely and effectively for patient care, research, operational efficiency, and emerging technologies like AI.
The principles of DevOps and DataOps align well with the modern data platform, potentially enabling self-service analytics and reducing the need for a background in data science. The continued evolution of automation technology may further streamline data management processes.
References: [1] Olenik, K. (2021). The Operational Perspective in Data Management. Healthcare IT News. [2] Shannon, J. (2020). The Role of Vendor Partners in Data Management. Healthcare Analytics & Insights. [3] World Economic Forum. (2020). The Future of Health is Digital: Harnessing Data for Better Health Outcomes. [4] Krishnan, A. (2021). The Transformative Potential of Modern Data Platforms. Forbes. [5] HealthIT.gov. (2021). Data Governance in Healthcare. U.S. Department of Health and Human Services.
In the context of modern healthcare, data-and-cloud-computing technology plays a vital role in ensuring the effectiveness of data governance, which is instrumental in managing vast, diverse datasets collected by platforms like electronic health records, clinical data warehouses, and AI-enabled systems. Effective data governance also fosters data quality, accuracy, interoperability, and compliance with regulations such as HIPAA.
Furthermore, the principles of DataOps, with its potential for self-service analytics and reduced reliance on data science background, nicely align with the modern data platform, and the continued evolution of automation technology may further streamline data management processes in the realm of data-and-cloud-computing.
