Healthcare organizations are eager to tap into the piles of big data they’ve amassed. Today’s technology is leading the charge, making it more attainable and cost-efficient for companies to take advantage of this information. But before you can truly take away any benefits from your healthcare analytics, it’s important first to master big data governance.

Every piece of the healthcare industry relies on a never-ending stream of information: contact information, insurance claims, vital readings, medical histories, and lab results, to name a few. Data is the lifeblood of any healthcare organization and needs that information to be correct, organized, and readily available when it’s needed.

Let’s look at what big data governance means for healthcare organizations and what successful implementation looks like to help you better leverage your healthcare analytics.

Big Data Governance: Past and Present

Before the age of computers electronic medical records, medical data was stored in paper charts and large file boxes. To gain access to this data, someone had to physically search for it. Patients receiving care from multiple facilities would have multiple charts and records, and facilities would have to request that information to be faxed or mailed to their facility.

Data scientists had no easy way to compile this fragmented ecosystem of information. Files were often obscured by messy handwriting, missing papers, or incomplete records, making healthcare information largely useless.

As technology evolved into EMRs, CRM, and other advanced software, so did the concept of Big Data Governance. This newfound ease of tracking, accessing, and compiling data has attracted interest in healthcare data and its resulting insights. Users can now establish a way to organize the mountain of data they collect and use these new tools to streamline everything from care to communication.

Requirements for Better Data Governance in Healthcare

Not too surprisingly, the actual practice of big data governance hasn’t quite caught up with the ideas and possibilities. The shift to a digital environment has led to frustrations, information overload, and an inability to properly leverage the technology tools that are supposed to make their jobs easier.

How can healthcare organizations overcome the challenges they face when moving from concept to common practice? Here are a few priorities that must be considered:

System Availability and Reliability

Though disaster recovery and offline functionality aren’t often discussed in data governance strategies, they most certainly apply. If systems can’t run reliably so that data can be properly collected and accessed, the value of that data decreases.

Data Consistency

Establishing a consistent hierarchy of how data sets should look and function better positions companies to use data appropriately. It’s becoming more difficult to manually catalog data, and will continue to grow in complexity as more data is collected.  Ensuring a consistent, streamlined format not only sets user expectations, but also helps to promote widespread adoption.

Useful Data

Once you determine what data to include in your big data governance strategy, it’s important to decide how users will find the information they need. Each organizational role has its own priorities when searching databases. Role-based views and customizable search features can add greater value to the data you collect.

What Successful Big Data Governance Looks Like

Simply put, big data governance in healthcare assumes business use case to help leaders make informed decisions. Data isn’t inherently valuable on its own; rather, companies must determine how they use their data to drive business growth and add value to the organization.

For more insights on healthcare data trends and use cases, head back to the Lifepoint blog.