Three Keys to a Successful Data Governance Strategy

As data becomes more important across healthcare decision making, so does the need for an effective healthcare data governance strategy. Without a data governance strategy tailored to the unique needs of the healthcare organization, the data falls short of its potential to advance processes, workflows, and care delivery. Common challenges to implementing data governance include breaking down long-existing data silos, leadership resistance to new data processes, and the expertise needed to create a healthcare data governance strategy that accounts for massive amounts of data and data sources.

While the above challenges persist, effective data governance can alleviate many of these burdens. Data governance varies depending on the healthcare organization, but, in general, it consists of gathering, securing, and accounting for every piece of data, organizing that data based on level of importance, and distributing data. Therefore, a high-quality data governance strategy allows health systems to maximize their most valuable data sets by delivering relevant analytic insight to decision makers when they need it.

Three Keys to Effective Healthcare Data Governance

Organizations can promote systemwide data-informed decision making by considering three keys to an effective data governance strategy:

#1: Start with the Data Governance Basics

As data has become ubiquitous in healthcare, health systems have learned how to aggregate it, but many struggle to effectively distribute the data so team members can use it in daily practice. Health systems often know they need data governance because it leads to effective, systemwide data use, but the challenges of developing a data governance strategy often discourage organizations.

Health systems can start with fivedata governance basicsto navigate the challenges around creating a data governance strategy. This stepwise approach helps health systems get on the right track toward enterprise data governance and better data access:

1. 识别并调整数据和分析，以支持组织的优先级。
2. Identify the data governance priorities.
3. Identify and recruit the early adopters.
4. Identify the scope of the opportunity appropriately.
5. Enable early adopters to become enterprise data governance leaders and mentors.

#2: Ensure the Data Governance Strategy Supports Sustainable Improvement

Because data reveals variations in care, trends over time, and improvement opportunities, health systems understand that the most meaningful change comes from data insight. Therefore, health systems must realizedata governance’s rolein a system’s overall improvement strategy.

有效的数据治理策略通过包括明确的数据优先级和由参与的管理员和临床医生组成的数据治理机构来支持可持续的改进。在此基础上，数据治理领导者应该采用数据技术和工具，将数据的范围从领导层扩展到各级团队成员。

#3: Align the Data Governance Strategy with Organizational Priorities

医疗保健数据治理领导者应该对其数据治理策略采取灵活的心态。敏捷方法是成功的必要条件，因为数据和团队成员的数据需求会不断变化，需要来自不同领域的数据治理领导者定期协作，讨论策略的变化。One way to successfully shift the data governance strategy is to ensure it is in sync with the health system’sorganizational prioritiesso that it supports high-level goals by maximizing data, team members, and resources (e.g., technology).

一旦数据治理策略与组织的最高优先级一致，领导者就可以建立跨规程的数据治理团队。跨学科团队使卫生系统能够平均分配数据资源，以支持不同的优先事项(如临床、业务和财务)。从那里，被分配的团队成员可以开始使用资源来执行数据治理项目。随着数据治理策略的发展，团队成员应该考虑如何将数据治理工作从单个项目扩展到即将到来的项目和优先级。

Healthcare Data Governance: The Bedrock of Data-Informed Decision Making and Measurable Improvement

数据治理对于确保团队成员能够及时访问他们需要的数据以做出最明智的决策至关重要。大量数据使数据集难以组织，使许多卫生系统的数据操作方法不协调。尽管很难导航—尤其是在治理数据的早期阶段—但有效的数据治理策略提高了数据的易用性，使团队成员更有可能在日常决策过程中使用数据。

The most effective healthcare data governance strategy starts with the data governance basics, focuses on sustainable improvements, and aligns with high-level organizational priorities. This approach moves data from spreadsheets to the point of decision making, where data reaches its full potential to drive change.

Additional Reading

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5. Self-Service Data Tools Unlock Healthcare’s Most Valuable Asset