Data Governance in Healthcare: Optimizing Operations and Improving Patient Care
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Data governance in healthcare is essential for ensuring compliance with data protection regulations, supporting clinical decisions, and providing better patient care.
So, let’s explore the importance, benefits, and implementation of robust data governance in the healthcare sector.
Table of contents
- What is data governance in healthcare?
- The need for data governance in healthcare
- Unveiling the benefits of effective data governance in healthcare
- Implementing a healthcare-specific data governance framework: Key components
- Evaluating healthcare data governance solutions
- In summary
- Data governance in Healthcare: Related reads
What is data governance in healthcare?
Data governance in healthcare is a standardized and structured approach to collecting, managing, analyzing, and sharing medical data transparently while adhering to ethical and regulatory standards.
“An organization-wide framework for managing health information throughout its lifecycle—from the moment a patient’s information is first entered in the system until well after they are discharged.”
Health data is a strategic asset and strong data governance is crucial for making well-informed decisions and ensuring the highest quality of patient care.
According to the World Health Organization (WHO), the COVID–19 pandemic exposed long-standing data governance issues, such as intellectual property rights, data sharing, interoperability, reuse, and storage.
With data governance, you can ensure that data collection, management, and use are ethical. This also helps in reducing inequalities in access to health and the resources for healthy living, according to research presented during the 2021 Health Data Governance Summit.
The need for data governance in healthcare
Healthcare data management faces challenges, such as:
- Ensuring data privacy and security
- Maintaining regulatory compliance
- Dealing with disparate data sources
- Ensuring interoperability across various systems and data formats in the healthcare data ecosystem
Let’s consider a large hospital system grappling with integrating data from multiple electronic health record (EHR) systems. This issue can lead to several complications, such as:
- Difficulty accessing comprehensive patient information
- Increased administrative workload with tasks such as manual data entry and reconciliation
- Potential risks to patient safety due to inconsistencies in data across various EHR systems
- Increased costs due to inefficiencies and time spent managing disparate data sources
To tackle these challenges, the hospital system can implement a comprehensive data governance strategy that streamlines data management processes and systems, sets up data standards, improves data quality, and enhances collaboration among all stakeholders.
The consequences of bad data privacy and security practices in healthcare
Patient data includes personal data like name, date of birth, address, bank account number, card number, and medical data like illnesses or disabilities. Data breaches that reveal such data can damage the reputation of healthcare providers and their patients.
Ensuring data privacy and security in healthcare organizations is not only crucial for protecting sensitive patient information but also for maintaining compliance with various laws and regulations.
Non-compliance can result in severe penalties, including hefty fines and reputational damage. That’s because key healthcare data regulations in the US and the EU emphasize the need for establishing proper data security and privacy practices.
So, before proceeding further, let’s take a quick look at these key healthcare data regulations.
Healthcare data regulations for patient data privacy and security: HIPAA and the EU GDPR
Regulation of healthcare data in the US: HIPAA
In the United States, the Health Insurance Portability and Accountability Act, or HIPAA is a federal law enacted in 1996 that guarantees privacy protection for healthcare data. HIPAA applies to any entity handling health-related information, including those creating healthcare applications for the US market.
HIPAA non-compliance can be costly. In 2014, the New York-Presbyterian Hospital and Columbia University were collectively fined $4.8 million for failing to secure thousands of patients’ electronic protected health information (ePHI) held on their network.
The breach occurred when a physician attempted to deactivate a personal computer server, resulting in ePHI being accessible on internet search engines.
“The $4.8 million penalty was issued because the entities in question failed to conduct a risk analysis and did not employ the appropriate safeguards to minimize the risk to electronic PHI.”
OCR Director Lisa J. Pino emphasizes the need for healthcare organizations to know where and how their data is stored:
“HIPAA-covered entities are vulnerable to cyber-attackers if they fail to understand where ePHI is stored in their information systems.”
This was after the Oklahoma State University – Center for Health Sciences (OSU-CHS) was fined $875,000 due to a 2017 data breach. The University violated multiple HIPAA requirements, such as failure to set up audit controls, delays in reporting the breach and notifying those affected, and not performing organization-wide risk analysis.
Regulation of healthcare data in the EU: GDPR
The General Data Protection Regulation (GDPR) is a broad-reaching regulation that came into effect in 2018, and it applies to all sectors, not just healthcare.
The GDPR governs the handling of the personal data of EU citizens, no matter where in the world the organization collecting the data is located. That being said, GDPR also has important implications for healthcare applications.
Any application that collects data from EU citizens, including health-related information, must comply with the GDPR. This means that entrepreneurs who are developing these kinds of applications must ensure robust data security measures and respect the privacy rights of their users, as stipulated under the GDPR.
Like HIPAA, GDPR violations can lead to hefty fines.
In 2021, the French Lead Supervisory Authority (LSA) fined Dedalus Biologie — a company selling software solutions for medical analysis laboratories — 1.5 million euros for health data breach and GDPR non-compliance.
An LSA investigation discovered that the company did not establish:
- Specific procedures for data migration operations, monitoring, and reporting security alerts on the server
- Encryption of personal data stored on the problematic server
- Authentication processes for data access
- Security protocols for collecting, storing, and accessing personal data
That’s where healthcare data governance can help. Let’s check out the benefits of implementing a strong data governance framework.
Also, read →
Unveiling the benefits of effective data governance in healthcare
Health data can generate value with:
- Improved patient care with interoperable systems
- Optimized health service and resource efficiencies
- Greater support for innovation and research in healthcare
- Better healthcare decision-making
- Compliance with healthcare regulations and standards
Let’s see how.
Improved patient care with interoperable systems
The Health Data Collaborative highlights interoperability as one of the biggest challenges in using health data to optimize patient outcomes.
Healthcare data comes in various formats and from numerous sources, such as electronic health records (EHRs), medical devices, health surveys, clinical trials, and more. This data is held in silos by the entities collecting them
Data governance can establish data exchange standards, data formats, and data sharing policies, enabling seamless data integration across different systems and providers.
This leads to a healthcare data system that’s interoperable, which will enhance care coordination, reduce duplication of tests and procedures, and ensure comprehensive patient care.
Optimized health service and resource efficiencies
Data governance can help in delivering better services to patients as it optimizes operational processes and workflows. It helps in streamlining data collection, storage, and access while eliminating redundant and duplicate data.
Such a system can ensure optimized, efficient health service delivery.
Here’s an example from an Ohio University’s Online Programs article:
“During a routine examination, a doctor records a patient’s blood pressure. If the patient’s blood pressure is higher at the next checkup, and higher again at the checkup after that, the doctor can use the recorded data to draw conclusions about the patient. Using the information stored in the patient’s EHR, the doctor can prescribe medication or help the patient establish a plan for lowering high blood pressure.”
Greater support for innovation and research in healthcare
Data governance establishes processes and policies for data access and sharing, making it easier for researchers and innovators to access relevant and reliable healthcare data.
As mentioned earlier, it also standardizes data formats, defines data exchange protocols, and promotes collaboration and knowledge sharing across the healthcare data ecosystem.
As a result, healthcare organizations can analyze data at a broader scale, identify public health trends, and conduct epidemiological studies.
Better healthcare decision-making
Improving data quality and enhancing decision-making are core benefits of implementing a robust data governance program.
For instance, establishing data standards, validation rules, and data cleansing techniques helps eliminate errors, inconsistencies, and redundancies in data. This improves data quality and accuracy, thereby enabling healthcare providers to make informed decisions, enhance patient safety, and improve care outcomes.
Moreover, data governance facilitates data-driven decision-making as healthcare providers can leverage data and analytics to get insights on everything from resource allocation to clinical outcomes.
For instance, accurate and trustworthy data can help in several disease-fighting tasks according to the World Economic Forum, such as:
- Predicting where and how fast an illness will spread
- Allocating inevitably scarce resources
- Identifying so-called infection clusters
- Tracking and tracing the contacts of those who have been found to be carriers
Compliance with healthcare regulations and standards
Data governance helps healthcare organizations comply with industry regulations and data standards.
For instance, HIPAA’s minimum necessary standard requires organizations to “take reasonable steps to limit the use or disclosure of, and requests for, protected health information to the minimum necessary to accomplish the intended purpose.”
So, healthcare organizations must set up an infrastructure that tracks data access and monitors requests in real time. A solid data governance framework ensures that your data usage practices align with legal requirements, privacy regulations, and industry best practices.
This, in turn, mitigates legal and financial risks while establishing a standard for ethical data handling and sharing.
Read more → Benefits of data governance
So, what would a strong data governance framework offering the above-mentioned benefits look like?
Implementing a healthcare-specific data governance framework: Key components
A healthcare data governance framework is a comprehensive system designed to handle the availability, integrity, usability, and security of data within an organization.
According to the American Health Information Management Association (AHIMA), healthcare organizations must establish:
“A basic framework for collection, retention, use, accessibility, and sharing of healthcare data, consisting of policies, procedures, standards, ownership, decision rights, roles and responsibilities and accountability related to the data.”
There are five key functional components of such a framework:
- Data standards and definitions for data integrity, access, privacy, security, sharing, and retention
- Data quality management for maintaining the accuracy, completeness, consistency, and reliability of data throughout its lifecycle
- Metadata management for documenting data definitions, standards, and conventions, and ensuring accountability regarding metadata decisions
- Master data management for ensuring consistency in the interpretation of key business attributes. Also, read → Metadata management vs. master data management
- Data architecture that defines data requirements, supports all kinds of data assets, and guides integration, maintenance, and retrieval of data
Read more → Data governance framework
A step-by-step guide to implementing data governance in healthcare
Here are five steps you can follow to set up a healthcare-specific data governance framework for your organization:
- Define the data governance program scope by mapping out the organizational structure, authorities, councils, and roles. Read more → Data governance policy
- Create a Data Governance Management Team with a Chief Data Officer working with the Chief Medical Information Officer to establish healthcare data governance plans or programs. This will also help in driving accountability. Read more → What does a data governance team do?
- Define key metrics to demonstrate value — data accuracy for data quality, data issues corrected for process improvement, and reduction in rework for cost reduction and efficiency.
- Understand the compliance standards and policies to be followed.
- Locate and identify PHI (Protected Health Information) — names, addresses, social security numbers, etc. — and use the appropriate encryption, masking, or hashing policies to store PHI.
- Set up proper user permissions and authentication protocols for monitoring data access.
- Train your teams in adopting and following your data governance program.
Also, read → Data governance best practices for 2023
Evaluating healthcare data governance solutions
When evaluating healthcare data governance solutions, there are several factors and tooling capabilities to consider.
Let’s look at the must-have capabilities for healthcare organizations:
- Data classification and tagging
- Data search and discovery
- Metadata management
- Data lineage and traceability
- Data security and privacy
- Compliance and reporting
- Integration and interoperability with the healthcare tech stack
Read more → Data governance implementation and tooling
Data governance in healthcare is vital for practitioners to have access to the right data without compromising the privacy, security, and accuracy of patient data. AHIMA emphasizes the need for healthcare data governance to be organization-wide, including interdisciplinary teams consisting of subject matter experts.
This article covers the need for data governance in healthcare, followed by benefits, framework components, and implementation. These should be considered as a starting point and as your organization evolves, so should your healthcare data governance initiatives.
Data governance in Healthcare: Related reads
- What is Data Governance? Its Importance, Principles & How to Get Started?
- Data Governance in Manufacturing: Steps, Challenges, and Practical Examples
- Data Governance in Retail: Best Practices, Challenges, and Viable Solutions
- Data Governance in Insurance: Why is it Important and How it Drives Positive Business Outcomes
- Key Objectives of Data Governance: How Should You Think About Them?
- Data Governance Framework — Examples, Templates, Standards, Best Practices & How to Create One?
- Data Governance and Compliance: Act of Checks & Balances
- How to implement data governance? Steps, Prerequisites, Essential Factors & Business Case
- How to Improve Data Governance? Steps, Tips & Template
- 7 Steps to Simplify Data Governance for Your Entire Organization
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