Keep up with the latest on information governance as this key strategy emerges for addressing a myriad of information management challenges in healthcare. This blog will highlight the trends and opportunities IG presents for ensuring information is treated as an organizational asset.
By Lydia Washington, MS, RHIA, CPHIMS
Data governance is a hot topic these days, as healthcare organizations begin to realize that the analytics capabilities that are necessary for new care and payment models are not feasible without some sort of unified and consistent enterprise approach to data management. Building an effective data governance (DG) capability is part of, and should be integrated with, the organization’s larger information governance (IG) strategy. Many use the terms “data governance” and “information governance” interchangeably, but these two concepts are actually very different (although closely related) concepts. DG and IG are distinct in focus, scope of activities, and reach. AHIMA takes a closer look at the distinctions in a new infographic available at www.IGIQ.org.
IG and DG are co-dependent upon each other. The same structures and functions that are necessary for IG—leadership, alignment with strategy, stakeholder engagement, workforce awareness, and operating polices are also necessary for effective DG. On the other hand, there is no information if there is no data—data are the building blocks for information. Functions such as lifecycle management, protections, and privacy are just as critical for data as for information. Information governance provides the framework and accountabilities to support and promote data governance.
In terms of the distinction in focus and scope of activities between the two, I like the distinction Merida Johns draws in her book, Enterprise Health Information and Data Governance—that data governance primarily addresses system INPUTS—those highly granular pieces of data—while information governance primarily addresses the system OUTPUTS AND USES of information. Thus, data governance deals with things like data models, metadata, master data, data standards, data dictionaries, and the other business processes and functions in which and by which data is created. On the output side, IG—which is broader—is more about how information is shared and disclosed for all sorts of uses such as patient care, compliance, legal purposes, protecting privacy, retention, and preservation. Health information exchange, records management, content management and intellectual property (IP) management also fall within the domain of IG.
Like information governance, DG requires the engagement and collaboration with business process owners and stewards. It must move beyond the sole purview of IT if the organization is to have the necessary capabilities for analytics.