Healthcare Unstructured Data

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Healthcare organizations rely on the power of data to improve operational efficiency and gain valuable insight into patient health and treatment. However, of the volume of data that is available, only 10% – 20% of it is usable. As a result, 80% – 90% of healthcare unstructured data is not leveraged because it is too challenging to interpret.

In this article, we explain the differences between structured and unstructured data. We also explore the cutting-edge technologies that now make it possible to leverage previously inaccessible data types and transform them into actionable business intelligence.

 

What Is Structured Data?

Structured data types, also known as relational data types, can be managed and searched in a relational database or through a relational database management system (RDBMS). This includes integers, decimals, dates, time, strings, and Booleans. 

These data types are easily arranged in rows and columns and can be queried using programming languages like SQL to return relevant search information.

 

 

Examples of Structured Data in Healthcare

In healthcare, structured data is predominantly used to record patient information in electronic health records (EHR). Here are some examples:

  • A medical test result can be recorded in the form of a numeric or Boolean value.
  • Physical measures like height, weight, blood pressure, blood type, and stage of the disease can be recorded numerically.
  • Dropdown menus can be used for storing demographic information.
  • A radio button can be used to denote the patient’s gender, marital status, and other binary values.

In each example, what makes the values structured is the ease with which they can be parsed by computers and queried by humans. 

In an effort to make clinical data even more uniform and accessible, projects like the Structured Data Capture (SDC) Profile have provided an infrastructure for capturing, exchanging, and utilizing EHR data to improve clinical research, enhance adverse event reporting, and optimize public health reporting.

 

What Is Unstructured Data?

Healthcare Unstructured Data

Source: Deloitte

Unstructured data is any data type that cannot be stored in a relational database or RDBMS. Data in the form of images, videos, audio, webpages, free text, and even social media content fall into this category. This type of data is too complex to be parsed and interpreted. Of course, this data can still be stored, retrieved, and edited by other means.

Unstructured Data Examples in Healthcare

Like the lost treasures of Atlantis, unstructured health data remains one of the most precious and untapped resources in the healthcare ecosystem.

While determined medical professionals can certainly make use of this data, the process is time-consuming and fails to produce an overall, cohesive picture. Here are some examples of unstructured data:

  • Medical images such as PET, CAT, and MRI scans, as well as X-rays and ultrasounds.
  • Text files of varying lengths, such as medical notes and evaluations.
  • Social media content and comments pertaining to your practice or institution.
  • Audio recordings from speech therapy sessions.
  • Faxed versions of structured data.

 

Semistructured Data

For the sake of completeness, it’s also worth touching on the structural grey zone known as semistructured data. While this type of data cannot be stored in traditional databases, it does contain some inherent organizational features. This makes it simpler to parse than unstructured data, but more complicated than structured data.

Semistructured data can be managed in a non-relational database, also known as a NoSQL database. Instead of being stored in tabular form, non-relational DBs store data according to four flexible, non-tabular models. These are: 

  • Document databases
  • Key-value databases
  • Wide-column stores
  • Graph databases

Of course, this increase in flexibility corresponds to an increase in indexing difficulty. The most pertinent example of semistructured data is email.

Emails contain metadata (like internal markings and tags) that make them searchable with keywords. Semistructured data accounts for roughly 5% – 10% of all collected data.

 

Learn More About Managing Healthcare Data:

 

How to Leverage Unstructured Data in Healthcare

With the advent of artificial intelligence (AI) and machine learning (ML), enormous amounts of unstructured data can now be analyzed and mined for actionable business intelligence.

One of the leading technologies in this space is Natural Language Processing (NLP). NLP uses machine learning algorithms to convert human speech into machine-intelligible data. The process combines the power of computer science and linguistics to investigate the structure and rules of language.

Over time, NLP software becomes an intelligent system capable of comprehending, interpreting, and extrapolating meaning from speech and text.

Here are just a few examples demonstrating what NLP can do with unstructured data:

  • Extract key medical information from free-text clinical notes.
  • Organize each critical data point in terms of ICD-9/ICD-10 codes, in addition to HCC codes.
  • Extract key medical information from free-text radiology reports.
  • Convert unstructured data into structured data and transfer it to an EHR.
  • Compare like-findings to a database of similar medical reports.
  • Recruit patients for medical trials based on matching criteria.
  • Transcribe reports using speech recognition while adhering to healthcare data standards.
  • Extract medical codes and critical information by analyzing speech reports.
  • Prescribe treatment options using clinical decision support.

Additionally, NLP can actually improve regulatory compliance: Assigning accurate medical codes can facilitate faster insurance reimbursement and reduce the rate of claim denials.

Structured Data in Healthcare

Transform Your Healthcare Unstructured Data Into Actionable Business Intelligence

Ready to take your business intelligence to the next level? At True North, we can help you implement, migrate, and manage the latest machine learning software to make the most out of your unstructured healthcare data.

Take command of your healthcare IT and accelerate patient outcomes. It’s time to leverage the full power of your unstructured data to deliver the best patient care. Contact us today for your free IT consultation.

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