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As the healthcare industry and its supporting technologies rapidly expand, an immense amount of data and information is generated. Statistics show that about 30% of the world’s data volume is attributed to the healthcare industry, with a projected growth rate of nearly 36% by 2025. This indicates that the growth rate is far beyond that of other industries such as manufacturing, financial services, and media and entertainment.
This data has immense potential to improve patient care, enhance research, and optimize healthcare operations. However, effectively utilizing this wealth of data poses a considerable challenge. This is where data mapping steps in.
In this blog post, we explore the concept of data mapping within the healthcare industry, highlighting its advantages and examining practical applications through real-world examples.
Data mapping in healthcare is a process of matching healthcare data from different information systems, such as EMR/EHR, into a unified format. It enables healthcare providers to access and utilize patient data efficiently. The process involves creating a detailed software map or blueprint of all the data within the healthcare software ecosystem.
Healthcare data often comes from various sources, including electronic medical records, wearable devices, medical imaging systems, and billing systems. Each of these sources may use different formats and standards, making it difficult to integrate and interpret data. Data mapping aims to overcome this complexity and fragmentation common to healthcare data systems.
Gain more control of your healthcare data ecosystem with data mapping
Data mapping is typically part of the data migration process within larger projects. In healthcare, it is applied in various areas, but there are some common scenarios.
Data migration refers to transferring data from one system to another, often driven by switching to a new system, upgrading an existing one, or undergoing digital transformation activities, such as moving to cloud systems. Data mapping establishes a correspondence between data fields in different systems, error-free transfer, and maintaining data consistency with the original.
Data integration involves combining data from different sources into a single location, which is particularly important for companies using multiple data management systems. Data mapping plays a crucial role in integration, since it creates bridges between the systems that use your data, ensuring its consistency and accuracy.
Data transformation involves converting data from one format to another to enhance its usability and facilitate analysis. Data mapping allows you to create a unified format for data from diverse sources. For instance, when moving time and date data from a spreadsheet to a database, it can be converted to the standard “month, day, year” format.
Many reporting solutions employ unique terminology and data structures, so companies need to adjust their data to fit. Data mapping allows businesses to synchronize their data with the terminology and structure of reporting tools. It helps define what data is needed for specific analyses and reports, making decision-making more informed.
Electronic data interchange (EDI) automates document exchange between companies, optimizing processes, cutting costs, and boosting efficiency. In this case, data mapping specifies the data used in documents, where it’s located, and how it’s transformed to match partner systems.
Poor-quality data costs organizations an average of $12,9 million per year, according to Gartner. This, in turn, leads to more complex data ecosystems and inaccurate decision-making. With data mapping, healthcare providers can enhance the quality of care, minimize expenses, improve patient outcomes, and make effective data-driven decisions.
By matching data from different sources, healthcare providers gain a better understanding of a patient’s health profile, including allergies, medications, and past treatments. This leads to faster referrals, minimized delays, and decreased administrative burdens, resulting in cost savings and increased patient satisfaction.
Interoperability ensures that doctors and other healthcare professionals can access the complete picture of a patient’s health information, even if it’s spread across different systems. This leads to better-informed decisions, improved care coordination, and better patient outcomes.
In healthcare billing, manual data entry is common, leading to errors and underbilling or overbilling. Data mapping automates data transfer between different systems, reducing these errors and standardizing formats for easier insurance processing.
Healthcare organizations can leverage data mapping to simplify compliance with regulations like HIPAA. By mapping data elements to specific standards, they can ensure the accuracy, security, and privacy of protected health information.
By adopting data mapping, healthcare organizations can perform comprehensive data analysis and identify areas for resource optimization. These insights enable them to allocate staff and equipment more efficiently, reduce operational costs, and maximize the use of resources.
Researchers can use data mapping to conduct large-scale clinical trials and research studies. This allows them to identify trends in disease patterns and relationships, predict resource needs, and develop more effective healthcare strategies.
“Data mapping in healthcare is an essential element of informed decision-making. It matches different sources into a single repository, which helps to enhance diagnostics, personalize treatment, and increase the efficiency of the healthcare system. Ultimately, it is an investment in improved quality of life, reduced costs, and data-driven and patient-centered healthcare.”
Anastasia Ilkevich,
Portfolio manager in Healthcare and Medical technologies / Account Manager
Epic’s EHR software is utilized by more than 305 million patients worldwide. At the core of seamless data exchange lies data mapping. This technology enables healthcare providers to exchange information effortlessly and deliver enhanced, personalized care.
Epic’s unified electronic medical record integrates doctor’s appointments, test results, scans, and more, providing physicians with a comprehensive view to make informed decisions.
Patients also benefit from using Epic. They can easily track their health journey and conveniently share their records with other healthcare providers.
Merative, formerly known as IBM Watson Health, applies AI, data analytics, and cloud computing to develop products and services for the healthcare industry, facilitating medical research and enhancing frpatient care.
Data matching allows Merative to integrate patient data across institutions for deeper research. It also ensures accuracy and standardization of data for accurate AI analysis, leading to better healthcare decisions.
InterSystems’ HealthShare platform solves the issue of data silos in healthcare. By utilizing data mapping, HealthShare seamlessly integrates and aggregates patient information from various sources like electronic medical records and imaging systems.
The company’s technology manages over 1 billion medical records worldwide, providing support to all 20 institutions recognized as Top Hospitals by U.S. News & World Report.
Healthcare data mapping is essential for integrating disparate systems, enhancing patient care, and increasing operational efficiency. However, successful implementation requires careful consideration of the associated costs.
While there’s an initial investment in data mapping, the long-term benefits often outweigh this. Determining the precise price can be challenging, as it depends on various factors.
Complexity of data sources
The format of data
System structural differences
Ongoing maintenance
Team size and composition
Project duration
As healthcare becomes increasingly data-driven, future trends include enhanced interoperability, AI-driven analytics, blockchain integration for data security, and predictive modeling for personalized medicine. However, there are some key trends to watch.
Data mapping usually involves converting the data format (e.g., CSV to XML) to ensure compatibility. Semantic data mapping aims to understand the meaning behind the data. It uses ontologies and logical graphs to understand the relationships between data points better. This enables more accurate data comparison and analysis, leading to the advancement of personalized medicine and improved patient outcomes.
Data mapping often involves sending all data to the cloud for analysis. However, with IoT devices generating a constant stream of vital signs and sensor readings, this approach is not practical. That’s where edge computing comes in handy. It processes important data right on the devices or gateways. This enables real-time analysis and immediate action, such as triggering alerts for abnormal readings.
Data mapping is crucial for managing the vast amount of healthcare data generated. With data mapping, healthcare providers can deliver more informed care, reduce errors and operational costs, and personalize treatment plans. This results in a healthcare experience that is more efficient, effective, and patient-centered for everyone.
However, successful implementation requires careful planning and experience. Our team of experts can help you navigate the complexities of the process and ensure a seamless transition. If you’re interested in learning more about data mapping, its potential benefits for your business, and how we can help you leverage it for positive change, don’t hesitate to get in touch with us.
Data mapping in healthcare is often used to exchange usable information between two or more systems such as an EMR or EHR for a specific purpose. The gathered insights can be used for dataset-based analytics, predictive analytics, medication testing, patient research, case studies, and more.
Data mapping facilitates care coordination and decision-making processes. It also streamlines data aggregation from multiple sources, such as EMR or EHR, for tasks such as performance analysis and trend forecasting. Also, data mapping helps safeguard patient data, ensuring compliance with privacy regulations like HIPAA and GDPR.
Healthcare data mapping, when done right, prioritizes security and regulations compliance. This requires encrypting data using robust algorithms and storing it in a protected environment, with access restricted to authorized personnel only. Also, being compliant with privacy regulations like HIPAA and GDPR allows for additional security measures such as access controls, regular audits, and staff training on data protection best practices.
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