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What are the key functions of data management?

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What are the key functions of data management?

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The data management function is a core set of business processes, such as Finance, Human Resources, or Facilities Management, that provides resources to facilitate the establishment and adoption of best practises across data management disciplines and will always be required throughout the entire lifecycle of patient demographic data.

The scope of the data management function will vary based on the organization's size and the extent of its authority over patient demographic data assets. In a modest organisation, this function may be performed by a single individual on a part-time basis. For larger organisations with a broader scope of data governance, a multi-person organisation may be necessary. Nonetheless, the central idea is to assign responsibility for work products that an organisation constructs and maintains over time. These deliverables may include data management policy and process documentation as well as quality standards designed to enhance the quality of patient demographic data.

Data management encompasses a range of activities and processes aimed at effectively handling data throughout its lifecycle. The key functions of data management include:

Data Collection: The process of gathering data from various sources, such as databases, applications, sensors, or external systems. It involves identifying the relevant data sources, ensuring data quality and accuracy, and extracting the required information.

Data Storage: The function of storing data in a structured manner to facilitate easy access, retrieval, and manipulation. This involves selecting appropriate storage technologies, such as databases, data warehouses, or cloud storage, and implementing efficient data organization strategies.

Data Integration: The process of combining data from different sources and formats into a unified view. It involves transforming and mapping data to ensure consistency, resolving data conflicts, and creating a comprehensive and coherent data repository.

Data Quality Management: The function of ensuring that data is accurate, complete, consistent, and reliable. It includes data cleansing, validation, standardization, and the establishment of data quality rules and metrics. Data quality management aims to enhance data integrity and usability.

Data Security: The practice of safeguarding data against unauthorized access, breaches, or loss. It involves implementing security measures, such as access controls, encryption, data masking, and regular backups. Data security also includes compliance with relevant regulations and privacy policies.

Data Governance: The establishment of policies, standards, and procedures for managing data assets. Data governance ensures data is used, stored, and shared appropriately, and that data-related decisions align with business objectives and legal requirements. It involves defining data ownership, roles, responsibilities, and data management frameworks.

Data Analytics: The process of extracting insights and knowledge from data to support decision-making and drive business outcomes. It includes techniques such as data mining, statistical analysis, machine learning, and predictive modeling. Data analytics helps uncover patterns, trends, and correlations within the data.

Data Privacy and Compliance: The function of ensuring compliance with privacy regulations, such as the General Data Protection Regulation (GDPR) or the Health Insurance Portability and Accountability Act (HIPAA). It involves implementing data anonymization, consent management, data retention policies, and auditing mechanisms to protect individuals' privacy rights.

Data Archiving and Retention: The practice of storing and preserving data for long-term retention, regulatory compliance, or historical reference. Archiving involves moving infrequently accessed data to cost-effective storage, while retention policies define how long data should be retained and when it can be safely deleted.

Data Access and Sharing: Enabling authorized users to access and share data securely. This involves managing user permissions, implementing data access controls, establishing data sharing agreements, and providing mechanisms for data collaboration and dissemination.

These functions collectively ensure the availability, integrity, security, and usability of data, enabling organizations to leverage their data assets effectively and make informed decisions.


Jul 7, 2023