With the rapid advances in healthcare technology, the movement to electronic health records, and the relentless accumulation of regulatory requirements, the shift from records management to information governance is increasingly becoming a necessary reality.
In a 2012 CGOC (Compliance, Governance and Oversight Counsel) Summit survey, it was found that on the average 1% of an organization’s data is subject to legal hold, 5% falls under regulatory retention requirements and 25% has business value. This means that 69% of an organization’s ESI is not needed and could be disposed of without impact to the organization. I would argue that for the healthcare industry, especially for covered entities with medical record stewardship, those retention percentages are somewhat higher, especially the regulatory retention requirements.
According to an April 9, 2013 article on ZDNet.com, by 2015, 80% of new healthcare information will be composed of unstructured information; information that’s much harder to classify and manage because it doesn’t conform to the “rows & columns” format used in the past. Examples of unstructured information include clinical notes, emails & attachments, scanned lab reports, office work documents, radiology images, SMS, and instant messages. Despite a push for more organization and process in managing unstructured data, healthcare organizations continue to binge on unstructured data with little regard to the overall health of their enterprises.
So how does this info-gluttony, (the unrestricted saving of unstructured data because data storage is cheap and saving everything is just easier), affect the health of the organization? Obviously you’ll look terrible in horizontal stripes, but also finding specific information quickly (or at all) is impossible, you’ll spend more on storage, data breaches will could occur more often, litigation/eDiscovery expenses will rise, and you won’t want to go to your 15th high school reunion…
To combat this unstructured info-gain, we need an intelligent information governance solution – STAT! And that solution must include a defensible process to systematically dispose of information that’s no longer subject to regulatory requirements, litigation hold requirements or because it no longer has business value.
To enable this information governance/defensible disposal Infobesity cure, healthcare information governance solutions must be able to extract meaning from all of this unstructured content, or in other words understand and differentiate content conceptually. The automated classification/categorization of unstructured content based on content meaning cannot accurately or consistently differentiate the meaning in electronic content by simply relying on simple rules or keywords. To accurately automate the categorization and management of unstructured content, a machine learning capability to “train by example” is a precondition. This ability to systematically derive meaning from unstructured content as well as machine learning to accurately automate information governance is something we call “Predictive Governance”.
A side benefit of Predictive Governance is (you’ll actually look taller) previously lost organizational knowledge and business intelligence can be automatically compiled and made available throughout the organization.
