Guide for Handling Both Organized and Disorganized Data in Healthcare Institutions
In the vast world of healthcare, unstructured data—comprising medical images, written narratives like clinical notes, problem lists, discharge summaries, and radiology reports—plays a significant role. Accounting for 80% of all clinical content, this data type poses unique challenges for management and analysis.
Data governance is the key to navigating these challenges, ensuring data accuracy, security, compliance, and usability. By establishing a governance framework, healthcare organisations can maintain consistency and adhere to regulations such as HIPAA and GDPR.
A governance framework involves creating policies, procedures, and standards specifically designed for managing unstructured data. This includes data quality management, security, privacy, ownership, and access controls to ensure compliance with healthcare regulations.
Identifying where patient-sensitive unstructured data resides and tagging it appropriately is another essential aspect of data governance. This helps build a risk profile and apply the proper security and privacy controls.
Implementing access controls and security measures, such as authentication, authorization, audit trails, and data masking, protects patient privacy and reduces breach risks. Metadata enrichment and data lineage tracking, which involves attaching metadata to unstructured data, increase its discoverability and reuse while maintaining transparency about data origin and transformations.
With proper governance, unstructured healthcare data can be securely leveraged to enable AI-driven insights, improving diagnostics, treatment planning, and operational efficiency without compromising patient confidentiality.
Moreover, data governance helps healthcare organisations meet complex privacy and data handling regulations by controlling how unstructured patient data is accessed, shared, and stored. This ensures compliance with data protection laws, transforming unstructured healthcare data from a liability into a strategic asset.
However, the proliferation of unstructured data in healthcare also presents challenges related to data retention, purging, and destruction. According to Brian Laberge, a Solution Engineer at Wolters Kluwer, the issue isn't the amount of data that must be stored or the length of time it must be stored, but rather where it has been stored and what has been stored.
Working with unstructured data in healthcare presents challenges due to its large storage requirements and the need for processing or "normalization" before it can be read by machines. Despite these challenges, the benefits of effective data governance in healthcare are clear: a secure, organized, and trustworthy data environment that enhances healthcare outcomes and system performance.
[1] Healthcare IT News. (2021, January 13). Healthcare's unstructured data problem. Retrieved from https://www.healthcareitnews.com/news/healthcares-unstructured-data-problem [2] McKinsey & Company. (2020, October 13). A new approach to managing unstructured data in healthcare. Retrieved from https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/a-new-approach-to-managing-unstructured-data-in-healthcare [3] Wolters Kluwer. (n.d.). Healthcare unstructured data management. Retrieved from https://www.wolterskluwer.com/en/solutions/clinical-document-archiving [4] American Hospital Association. (n.d.). Data-driven healthcare. Retrieved from https://www.aha.org/topics/data-driven-healthcare
In the realm of healthcare, effective data governance is crucial for managing unstructured data associated with medical-conditions and health-and-wellness, ensuring compliance with regulations like HIPAA and GDPR. This strategy involves creating policies, procedures, and standards specifically designed to handle such data, implementing access controls and security measures, and tagging sensitive patient data appropriately.
By establishing a governance framework, healthcare organizations can also meet complex privacy and data handling regulations, transforming unstructured healthcare data from a liability into a strategic asset by leveraging it for AI-driven insights, improving diagnostics, treatment planning, and operational efficiency without compromising patient confidentiality.
