Natural Language Processing (NLP), a specialized type of artificial intelligence (AI) that derives a person’s intent from unstructured text or speech, is a powerhouse technology based in automation. It quietly works behind the scenes to improve patient experience by answering patient questions in real time, confirming appointments, and alleviating strain on staff. It can even take in data to answer questions within patient charts, portals, and electronic health record (EHR) systems.
Here is an overview of NLP’s appeal, how it helps health systems, and why developing it across languages is important for diverse patient populations and improving healthcare literacy and equity.
How Natural Language Processing Enhances the Patient Experience
Many industries incorporate NLP into their capabilities. Commercial businesses have adjusted to the demand for real-time, non-business-hours interactions by adding digital assistants and chatbots to power their customer service applications In healthcare, NLP can transform communication for patients when they seek and receive care by offering a new avenue into patient engagement. Patients and their caregivers are busier than ever, balancing their work and personal lives. This means that your facility's hours may not always be the best time for patients to engage with you. Our Communication & Reminders patient outreach solution allows your organization to meet patients in their moment of intent and respond at any given moment to a request. Even more, with NLP, you can respond to the patient outside of regular business hours without requiring any staff overtime or evening hours. In this respect, AI-powered NLP is a strong, behind-the-scenes driver for transforming patient communication and experience.
What is the Difference Between NLU and NLP in Health?
To provide the best results, NLP works closely with cognitive search and Natural Language Understanding (NLU). For example, when NLP encounters a phrase or question that it has not been taught to understand, such as, “How long will my appointment be?” or “What is the address of my appointment?,” cognitive search enters the playing field.
Cognitive search’s job is to search across a large body of pre-approved information (FAQs, manuals, etc.) to provide the most relevant response to the seeker. Similarly, NLU is designed to consider additional context (for example, the user’s location) to better understand patient needs.
NLP’s applications include:
Messaging within EHRs (Electronic Health Records)
All of which broaden the ways that patients can reach out, respond, or pose a question to their provider or health system.
NLP Helps Patients Feel Heard and Understood
Properly configured NLP makes the user feel understood by technology rather than frustrated – increasing patient satisfaction and reducing friction.
By enabling increased sentiment detection with NLP, provider communications can measure a patient’s frustration or satisfaction to uniquely respond to patient needs. NLP can further understand the sentiment in a patient’s response or question, whether through a message received following an appointment reminder or an update sent via text. By identifying sentiment and intent, this use of technology plays a unique role in remotely triaging and interacting with patients using knowledge and empathy.
Even more, NLP can help solve a problem or concern by identifying certain words before a complaint occurs and can also be leveraged to better understand sentiment, detect patient satisfaction, questions, and trends to build a robust repertoire of data for more personalized, tailored responses.
How Hospitals and Health Systems Benefit from NLP
The impact of the pandemic has created and heightened healthcare concerns, including the impacts of delayed care and higher patient volumes. The ensuing escalation of questions directed to clinicians has placed significant pressure on health systems to schedule patients and efficiently manage administrative tasks.
According to a McKinsey report on AI, the implementation of NLP provides positive opportunities for automation. NLP can aid providers in efficiently catering to increased demands by automating communication with patients, including triage, and sharing reminders and updates, which enables providers to shift more time and attention toward in-person visits.
How Does NLP Serve Non-English Speaking Patient Populations?
Although the technology is making strides in enhancing the healthcare experience, it is undergoing constant refinement as patient needs and inquires evolve, including being developed in languages other than English. If your NLP is not designed to comprehend languages beyond English, some patients will face immediate access barriers, affecting their ability to seek further guidance and action.
The potential for NLP is vast, and the ways it uniquely leverages AI, detects sentiment, and draws from data sources to respond to patients serves as the key to unlocking the doors to a new frontier of patient engagement.