What is the importance of Healthcare Data Governance

Data has been gaining more and more prominence in the healthcare industry, becoming a strategic asset.

This article unfolds how healthcare companies can benefit from data governance and gain a competitive advantage in data analytics under a prudent strategy.

Why is Data Governance Important for Healthcare Companies?

The healthcare industry has learned the art of data collection. However, with the steady increase in data volume, their mistrust of data also has grown. It is where the role of data governance comes into the picture. It builds trust in data apart from increasing its effectiveness.

Data security is a crucial concern for analytics teams, so they emphasize protecting the data. But there is an angle that needs attention.

What can be the value of data if only a few people can use it? So, the solution for companies is to secure their data from misuse while making the data accessible to put it to the best use.

Practical Steps of Healthcare Data Governance

Here, we discuss the following practical steps for healthcare companies to deal with the complexity of data governance:

Identify Your Organizational Priorities

If data governance is done to keep up with the growing trend without any firm objective, it will not elicit any support to sustain momentum. Moreover, it will entail almost nil analytic advantage to the organization. So, having such data governance is like having no governance at all.

So, to have meaningful data governance, you need to identify your organizational priorities first. Bear in mind that the primary purpose of data governance is to serve your organization’s strategic goals.

Identifying your organizational priorities call for some effort. First, it requires a solid understanding of the objectives or your company’s goals and the rationale behind them. For example, some top goals of your healthcare company could be increasing patient engagement over the next six months, increasing telehealth services, or decreasing adverse drug events by five percent.

Identify Your Data Governance Priorities

For example, if decreasing adverse drug events was one of your organization’s priorities, you can start a data validation process to ensure that only the correct data is stored. That will make the analytics more accurate and insightful.

Set up such a data governance prerequisite as it will help.

The fact remains that the end goal of all data-related efforts is actuating enterprise data governance. Therefore, it will be wise for you to select relevant data governance opportunities for the long term beyond the narrow initial focus.

But, starting could be with a narrow scope. Let us refer to the example of decreasing adverse drug events. The data quality validation process could be focused on initially. With time, it could be expanded as a shared process to validate data quality in any department of your healthcare company.

Recruit the Early Adopters

You should choose energetic and knowledgeable leaders who understand the importance of data governance. Such leaders are likely to become the champions of your new data governance program. The leaders are also called early adopters.

The characteristics of early adopters are:

  • They should be connected to the right resources.
  • They should be excited to get work and understand what should be done. Early adopters should motivate others to get involved.
  • Early adopters should understand data governance more and should be aware of the challenges and benefits. The awareness imparts the momentum to break through the inertia early in the data governance process.

Identify the Opportunity Scope

It will help if you narrow the opportunity narrowly and work with a small pilot team to improvise the process to get the initial traction.

It is a wise tactic to focus on a particular data governance opportunity, such as data quality, or data usage, within a specific area, like clinical domain, patient population, or geographic region.

It will help to manage a subset of your company’s data governance effectively. In addition, it will be easier than trying all opportunities at once.

You can realize the difficulty with the following example. Say you choose a broad goal, such as “increase patient engagement,” which will entail the refinement of something more precise, such as “increase usage of the patient portal by 10 percent of patients in the Tri-Cities region.”

It would result in the team focussing on the patient-portal data. And that can lead to lowering the amount of data, and oversight, retarding the team’s progress.

Allow Early Adopters to Become Data Governance Leaders and Mentors

As they taste success, they will gradually evolve as champions of data governance in your healthcare organization.

They will eventually recruit and mentor other members of the data governance team. As their knowledge comes from their own experience, they understand every nook and corner of data governance.

Conclusion

Known for his boundless energy and enthusiasm. Evan works as a Network Security Manager, an avid Blog writer, particularly around Technology