Natural Language Processing (NLP) helps computers understand the meaning, intent and sentiment behind a conversation. NLP is the modern technology that is responsible for computer software that translates text and responds in real-time. Natural Language Processing is commonly used in business solutions and processes to improve efficiency or streamline customer support. Conversational AI apps use NLP to build patterns and algorithms that support natural dialogue. In the healthcare industry, there are a wide range of specific uses for the technology and how it can advance or improve patient care.
How is NLP used to Power Software?
Conversational AI is based on Natural Language Processing and this technology can be leveraged by automating dialogue or detecting data correlations. NLP is a branch of artificial intelligence that breaks down conversations into fragments so that computers can analyze the meaning of the text the same way a human would analyze it. The complex technology uses word choice, sentence structure, and tone to process a text or voice response for a virtual agent.
Conversational AI is the modern technology that virtual agents use to simulate conversations, so NLP is useful in supporting those types of applications. By using data and mimicking human communication, it helps computers talk with humans in a more advanced way. There are also other ways to use Natural Language Processing. Research, data mining, note taking, and real-time queries all can benefit from NLP. This type of technology is moving the healthcare industry into the future.
How is NLP Used in the Healthcare Industry?
Since NLP software can decipher speech, it has become an effective tool for updating records for patients, managing patients requests or conversations, and improving office visits. From making appointments to taking notes, Natural Language Processing allows physicians and healthcare employees to spend less time collecting information or searching for data. This frees up time for the staff to spend with the patients or for the employees to perform other important tasks. From an operational standpoint, NLP applications take some of the weight off of the staff and place it on technology.
Natural Language Processing provides the power and insight to take any floating data and make sense of it, while maintaining security and HIPAA compliance that are essential in the healthcare industry. All of the patient records that the healthcare industry has at their fingertips are often sitting around, without the ability to be useful or organized. NLP can make sense of all of the data, access it immediately, and help experts in the industry make more informed decisions with the results. NLP will continue to modernize the healthcare industry with the applications below.
Top NLP Applications in Healthcare?
Recognizing Data Subsets
Since NLP can interpret large amounts of data, concurrently and in real time, it has become useful in the healthcare industry for analyzing patient information. It has the power to recognize patterns, or subset of data, which provides the healthcare employee with backup up on any assessments or evaluations. By indexing data points, the data can lead to conclusions, assessments, and provide much needed insight that wasn’t available with previous technology.
Organizing Unstructured Data
If physicians are all writing notes in their files, or using siloed note-taking platforms, all of that information gets buried behind paperwork or closed portals. Some doctors are using shorthand, or acronyms, and other doctors are logging notes into a patient file that sits unused in a software or profile. Natural Language Processing makes those notes easier to search, understand, or reference in the future. Most notes in the healthcare industry are sitting around without any structure or process. The dots can’t be connected this way- not for healthcare employees or for patients. By using speech algorithms that can learn, NLP makes the data usable and accessible so that AIs and physicians can learn and act on the information they have stored.
Appointment Setting, Confirmation & Cancellation
Instead of using a staff member’s day to set appointments for patients, call and confirm future appointments, or handle incoming cancellation requests- Natural Language Processing can do all of that. A healthcare office might have multiple front desk staff members solely handling those tasks. This shift to using Conversational AI applications can not only free up employee time, it can save money for the company and save frustrations on the users’ end.
How many times have you called a doctor’s office and been put on hold when you just want to cancel or reschedule your appointment? When you get a call from a doctor’s office just to confirm your appointment, do you really need to be speaking to a live agent? Probably not. Conversational AIs that are powered by NLP can handle making those phone calls for the office team. A virtual agent can ask the questions that would assist the patient in making an appointment, rescheduling an appointment, canceling an appointment or confirming an already made appointment. NLP can free up your office staff while improving your patient experience. Everyone gets their desired solution faster and easier. NLP can also help refill prescriptions or answer post-operative questions, automating these tasks.
Note Taking During Appointments
Physicians, nurses, and dentists can utilize NLP tools to take notes for them. Instead of spending an appointment scribbling notes in a file, or typing the entire session, healthcare employees can listen and focus on the needs of their patients. Natural Language Processing is a reliable way to aggregate the notes and reduce errors while recording the necessary information. This type of clinical support helps physicians with diagnostics, risk assessments, and reduces medical errors. The employee can focus on the patient while they are in the office and review the notes, conclusions, or patterns in data at another time. The human touch of a being in an office, or making eye contact on a telemed call, can return to the experience.
Modern Clinical Support
NLP tools go a step beyond transcription. As this type of software improves, there are exciting improvements on the horizon. Natural Language Processing can help learn from the data, detect patterns, and possibly assist physicians in detecting problems or conditions. If Natural Language processing can pick up on symptoms and learn to research in real time, it could be a technological assistant to the physician. By decoding language in real time, NLP could support research, solutions, and plan next steps in reports for the healthcare employee. This type of healthcare support is the key to the future. A human can only process as far as their current capacity allows them. With distractions, limited experience, long days, or rare conditions- human error can cause someone to miss something that NLP could pick up on.
All of these examples show how Natural Language Processing can change the method in which the healthcare industry delivers patient care. By improving the way that the industry can interact with the patient, while retaining the information in an accurate and timely way, NLP platforms can improve the patient relationship in the office and in the contact center.
Exact data, based on precise metrics, is something that all healthcare fields strive for. If you are looking for more details on how Plum Voice has previously worked with healthcare companies, read a case study from another client about custom built solutions that helped them reach their goals. Natural Language Processing in healthcare can create new opportunities or changes to your operations.
The bottom line is that people working in the healthcare industry could always use more time directing their energy on their patients. NLP tools can aid in this by taking over some of the redundant tasks that staff members are doing. A large IT team or on-staff developer is not necessary to get started. Find out how a custom NLP solution could unlock new potential for your team.