Using NLP on Written SOAP Notes to Compartmentalize Data for Informatics. A Speedier Workflow

A natural language processing (NLP) tool can work wonders for any healthcare organization’s data management processes. When using NLP on written notes, you can easily convert the information from these notes into digital data and add them to an electronic health record (EHR). Read on to learn more about how you can use this technique to create a faster workflow.

What is NLP?

Natural language processing provides an automated and scalable way to convert written data into structured data. Most commonly, it refers to a computer’s ability to understand human language, but it can also refer to a computer’s ability to understand human writing. NLP can be used in a variety of scenarios, but it’s particularly useful for converting handwritten notes into data that can be used in an EHR. This data can be used to flag patient concerns, generate reports, and track progress over time. With NLP, you can quickly gather data from written notes and then use that data in a variety of ways.

The Importance of Written SOAP Notes

When a doctor or nurse documents a patient encounter, they’re required to use a standardized format. This format includes a set of headings, such as Subjective, Objective, Assessment, and Plan. These headings provide an outline that helps a doctor or nurse include important details about a patient’s condition. Most healthcare organizations require written notes as part of their documentation process. Written notes have various advantages, such as helping healthcare providers focus on the patient rather than on their computer screen. The Subjective and Objective headings are useful for recording a patient’s chief complaint and the findings that led to the diagnosis. The Assessment heading allows a healthcare provider to document their thoughts on the patient’s diagnosis, their overall health status, their risk of complications, and their treatment plan. And the Plan heading allows providers to list out the tasks they need to complete before the end of the visit.

Benefits of Using NLP on Written Notes

- Faster data entry - When you use NLP on written notes, you can convert handwritten data into digital data much more quickly than you could with a manual process. The faster data entry also allows you to generate reports more quickly.

- Organized data - Using NLP on written notes allows you to organize patient data more effectively. The structured data derived from written notes can be used in a variety of applications, including an EHR, a physician order entry system, or a lab results system.

- More accurate data - Because NLP is computer-generated, it doesn’t make the same types of errors as a human note taker. This means that the data it generates is more accurate.

- Data integrity - Using NLP on written notes also ensures data integrity. This means that the data is accurate, timely, complete, and maintains consistency across different providers and facilities.

- Patient privacy - Since NLP converts data from written notes, it’s important to recognize that the data won’t be completely verbatim. This means that you should take care when reviewing the data and make sure that you’re not violating patient privacy.

How to use NLP on Written SOAP Notes?

There are a few things to keep in mind when using NLP on written notes. First, make sure that your written notes follow the SOAP format. This will make it easier for the NLP tool to recognize the information. Then, use an NLP tool to convert handwritten notes into digital data. You can do this either manually or with an automated tool. The more advanced NLP tools will have various customization options that can help you tailor the conversion process.

Use NLP and EHR data together

As you use NLP on written notes, you’ll also be adding that data to your EHR. You can use this data to generate reports that help you track patient progress over time and flag patients who are at a higher risk of developing complications. Once you’ve used NLP on notes and integrated that data into your EHR, you can use it in other ways as well. For example, you can use it to generate alerts when a patient is due for a follow-up visit or to flag patients whose symptoms indicate a need for further testing. To do this, you’ll need to define an ontology that includes the codes and relationships that you want to see in your reports. You can then use this ontology to populate your EHR with data from your written notes.

Conclusion

To use NLP to its full potential, you need to start with written notes. By using NLP on written notes, you can quickly turn handwritten data into structured data that can be used in an EHR. By taking this approach, you can save time and effort and ensure data accuracy. You can also use the EHR data to generate reports, alerts, and other tools that help you improve patient care.