Your patients are more than data sets (which probably goes without saying).
But the best way to make sure you’re providing the best patient care is by ensuring that patient data is correct.
Think about it. Every day, you rely on patient records for accuracy to make real-world clinical decisions that impact their daily lives. If a single missing medical record or broken or dead table contains crucial medication information that you can’t access, there could be very real and very negative consequences. One missing piece of data can cause an insurance claim to be denied.
That’s a lot of pressure.
Now, let’s add in the fact that if you’re here, you likely already read in our previous blog post about healthcare data that healthcare generates over 30% of the world's data, with that number growing by the day. This data has to be trustworthy, secure, and reliable.
Enough with the pressure! How do you ensure that your data is trustworthy?
With data lineage. Let’s dive in.
Data lineage provides a detailed record of the journey of data from its origin to its final destination, including any transformations, modifications, or updates made to the data along the way. Understanding this journey is crucial in ensuring that patient data is correct, and therefore critical to keeping patients safe. It is also imperative that this information adheres to and complies with laws governing data use in healthcare.
Now, let’s break down the technical process involved in using data lineage for better patient outcomes in healthcare.
The technical process of data lineage in healthcare typically involves data source identification, data extraction, data transformation, data loading, data mapping, and data management. These steps enable healthcare organizations to track the movement of data through various systems and applications, including any modifications, transformations, or updates made to the data.
Let’s take a look at what each of these steps entails.
As you can imagine, each of these steps is extremely cumbersome when done manually. Automated data lineage creates a visual map in a matter of minutes vs. hours, finding dependencies along the way.
The benefits of data lineage in healthcare are numerous. For starters, it ensures that the data being used for patient care is accurate and reliable, which is essential for making informed decisions about patient care.
Next, healthcare organizations are subject to various regulations that require them to maintain accurate and complete medical records. Data lineage makes it easier for healthcare organizations to comply with these regulations.
Moreover, data lineage provides a clear understanding of the data being used in healthcare, which improves data governance and helps to ensure that data is being used appropriately. With accurate and reliable medical data and clinical data integrations, healthcare providers can make informed decisions about patient care, which can lead to improved patient outcomes.
One use case for data lineage in healthcare is in the management of electronic health records (EHRs) and healthcare data integration. By tracking the data lineage of patient records as they move through different systems and applications, healthcare organizations can identify and resolve data inconsistencies, reduce errors, and enhance data accuracy. This can result in better patient outcomes, improved care coordination, and increased regulatory compliance.
One such example can be found in Manta customer CHRISTUS Health. During required quarterly EHR system upgrades, CHRISTUS Health was experiencing major downstream impacts and system outages. More specifically, EHR system upgrades led to data problems including new and deprecated columns, which resulted in downstream impacts affecting end users.
Without visibility into how required upgrades would affect their data environment, the CHRISTUS team was forced to take a reactive rather than a proactive approach to impacts. Rather than CHRISTUS flagging potential impacts in advance and addressing them before they posed problems, end users would inform them of outages as they occurred. Then, CHRISTUS engineers needed to backtrack and troubleshoot what had already gone wrong.
By incorporating automated data lineage, CHRISTUS Health could scan key parts of its data environment to identify EHR system changes and create proactive quarterly updates. Insights that once required days of tedious work — leaving the team in a constant reactive mode — took minutes or hours after implementing lineage tools.
The end result is significantly reduced downtime and a high level of service-level agreement (SLA) for system uptime.
Data lineage is revolutionizing healthcare data management by providing a detailed record of the journey of data from its origin to its final destination. Ready to unlock the benefits of data lineage for your healthcare organization? Request a demo with one of our data lineage experts today.
P.S. This article was written by a human.