Mastering Healthcare Data Governance through Data Lineage

The healthcare industry faces the greatest risks when it comes to data governance. First, healthcare organizations continue to be faced with massive (and ever-increasing) amounts of highly regulated personal data.

The impact the use of medical data has on people’s lives is at the core of why data governance is important in healthcare. In healthcare, managing the accuracy, quality, and integrity of data is the focus of data governance. When healthcare organizations excel at this, it can lead to better clinical decisions, improved patient outcomes, and prevention of medical errors.

Nonetheless, many healthcare organizations face challenges. Healthcare organizations need a strong data governance framework to help them comply with regulations such as the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in the EU.

How can healthcare providers improve their data governance strategies, especially considering the ripple effects of small changes? Data lineage can help. Data lineage allows teams to establish a strong data governance strategy to take full control of their healthcare data pipeline.

Understanding data governance in healthcare

The need for a strong data governance framework is undeniable in any highly regulated industry. However, the healthcare industry is unique in that it collects and processes massive amounts of personal data to make informed decisions about patient care. A single corrupted or incomplete piece of data not only causes non-compliance and audit issues, but can also cause harm to real people. for example:

• Health care providers routinely rely on medical records to diagnose patients and develop treatment plans. These inaccuracies in medical records can have serious consequences, leading to misdiagnosis, medication errors, or delays in treatment.
• Inaccuracies may further delay or complicate coverage.
• Healthcare organizations must comply with data privacy regulations such as HIPAA and GDPR. Failure to comply with these laws can be costly and reputational, and poses risks to patients and practitioners if a data breach occurs.

Conversely, confidence in the accuracy and consistency of data can minimize the risk of adverse health outcomes, rather than simply reacting to or causing them. Additionally, using predictive analytics can help identify patient trends, patterns, and potential future health risks.

It is worth noting that most electronic health record (EHR) systems offer predictive analytics capabilities. The accuracy of these analyzes is limited by the accuracy of the data used.

Therefore, it is essential to have a comprehensive understanding of the data environment and a clear management system. Detecting leaks and pressure points depends on implementing a strong data governance strategy with data lineage as a critical component.

The challenges of healthcare data governance and how data lineage can help

Data governance can help healthcare organizations maximize the accuracy and security of their data assets. At the same time, implementing a data governance framework poses several challenges, including data quality issues, data silo security, and privacy issues.

1. Data quality issues

Positive business decisions and outcomes depend on reliable, high-quality data. However, despite the best efforts of business leaders, healthcare facilities continue to face data quality issues due to the number of people entering data and the pressure situations in which data entry frequently occurs.

A study conducted by the Journal of the American Medical Association (JAMA) found errors in the records of one-fifth of patients who received outpatient medical notes. Of those patients, 21% identified the error as a serious error, with common problems including diagnostic errors, medication data errors, and incomplete or inaccurate EHR data translation. These errors are very important and can happen every day. To prevent these errors, it is important to map data flows and flag data quality issues through root cause analysis to reduce the impact on patients.

2. Data silos

In the healthcare industry, which generates approximately 30% of all data worldwide, patient data is often unstructured and scattered across disparate systems. result? An incomplete picture of patient health and multiple sources of information prevent you from achieving the benefits of data visibility, such as informed patient care. These distributed data sources also create compliance and auditing challenges.

The solution lies in the ability to visualize patient data from multiple sources in one place. This is what enterprise data lineage does. Data lineage extends across your data environment to create a comprehensive map of all data flows and dependencies, effectively eliminating data silos.

However, not all data lineage solutions can visualize data from different silos. Some platforms only allow you to view data stored in specific catalogs. Choosing a catalog-agnostic solution can help solve this problem.

3. Security issues and chain of custody

Healthcare organizations are in a unique position because they rely on cross-departmental information sharing to facilitate patient care and adhere to strict regulations to ensure secure data transfer.

As part of HIPAA and GDPR compliance, healthcare organizations must provide auditors with details about the chain of custody of patient records. This includes information about who accessed the record, when they accessed it, and from where. Establishing a chain of custody for data stored in an EHR system that can be accessed by multiple devices within a healthcare facility can be laborious and time-intensive. This is especially true when dealing with numerous records that exist in paper format or are manually entered or scanned.

Data lineage significantly reduces the effort required to establish a chain of custody within a healthcare information system. Mapping data flows allows you to trace the reverse path of data to determine where and when data has changed in the system. This, combined with governance efforts that establish the meaning, quality, and stewardship of data stores in the chain of custody, can provide the critical data pipeline information that auditors require.

Better patient care and predictive analytics

High-quality data allows you to provide informed, collaborative, and personalized patient care. Additionally, there is greater confidence in predictive analytics within EHR systems to predict patient status, disease progression, hospital length of stay, and readmissions. All of this relies on trusted data and requires data lineage for governance.

Enhanced Compliance

Establishing and demonstrating compliance with healthcare-related regulations such as HIPAA and GDPR can be difficult if you struggle with data silos, data quality, or demonstrating chain of custody. Data lineage helps clearly and quickly establish the chain of information flows and dependencies for auditors, which are key to compliance.

Enhanced data security and privacy

Data privacy is essential in the healthcare industry. Data Lineage does not share or process any personal information when creating maps of your data environment. Instead, use active metadata. This means you can build a strong data governance framework without compromising patient privacy.

Improve operational efficiency and reduce costs

Manually mapping data flows is a time- and resource-intensive process, especially in the highly complex healthcare industry. One of the biggest advantages of automated data lineage for data governance is operational and cost-effectiveness. You can save money and time on labor costs and focus your efforts on what matters most to your organization.

We are 90% faster

“Our ETL team can identify the impact of planned ETL process changes 90% faster than before.” Robert D, GEMU BI Team Leader

90% increase in source system change analysis

“The effort to analyze the impact of source system changes has been reduced by at least 90%, from hours to minutes (or seconds).” Michael L., BI Manager, Schumacher Clinical

Data Governance and Compliance

Ensuring compliance with regulations such as HIPAA and GDPR in the healthcare industry is another important part of data governance, which is critical to protecting patient privacy and promoting secure information sharing essential to the highest level of patient care.

Some healthcare organizations today still struggle to comply with HIPAA and GDPR. Meanwhile, the world’s regulatory environment is becoming increasingly complex. In fact, Gartner® predicts that by the end of 2024, 75% of the world will have data protected by modern privacy regulations. Considering that the healthcare industry is generating new regulated patient data every second, now is the time to launch an effective data governance strategy.

It is worth noting that these regulations do not only apply to patient care-focused organizations. Almost every area of ​​healthcare has dealt with large amounts of protected data, including:

• biotechnology company
• health insurance provider
• Medical device manufacturer
• pharmaceutical company

Data lineage allows you to obtain a detailed map of your data flows to help you process and protect your data within the stringent requirements of regulatory frameworks such as HIPAA and GDPR. It also makes it easier to prove chain of custody to auditors who need to determine who has accessed regulated data assets and enforce stricter controls on who has access.

Next steps to strengthen data security and enhance compliance

The modern healthcare industry is experiencing increasing complexity due to the emergence of EHR systems, proliferation of healthcare data, and an increasingly complex regulatory environment.

To keep pace, today’s healthcare companies must implement data governance. A strong data governance framework helps ensure that the data you collect, process, and use is accurate, consistent, and trustworthy. Otherwise, you risk making uninformed decisions about patient care based on faulty data or inaccurate predictive insights. These decisions can have serious or even fatal consequences for patients.

Data governance is also essential when complying with healthcare data privacy regulations such as HIPAA and GDPR. All healthcare organizations that process protected data should have a data governance strategy in place to remain compliant with these regulations and prepare for new regulations that may arise.

Despite challenges such as data quality issues, data silos, security issues, and demonstrating chain of custody, there is a solution: automated data lineage. By using automated data lineage, organizations can overcome common data governance barriers, improve patient care, strengthen regulatory compliance, enhance data security and privacy, and improve operational efficiency while reducing costs. there is.

Explore automated data lineage solutions for data governance in healthcare.