Five Practical Steps Towards Healthcare Data Governance

Asdatagains more prominence in healthcare as a top strategic asset, health systems are increasingly understanding the importance of adata governancestrategy. Healthcare analytics leaders are learning, however, that there’s a big leap from knowing they need data governance to implementing a strategy. Even expert data analysts benefit from guidelines as they move towards data governance.

This article discusses the importance of data governance in healthcare and how organizations can transition from simply doing analytics to doing analytics under a strategy that safeguards and maximizes one of their top assets—their data.

Healthcare’s Urgent Demand for Balanced Data Governance

According to theHealthIT.gov到2015年，超过80%的美国医院已经知道如何收集他们的临床数据。但是，就在卫生系统数据增加的同时，对其数据的不信任也在增加。According to a 2018survey, less than half of healthcare CIOs have strong trust in their data. They often don’t know how their analytics are derived or on what data they are based, and they rarely have any easy way to alleviate their concerns.

Balanced data governance builds trust and effectiveness. In years past, analytics teams emphasized data security. Protecting data was paramount, and it continues to be important today. But what good is data if only a few people can use it? To paraphraseHenry David Thoreau,that governance is best which governs least.Effective organizations secure their data from misuse. Beyond that, their job is to liberate data and facilitate its best use by everyone.

Five Manageable Steps to Healthcare Data Governance

作为一个涉及多个方面(从数据安全性到数据质量再到数据管理)的主题，定义数据治理的细节超出了本文的范围。数据治理的压力太大了，以至于许多组织都很难开始;或者他们确实开始了，但是范围太广了，所以很难获得吸引力。

According to data management expertWill Bryant，“调查报告显示，多达三分之二的初始数据治理努力最终夭折。”Bryant explains that these efforts “mushroom into such complexity during the planning and design phases that they are abandoned before they have the chance to deliver any value.”

Healthcare organizations can navigate the complexity of data governance set-up by following five practical, manageable steps:

1. Identify the Organizational Priorities

对于分析师、报告作者和其他数据从业者来说，识别数据问题通常很容易。但是，仅根据数据感知来决定数据治理的重点通常是失败的。为了治理而进行的治理是一种空洞的努力，很少找到足够的领导或基层支持来获得或维持势头。如果是这样的话，它经常会成为一种不考虑组织分析需要的规律。这样的治理可能比根本没有治理更糟糕。

The purpose of data and analytics is to serve the strategic goals of the organization. So, the first step in developing a new data governance program is to identify the organizational priorities. This requires an understanding, for example, of the top five targets the executive team wants everyone in the organization to help deliver over the next year. These could include lofty goals, such as “increase patient engagement” or “improve performance-management analytics.” They might also include more specific goals, such as “decrease adverse drug events by 5 percent” or “increase patient use of telehealth services by 9 percent.”

A simple list of the organizational goals, however, is likely insufficient. Effort should be made to understand the rationale behind the goals, the discussions that led to them, who was involved, and the nuance of their positions. (Understanding these last two points will be important for step 3.)

2. Identify the Data Governance Priorities

开发新的数据治理计划的第2步是确定与第1步确定的组织优先级重叠的数据治理机会。这些组织的优先级甚至可能已经发展为改进计划。

All analytics depend on timely and reliable data, so it’s likely that finding overlapping data governance opportunities will be easy, especially in organizations whose data governance is still maturing. For example, if decreasing adverse drug events were one of the organization’s priorities, proposing the creation of an accompanying data validation process to ensure the accuracy of the analytics would be an easy sell. Look for an implicit data governance prerequisite such as this and call it out

请记住，企业数据治理是这些工作的最终目标。如果可能的话，选择与最初的、狭隘的焦点相关的数据治理机会。起初将范围缩小可能是适当的。上面示例中的新数据质量验证过程最初可以关注不良药物事件数据，但这应该只是最终成为在组织中任何地方有效验证数据质量的共享过程的第一稿。否则，它可能只是整个组织中许多冗余的相关流程中的一个，每当另一个团队需要类似的东西时，这些流程就会被重新发明。这种变化不仅非常浪费，而且几乎不可能治理。

3. Identify and Recruit the Early Adopters

The next step is to survey the list of intersecting priorities identified in step 2, note the accountable leaders for each and identify which of these leaders are likely early adopters of data governance. Energetic leaders who truly understand the importance of data governance should be top of mind. Once each group establishes its governance objectives, these leaders often naturally become the champions of the organization’s new data governance program.

Creating a list of desired characteristics for a data governance leader launches the search for early adopters. Geoffrey

Moore’s bookCrossing the Chasmoffers valuable insights into important characteristics of effective early adopters:

• Connections: Early adopters need to be connected to the right resources.
• 热情:因为早期采用者会激励其他人参与进来，他们必须了解需要做什么以及为什么要这样做，并对开始工作感到兴奋。
• A deep understanding of data governance: Early adopters should understand data governance on more than a casual level and be aware of the challenges and benefits. Such awareness fuels the drive necessary to break through the inertia early in the program’s development.

随着候选名单的增加，一些探究每个人对数据治理好处的理解的问题将有助于将名单缩小到最有可能完成数据治理项目的人。Consider questions such as the following:

• What is the importance of data stewardship?
• 如果你是我们组织的数据治理负责人，你会招募谁，为什么?你会如何组织他们?
• How would you ensure that all metadata, populations, measures, value sets, and other terminology were organized and accessible to the organization?
• What is the role of data lineage? What are some ways to make such information current, accurate, and relevant?
• What are some ways to ensure the quality of data from sourcing and transformation to presentation in dashboards and other analytics?
• What business rules are needed and how should they be organized?
• What data policies should be established? What’s the best way to ensure accountability and adherence to policies?
• How would you approach metadata management?
• What about master data management? How should patient or provider matching be done? Would you focus on other items? Which ones and why?

4. Identify the Scope of the Opportunity Appropriately

Many organizations tackling data governance try to do too much too soon and get bogged down. It’s important to scope the opportunity narrowly enough to get traction with a small pilot team that is nimble enough to improvise and redesign processes on the fly. Focus on a specific data governance opportunity (e.g., data quality, data usage, etc.) within a specific area (e.g., clinical domain, patient population, geographic region, etc.) to target the effort on a manageable subset of the organization’s data governance—versus trying to fix all of it at once.

If the data governance team chooses one of the loftier organizational goals, such as “increase patient engagement,” it will need to refine this into something more precise, such as, “increase usage of the patient portal by 10 percent of patients in the Tri-Cities region.”

这是心理上和生理上的实用主义。通过关注团队的直接领域(例如，三城地区的患者门户数据)，它使问题变得更加熟悉。It also lowers the amount of data, oversight, and approval that might otherwise be needed and could impede the team’s progress

5. Enable Early Adopters to Become Enterprise Data Governance Leaders and Mentors

当前两组团队实现了他们的数据治理目标时，可能是时候将他们的过程一般化，以便更广泛地采用。这种从本地到组织的视角转变自然与每个早期采用者从团队领导者到企业数据治理领导者的转变相一致。有了新的成功，他们就有能力在总体上支持数据治理，并招募和指导其他人;他们传达的信息不仅仅是概念上的，而是基于他们自己来之不易的经验，这给了他们即时的可信性和大量的具体例子，让他们明白数据治理的方式和原因。

Data Governance: A Vital Tool Organizationwide

By following these five steps for doing data governance, a small team can kick off a data governance program, marry it with an organizational priority, possibly in the form of an existingimprovement倡议，推动企业数据治理的发展。通过招募热情的早期采用者来支持该计划，从小处开始，并专注于重叠的组织和数据优先级，数据治理将被广泛认为是推动整个组织的重要工具。

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

1. Three Must-Haves for a Successful Healthcare Data Strategy
2. Healthcare Data Governance
3. How to Build a Healthcare Data Quality Coalition to Optimize Decision Making
4. Four Critical Phases for Effective Healthcare Data Governance

---

PowerPoint Slides

你想使用或分享这些概念吗?Download the presentation highlighting the key main points.

Click Here to Download the Slides

Five Practical Steps Towards Healthcare Data Governancefrom世界杯葡萄牙vs加纳即时走地