How to Enhance BI in Healthcare with Data Lineage
Data is the fabric that supports the healthcare industry. It is a crucial asset in making informed decisions, driving improvements in patient care, and bolstering operational efficiency. Yet data in its raw form can be difficult to understand and hard to glean insights from.
That’s where Business Intelligence (BI) comes into play. BI is the process of taking that raw data and transforming it into valuable information, which can then help organizations make better business decisions. Taking it a step further, healthcare organizations can leverage BI to make better patient decisions.
In this post, we'll cover some of the unique challenges healthcare organizations face when it comes to effectively leveraging BI, and how to ensure that your data is accurate to address these challenges.
BI in the Healthcare Industry
BI in healthcare is used to analyze data on new treatments and medications and identify opportunities for research and development.
It’s also used in clinical settings to gather, store, process, and analyze data to make educated decisions regarding clinical practices and patient care. Clinical BI often depends on data from multiple sources, such as electronic health records, clinical data warehouses, and other Medicare data sources, to collect information regarding patient care and treatment outcomes.
According to Grand View Research, COVID-19 contributed to an 18.5% growth rate in the healthcare BI market from 2019 to 2020. That same outlook estimates that from now until 2030, the healthcare BI market will witness a year-over-year growth rate of 12.5%-13.5%.
This is a testament to the fact that BI is becoming increasingly valuable to the healthcare industry. At the same time, achieving BI is not as simple as flipping a switch from “off” to “on”. There are some barriers that healthcare organizations have to overcome before they can reap the benefits.
Barriers to BI in Healthcare
There are four key challenges that healthcare organizations face when it comes to BI: highly regulated data, access to data, data quality, and constant change.
Highly Regulated Data
Healthcare organizations have a unique challenge.Not only do they manage patients’ sensitive financial information, which requires compliance with financial regulations, but they also manage sensitive patient healthcare data regulated by healthcare-specific regulations like HIPAA.
According to HIMSS Analytics, the average hospital has 18 disparate electronic medical record (EMR) vendors. Additionally, only 2% of hospitals have a single EHR (electronic health record) or EMR vendor at their affiliated practice. With data coming from so many sources, achieving interoperability between platforms and gaining access to all relevant data becomes challenging.
With the sheer number of data sources in play, data quality emerges as another challenge in the healthcare space. With low confidence in data quality, healthcare organizations can’t rely on their data to drive accurate reports, predictions, or patient outcomes.
Many EMR vendors make changes to their underlying data architecture on a quarterly basis, which can break data flows that feed into downstream reports and analytics if unaccounted for.
How Data Lineage Breaks Down Those Barriers
Automated data lineage helps you understand how data flows through your complex data systems while documenting how it transformed along the way.
This helps you address all of the challenges discussed above. Think about it. With a map of your data flows, you can find out who accessed your data at any given point in time and how the data was used, making it easier to comply with regulations. You can see how data flows across multiple sources, giving you trust in your data quality.
You can also more easily adapt to the rapidly changing nature of the healthcare landscape. Manta’s data lineage enables you to conduct root cause analysis to more quickly and efficiently fix data flow pipeline breakages and impact analysis to see what changes a planned change will have on your data environment.
Impact analysis is one of the key features used by Manta customer CHRISTUS Health. When CHRISTUS approached Manta, they were struggling to manage the impact of EHR system updates across data sets and to get ahead of users and be more proactive about data pipeline issues. With Manta, they were able to create a new workflow that proactively approached required EHR upgrades using Manta’s impact analysis and revision comparison capabilities.
“Once we’ve been notified of the upgrades in our non-production environments, we run a scan through Manta to see if there will be any downstream impacts. If there will be, we send them to our developers to make changes before those impacts affect our end users,” said Jonathan Beverly, Information Technology Engineer Senior Information Services at CHRISTUS Health.
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*This article was written and edited by humans.