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Enterprise level data models are uncommon in the healthcare industry, and it can take a long time to build one from scratch. For an organization looking to build an enterprise level meta-data and data model, a practical strategy may be to start with a high ROI data hot spot or a high visibility data specific project. If your organization is looking into revenue management and optimization, this is a wonderful opportunity to start data modeling and management from these subject areas. At the end of the exercise, a clear view of the organization and its data flow should emerge.
When should an organization start building an enterprise level meta-data registry? The answer is now. With meaningful use and the emphasis on health information exchange, data will become increasingly important to an organization. Poor data quality will get noticed and new waves of data projects will begin to surface, but why be reactionary when you can be proactive and start getting results in the near future.
Accurate data can ease the burden on business units, IT, and management. Moreover, data sharing works only if data quality and integrity is maintained, and data quality and integrity work only if a solid enterprise data strategy and framework exists. Integrating data governance and data management as part of project management methodology is a conceivable way to entice project managers to consider, utilize, and maintain the integrity of data.
Remember, just like the blood coursing through our veins, data generation never stops. It's time proactive organizations take a look at building an enterprise level meta-data registry to harness this “unsung” asset-data.
Ajay Khandelwal is manager of enterprise architecture, Children's Hospital Los Angeles. Healthcare Informatics 2011 August;28(8):52-54
