How to extract data from EMR?
How to extract data from EMR might be a complex task if you’re unaware of all the options available. Normally, EMRs sometimes contain a mixture of structured and unstructured data.
While most EMR data extraction activities require pulling out data from structured elements, a significant volume of unstructured data must be highlighted. In this blog post, we will show you how to extract data from EMR in the easiest ways. Read on!
What is an EMR?
Before we answer your question about how to extract data from EMR, it’s evident to define an EMR in the first place. Mainly, electronic medical records are digital versions of paper charts in clinician offices, clinics, and hospitals. EMRs contain notes and information collected by and for the clinicians in that office, clinic, or hospital and are mostly used by providers for diagnosis and treatment.
On the same note, you might be lost regarding the difference between EHR and EMR. Click on the following link for everything you want to know.
Check out these articles after you’re done
What EMR brought to Healthcare
To explain how to extract data from EMR, let’s take a look at some of the EMRs benefits:
1- Less medical errors and administrative mistakes in comparison to paperwork
2- EMRs reduce administrative costs
3- Workflow optimization and mistakes diminishing
4- No more conflicting treatments and duplicate tests
5- Quicker and better primary care
6- No more conflicting treatments and duplicate tests
7- Tracking data and results in time
8- Improving patient diagnosis and public health
9- Identifying the population in need of preventive care and screenings
10- Better privacy and security when it comes to patient health data
11- Wiser decisions based on data
12- Self-care suggestions, web links, and reminders to ensure follow-up
13- Allowing the patients to access their records, take a look at their prescriptions and follow the required changes in lifestyle
Natural Language processing
Are you asking how to extract data from EMR? Then the first method you might want to explore is NLP data extraction! Ideally, the Natural Language Processing method effectively extracts data from clinical notes in a free-text format.
Now, how to extract data from EMR using NLP data extraction? Here’s the answer. NLP algorithms can find relevant healthcare-specific keywords in a text document. These include drug codes, diagnosis, clinical procedures, etc.
Consequently, after pulling out data from clinical notes, the algorithm can put them into a single record. Then a machine learning application can make patterns evident.
Artificial Intelligence tools
Mainly, when it comes to extracting data from EMR, it’s evident that AI tools are best used to extract unstructured data. Researchers have found that overall, structured EMR data did not meet the requirements for regulatory grade criteria, while unstructured data did.
That said, they conclude that using a preprocessor for EMR data extraction helps transform data into a format suitable for established machine learning techniques. Hence, the essence of the framework is to solve problems associated with EHR and EMR data extraction, such as:
- Unstructured data
- Missing values
- Several data types
- Dissimilarities in sampled data
Application programming interface
Speaking of how to extract data from EMR, you should know that investing in APIs will make extracting data easier. Ideally, with APIs, you can extract data from your EMR and transfer it to an archive or send it to another provider. Similarly, patients can access and compile their data from different providers and view them in one place. The data compiled will allow doctors to make effective decisions and recommendations from complete information.
Finally, choosing the most suitable tool for effective data extraction requires expert help. Hence, our team at Ambula Healthcare is always ready to answer your questions and help you choose the right tool for you! Contact us today at (818) 308-4108. And now paper charting vs electronic charting: which one is better?
