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Health Data Management: Challenges and Best Practices
The healthcare industry has evolved tremendously over the past few decades — with technological innovations facilitating its development. The global digital health market is expected to reach $456.9 Billion by 2026, showing the crucial role of health data management in the industry.
Source: Precedence Research
The increased volumes of information, varying in type and velocity, present immense potential to derive value from and aid the digital transformation of the healthcare industry. With the digitization of healthcare data, advanced analytics and reporting have taken center stage, facilitating improved decision-making in clinical care. Since traditional management systems cannot cope with the massive volumes of digital data, the healthcare industry is investing in modern data management solutions to enable accurate reporting and business intelligence (BI) initiatives.
What is Health Data Management?
Health Data Management, also known as clinical data management and health information management, refers to the management of medical data stored in a digital format as Electronic Health/Medical Records (EHR/EMR).
With the digitization of the healthcare industry, organizations store and process all medical records in an electronic format. These records include demographic information (age, address, gender, etc.), health records (lab reports, prescriptions, doctor visits, treatment history, etc.), and administrative data (insurance claims, billing details, etc.)
These electronic records are consolidated in a centralized data repository to enable efficient reporting and analytics. Accurate and complete data allow analysts to uncover meaningful insights to make patient care more efficient and improve medical outcomes.
Benefits of Effective Healthcare Data Management
Improved patient care
An effective healthcare data management system helps improve patient care by empowering users to derive meaningful insights from data. It enables users to optimize healthcare resources and treatments while ensuring the safety and privacy of patient data.
A comprehensive view of patients and relevant medical data allows healthcare providers to prepare care suggestions and counter rising health issues.
Reduced costs
The national health expenditures for the US healthcare system totaled $4.1 trillion in 2020, making it 19.7 percent of the total GDP. Healthcare organizations are constantly looking for ways to minimize their expenditures. Usually, the devil is in the details.
Using advanced analytics, Healthcare providers can identify cost drivers and make better financial decisions, such as recruiting suitable medical professionals, investing in the right equipment, and identifying the resources to optimize patient care.
Evaluate medical practitioners’ performance
Data-based performance management involves evaluating the performance and attitudes of doctors and healthcare personnel to ensure standards for quality care are met. With the help of cloud-based tools and software integrations, many healthcare organizations can monitor ongoing performance ensuring all employees are connected in terms of coaching, feedback, and performance evaluations.
Improved clinical care with predictive healthcare analytics
Predictive analytics enable healthcare providers to establish patterns and trends from data that may predict future trends. Identifying these trends can be helpful in various use cases, such as preventing disease outbreaks, forecasting readmissions, making a prognosis, and more.
Healthcare Data Management Challenges
Consolidating data from disparate sources
Healthcare data comes from various sources, including EHRs, EMRs, and unstructured documents. This data must be accurate, complete, formatted correctly, and stored in a centralized data repository for consumption. To ensure data standardization across various data formats and EHR systems, different IT tools and software solutions now fully automate data capture while providing data standardization tools that make data accessible, transmissible, and interoperable.
Storing and retaining healthcare records
Healthcare data volumes are significantly rising. In fact, the healthcare industry produces 30% of the world’s data alone. Archiving and processing large volumes of data can be complex and present high cost and security challenges. Many healthcare providers are moving to advanced cloud storage solutions to ensure compliance with HIPAA and other industry standards. Cloud storage also provides the ease of a scalable and safe storage solution.
Ensuring data accessibility across the organization
Data accessibility plays a crucial role in providing high-quality patient care. Healthcare providers must have seamless access to patient records, including medical history, test results, and other relevant information. Ensuring timely access to information cannot be accessible with a high volume of healthcare data produced. A centralized data system ensures a seamless clinical experience for both patients and physicians. This saves both time and resources required to access and file data.
Maintaining healthcare data compliance and security
Since healthcare data is confidential and sensitive, it is critical for hospitals to adhere to legal guidelines such as USA Health Insurance Portability and Accountability Act (HIPAA) to avoid data breaches. Compliance with legal healthcare guidelines ensures effective patient management by protecting confidential patient data.
Best Practices of Healthcare Data Management
To maximize the potential of implementing a healthcare data management system, hospitals and other healthcare facilities must collaborate to effectively manage, organize, safeguard, and transfer patient and provider information.
Ensuring Data Quality
Medical errors are the third leading reason for death in the US. Healthcare providers must use effective data management solutions with a mechanism to profile incoming data, verify the information quality, and eliminate errors to ensure accurate and complete data availability.
Protecting Data
In a 2022 report from IBM, the cost of a breach in the healthcare industry went up 42% since 2020. This was the highest average data breach cost of any industry. With threats of cyber-attacks and breaches, hospitals and health systems must improve detection and containment by implementing modern cybersecurity measures while following GDPR and HIPAA guidelines.
Enabling Healthcare Data Exchange
Healthcare Information Exchange (HIE) allows different applications, devices, and systems to share, access, and exchange healthcare information. This makes accessing and retrieving clinical data easier. This ensures optimal patient care with a safe and quick information transfer.
Healthcare Data Analytics
Data analytics can help unlock the true potential of healthcare data. It enables clinicians and healthcare systems to deliver enhanced patient care within and beyond the organization in population health analytics.
There are four different types of data analytics in healthcare:
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Descriptive analytics
Descriptive analytics in healthcare uses historical patient data and simple statistical measures, such as counts, percentages, averages, etc., to analyze data.
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Prescriptive analytics
Prescriptive analytics involves using historical data to predict events in the future while drawing helpful recommendations. This type of analytics outlines specific steps an individual or organization can take to achieve desired results or the best course of action.
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Predictive analytics
Predictive analytics mainly involves forecasting events and outbreaks using advanced statistical measures such as data modeling, mining, and machine learning on historical data. Examining trends and patterns in a high volume of data allows health data professionals to make informed decisions.
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Diagnostic Analytics
Diagnostic analytics is a form of advanced analytics used to identify the reason behind a particular trend or occurrence. This is done mainly by studying cause-and-effect relationships. In healthcare settings, this could mean understanding the cause and studying correlations, such as establishing a spike in fever rates with an infection.
Simplify Healthcare Data Management with Astera
Astera Data Stack is an enterprise-grade, all-in-one platform that enables healthcare organizations to unlock the true potential of their data. With the help of our AI-powered data capture technology, healthcare organizations can seamlessly extract data from unstructured documents. Our platform also has an extensive library of pre-built transformations and connectors to create automated workflows to streamline data management activities.
Authors:
Safa Ghori
