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unstructured data in healthcare

You can imagine, encountering and dealing with hundreds of individual healthcare data signals from every patient can get confusing at times. Having a massive amount of Unstructured Data in Healthcare makes things complicated, however; there is an expectation from medical professionals to make important decisions and provide the right solutions. Even the care team needs to follow sets of rules to make things less complex. Care teams create and add new patients to medical records and Doctors assess, diagnose, and treat patients.

When things don’t go hand in hand, it can get overwhelming for medical professionals to deal with the huge amount of unstructured data in healthcare. So, the question is – How to unlock the unstructured data in the Healthcare Industry for new insights into improving patient care?

Let’s find out your answers in this article, keep reading!

7 Challenges and Solutions for Unstructured Data in Healthcare

Dealing with a massive amount of unstructured data in healthcare can be really challenging. The risk of errors happening is much higher with unstructured data, and the end results can be drastic. Healthcare professionals are known for treating all the patients with utmost care, attention and there is no room for errors. Any doctor wouldn’t want to put their patient’s lives at risk. So, to make the unstructured data in Healthcare actionable and accessible, we have found some ways to overcome different challenges. Let’s explain to you about them below.

Interpreting Handwriting

medical structured and unstructured data

Many times, it gets difficult to understand the Doctor’s, Nurse’s, and other Care provider’s handwriting. You may say that this is a problem that can’t be rectified manually. Well, the world has advanced in the technological field drastically, so why not utilize it to reap the maximum benefits!

Natural Language Processing (NLP) is a type of Artificial Intelligence (AI) technology. Indeed, this is the key to make handwriting notes usable in the computer system. NLP doesn’t just recognize characters but also draws some conclusions and understands intent, like abbreviations and misspellings. Doesn’t that sound amazing!

Reading Radiological Images

unstructured data in healthcare

Analyzing X-ray, CAT, MRI, Ultrasound, and all kinds of medical images requires skilled, experienced, licensed professionals. This may also require taking a patient’s history and other variables into account to distinguish healthy tissue from abnormalities. So, if your patient data is not structured appropriately, it may get difficult for healthcare professionals to reach the right conclusions.

Artificial Intelligence or Machine Learning algorithms “Learn” from patterns of recognized images and correctly interpret the scanned results. So, integrating your healthcare systems with AI can help you read the radiological images with more accuracy, leaving no room for errors. Indeed, adopting AI and ML technologies can help medical professionals and organizations deal with the unstructured data in healthcare effortlessly!

Creating Metadata

medical structured and unstructured data

Metadata (in Healthcare) has applications where they can provide useful/functional information about a specific piece of health data. It can be used to index information that needs to be stored, retrieved, or exchanged beyond the facility walls.

You can preprocess unstructured data for use in an EHR or other system that requires structured data. For example, Codes or Keywords can be described by a Technician or a Physician, and metadata can be entered into the system, making the information easily searchable and accessible.

Accommodating File Size

medical structured and unstructured data

Unstructured data takes more storage than structured data. Why? Well, unstructured data sets are measured in terabytes and petabytes, and not in gigabytes. Thus, they require storage infrastructure with greater capacity. Medical structured and unstructured data has a high value which can be used by ghoulies. That’s why this massive data needs to be stored and protected under high-security systems.

Uploading huge-sized files on Cloud storage and then sharing it is a great way to save time and effort. Cloud servers are reliable as they are well-encrypted. Using multi-cloud clusters can help you get the information even if any of the servers crash due to downtime or other reasons. Plus your data is also secure!

Performing Searches

unstructured data in healthcare

In almost every industry, from surveillance systems to professional publishers, and even individuals constantly create audio content, videos, and use images. If we talk primarily about the Healthcare Industry, structuring and storing these media files in a systematic way is essential. Some databases, usually in the form of unstructured data do not understand the media file’s actual contents.

When you have the ability to understand and explain media, it is useful often in real-time, and also has far-reaching implications for Business, Governance, and Healthcare Industry. For example, recording 911 emergencies helps in medical investigations, analyzing patient history, preventing or detecting disease. In the same way, identifying the people in a video could be helpful for testimonials. Videos of patients could allow doctors to understand their medical needs and plan for the future.

Considering the massive volume of data involved, analyzing media file’s content manually can be challenging. To solve this query, you can start using automation solutions that are currently being developed. For example, to transcribe text out of audio files you can use speech-to-text technology, and that text can be analyzed to perform sentiment analysis. Meta tags are also helpful to classify media files and perform search operations. To store and arrange the data in a structured way, start using automation software. Such unstructured databases can be stored in Cloud space without a problem.

Using Streaming Data

unstructured data in healthcare

A traditional dataset typically captures information in a delineated time and space. In contrast, streaming data is the process of constantly generating and delivering a continuous stream of small files that capture event-based interactions on a second-by-second basis.

The relational databases that power almost every enterprise and every application are built on tabular storage. Using them to store unstructured data requires lengthy cleansing and transformation processes, creating engineering bottlenecks on ingest.

Typical data sources lend themselves to tried-and-tested forms of analysis and reporting and the potential of streaming data can be unlocked through experimental techniques, predictive modeling, and machine learning. Applying these techniques requires broader and more flexible access to information and can be helpful in structuring the data according to existing enterprise data warehouse specifications.

Managing Huge Data Volumes

medical structured and unstructured data

The first essential requirement to manage unstructured data is to start storing the entire data that you generate, no matter its form or where it is created. With modern technology, storing data has become cheaper; data that needs to be retained in the longer term can cost you as little as a few dollars per terabyte annually on cloud-based storage solutions.

Once you are done storing all this information, the next step is to gain insightsUse native tools, such as ReportMiner. This tool will help you extract unstructured data from different sources and systemize them with your structured data. By doing so, all your information is available for your data analytics tools.

Learn to Accept Challenges

Healthcare patients are actively looking for solutions that help extract value from unstructured data. It doesn’t matter if it’s about Medical structured and unstructured data, medical providers want to ensure that they get the maximum benefit from the data.

But when the industry faces financial pressure, new regulatory needs, and a paradigm shift to value-based care, they need practical ways to do it. If you don’t have the right resources to do so, UNV Healthcare can assist you in getting solutions to your complex problems and help you reach your desired goals.

How can UNV Healthcare help?

Best Healthcare Marketing Agency for Solutions for unstructured data in healthcare

UNV Healthcare is one of the best solutions to your Healthcare Marketing needs. Our business has been in the market for around a decade now. We provide multiple Digital Marketing Services under one roof.

With our knowledge and marketing expertise, we have helped many brands across the U.K., the U.S., India, Australia, Canada, and Singapore grow with our unique strategies. Our dedicated, experienced team of professionals always keeps themselves updated with the emerging technologies in the healthcare sector. They are potent enough to carry on deep research and will help you choose the best tools to integrate with your systems. Not only that, they will come up with robust strategies to make you stronger on the Digital Marketing front.

We deliver only the best as we love to see our clients win every time. If you want to take your medical practice to the next level and need more solutions for unstructured data in healthcare, feel free to contact us for more details!

Refer to Analytics Insight’s blogs to learn more, get new ideas, and know what’s going on in the Data Management World of Healthcare!

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