Beyond the EMR – Medical Research Needs Structured and Unstructured Data

Healthcare data plays a vital role in advancing modern medicine. It helps shed light on the root causes of diseases, create innovative treatments and therapies, and enhance patient outcomes. For these reasons, healthcare research needs access to a diverse array of data, including both structured and unstructured data.

EMRs (Electronic Medical Records) and EHRs (Electronic Health Records) contain both structured and unstructured data. Structured data, such as patient demographics, medication lists, laboratory results, and treatment plans, is organized in a defined format and stored in fields within the EMR/EHR system. This type of data is easily accessible and can be processed by computer algorithms, making it convenient for analysis and research.

On the other hand, unstructured data, such as physician notes, reports, images, and videos, is not organized in a defined format and is more challenging to access and analyze. Despite its limitations, unstructured data provides valuable information about a patient’s health history and experiences that cannot be captured by structured data sources. Clinical events that are documented in physician notes often go undetected. Advanced artificial intelligence platforms can utilize natural language processing and mapping to extract insights from both structured and unstructured data. This offers a comprehensive picture of a patient’s care journey and detects subtle events that were not previously detected.

Accessing both structured and unstructured data can pose a challenge due to the fragmented nature of their storage, which is often in siloed systems and not interoperable. Although EMR/EHR systems play a crucial role in healthcare research by offering a centralized repository of data, they are not a comprehensive source of clinical information for research and analysis. To unlock the full potential of healthcare data and advance the field of medicine through research, it is necessary to unite data from diverse medical sources and eventually, patient-generated sources. A secure Trusted Data Environment can help.

Trusted Data Environments integrate a wide range of data. This includes structured and unstructured information from all corners of the organization to unlock valuable insights and optimize clinical, operational, and financial outcomes. Trusted Data Environments also enable healthcare stakeholders to participate in external research initiatives by securely sharing critical data to enhance patient outcomes while always maintaining the integrity of the data.

In conclusion, structured and unstructured data are both vital components of healthcare research and comprehensive patient care. Researchers must have access to all types of data in order to fully understand and address the complexities of modern medicine.

About Lynx.MD

Lynx.MD offers a secure, SaaS medical intelligence platform for sharing real-world clinical data, accelerating research and development, and providing transformative analytics. With the Lynx Trusted Data Environment (TDE), organizations can collaborate with internal and external developers, data scientists, and researchers to build the next generation of data-informed applications, therapies and care options.