An effective data governance strategy helps healthcare organizations manage, use, and protect the data in their IT environments. It also helps to create a culture of data-driven decision-making by putting reliable information in the hands of information consumers in a timely manner.
However, there are a host of challenges when it comes to data governance. In this blog post, we’ll take a look at 6 of these challenges, and show you where you can learn best practices as you proceed with your data governance initiative.
Data governance provides framework
By definition, data governance is the foundation for organizing and managing data and information assets across the enterprise. It provides healthcare organizations with a means to integrate both clinical and business policy requirements, and it gives leadership quality information that allows them to make timely decisions for continuous improvement through analytics.
In today’s health practices, analytics is the bridge between information and evidence-driven decisions. Data governance provides the framework for defining the information included in an analytics environment and guides the process of defining information so that information consumers can properly interpret and use it.
Data collected in healthcare organizations is a valuable resource that can help control costs, predict future trends and requirements, and measure performance and outcomes. For example, value-based reimbursement has now increased the importance of data owned by healthcare organizations. As a result, data is no longer just an asset to the organization; it is critical to providing quality care and ensuring desirable outcomes.
6 data governance challenges
Unfortunately, establishing data governance best practices has been a challenge for healthcare providers. This is due to several reasons including:
- Lack of support. Executives and the board often do not provide enough support for a holistic foundation for data governance.
- Allocating resources. Significant staff bandwidth is required for a governance committee, including executives, service leaders, data owners, data stewards, data architects, and data analysts.
- Lack of staff integration. Data owners are too far removed from operations and business activities to be effectively integrated into the solution.
- Little trust in the data. Siloed, inaccurate, inconsistent, and unstandardized data results in lack of trust.
- Difficulty of training. Many organizations lack a strategy for educating, training, and supporting users on data governance practices.
- Inconsistent data protections. Lack of appropriate, consistent data access, restrictions, and protections.
Because these challenges are often new for leadership, even the most experienced CIOs and IT managers often don’t know how to create an efficient, effective strategy because there’s no mechanism for training or experience. As a result, they end up wasting time and resources, which has negative impacts on the organization and can damage the brand. At the same time, IT has no way to perform analysis on the data residing in their systems in any meaningful way.
The knee-jerk reaction is to plug in a technology solution in an effort to solve the problem quickly. However, jumping directly to technology in the hopes of finding that “silver bullet” can backfire. Plug-and-play solutions aren’t enough – data governance requires a strategy. You can’t make progress toward creating a learning health system without laying a solid foundation of information.
Making the most of your data governance
Data governance helps the organization start moving in the right direction and keeps the focus on the highest priorities However, data governance is also part of a larger set of processes that include design, implementation, deployment, knowledge transfer, monitoring and assessment, and more.
To learn more about what sophisticated data governance can do for your healthcare organization, check out our white paper—”How to Accelerate EHR Insights with an Enterprise Analytics Platform.”
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