Data is one of the most valuable assets in any organization and is necessary to sustain current and future business models. As healthcare transitions into a more analytically driven industry, managing data is especially relevant. Organizations are grappling with ways to manage continual changes in health information technology (IT), IT infrastructure, and the huge volume of data collected across the healthcare industry. The push toward value-based care has amplified the need for efficient exchange of quality patient data, which fills gaps in information and offers providers and payers a more complete picture of the patient. Data-centric strategies focused on managing the entire lifecycle of healthcare data are particularly important in today’s environment.

The policies and procedures to manage, protect, and govern information across a healthcare enterprise falls under data governance. Data governance includes data modeling, data mapping, data audit, data quality controls, data quality management, data architecture, and data dictionaries. A strong data governance structure is a critical component of any healthcare organization, as it provides a structure for analytics and other complex data initiatives.

In Spring 2018, eHealth Initiative Foundation and the LexisNexis® Risk Solutions healthcare business hosted the first in a series of roundtable meetings on data governance in healthcare. The meeting convened senior executives from stakeholder groups, including payer, provider, professional organizations, health information exchanges (HIEs), research, public health, laboratory, and pharmaceuticals. The goal of the meeting was to gather expert opinions on how to make data accessible, close quality gaps, turn insight into action, and protect sensitive patient information. This brief addresses the value of data governance in healthcare; existing challenges related to data governance; and key takeaways from the meeting.