The Importance of Sentiment Analysis In Healthcare

At a Glance: 

• Significance of Sentiment Analysis in Healthcare: In the digital age, sentiment analysis has gained popularity as a research method in healthcare where patient sentiments play a crucial role. Patient reactions, whether positive or negative, provide valuable insights for optimizing the patient experience and improving overall business outcomes.
• Application of Sentiment Analysis in Patient Communication: Patient sentiment analysis, often linked to the HCAHPS survey, enables healthcare providers to gauge patient satisfaction and identify areas for improvement. It helps in classifying patient comments, particularly regarding communication with healthcare professionals, providing granular insights into communication strategies and patient perspectives.
• Effective Implementation through Communication Hubs: Healthcare communication hubs can  integrate patient interactions, offering a platform for advanced sentiment analysis. By unifying patient sentiments delivered through various channels, these hubs facilitate improved communication, engagement, data analytics, and patient care management.

In recent years, sentiment analysis has become a popular and telling research method for organizations in various sectors. This trend has been accelerated in the age of digital media, where consumer thoughts and attitudes are visible everywhere, but often not organized.

Patients possess strong sentiments about the healthcare they receive. Virtually every interaction with a provider or a hospital will trigger a reaction, positive or negative. As a result, sentiment analysis in healthcare is very valuable.

The insights generated from an analysis of patient sentiments allow healthcare providers to bridge the communication gap between institutions and patients. This empowers them to optimize the patient experience and enhance business outcomes at a larger scale. This blog explores why sentiment analysis is important in healthcare, and how providers can make analyses work for them.

What is sentiment analysis?

Sentiment analysis is “contextual text mining that identifies and extracts subjective information in source materials.” In other words, this type of data gathering allows organizations to understand “the social sentiment of its brand, services, or products while monitoring online conversations.”

Sentiment analysis applies an amalgam of statistics, machine learning, and natural language processing (NLP) to identify and extract subjective information from text files, such as consumers’ judgments, opinions, feelings, thoughts, or assessments about a particular brand, topic, or event.

Also known as opinion mining, it helps uncover opinions, attitudes, and emotions based on what people say about certain things. Models of sentiment analysis focus on polarity (neutral, negative, positive), but also emotions and feelings (sad, happy, angry, etc.), intentions (interested vs. not interested), and even urgency (urgent or not urgent).

In healthcare, patient sentiment analysis helps providers gain a competitive advantage over their rivals since it enables service improvement based on their thoughts and feedback. Results from such analyses empower providers to get deeper insights into required treatments, the kind of quality of services consumers want, as well as the type of hospitals they receive treatment from.

Patient sentiment analysis often occurs in the context of an HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) Patients’ Perspectives of Care Survey. This survey is a “national, standardized, publicly reported survey of patients’ perspectives of hospital care. HCAHPS (pronounced “H-caps”), also known as the CAHPS Hospital Survey, is a survey instrument and data collection methodology for measuring patients’ perceptions of their hospital experience.”

In essence, sentiment analysis in healthcare is an accessible form of big data analysis that enables providers to figure out: Are their patients happy? What are they doing well? What are they doing not so well?

Sentiment analysis in healthcare helps providers improve patient communication

In the mission to provide high-quality healthcare, communication is crucial. Healthcare providers improve patient experience and health literacy when they implement healthcare communication strategies.

Patients want to easily schedule and reschedule appointments, access information, respond to questions, and so on. We all hate getting stuck on hold or embroiled in phone trees. We all want to communicate with providers and doctors quickly and easily.

Sentiment analysis in healthcare can tell providers whether these or other causes are frustrating patients. It gives providers a window into patient perspectives so they can see what matters to them, and how well they are communicating with them.

One of sentiment analysis’s benefits is that classifying patients’ comments into various HCAHPS categories becomes possible. This segmentation allows for highly granular analysis. Providers can examine communication with doctors, communication with nurses, the responsiveness of hospital staff, and more. This deepens providers’ understanding of their HCAHPS scores and what factors are impacting their communication with patients. The foundational sentiment analysis methods are:

1. Analyze the data collected to find out the most common complaints or compliments.
2. Segment information based on clinicians or departments, and other parameters to recognize opportunities for patient care improvement.

Sentiment analysis quantifies employee and departmental performance

In short, sentiment analysis in healthcare allows providers to identify where they are excelling (and where they could be failing) in terms of what they are providing patients. This includes the crucial category of patient communication strategies.

Sentiment analysis in healthcare allows providers to classify patients’ comments into components: people (nurses or physicians), places, and processes. By scoring comments on whether they are positive or negative, hospitals can quantify patients’ experience and identify areas of improvement.

Here are some examples that patients may say about their experience:

• “Helpful and caring nurses. They responded to my healthcare needs with care and urgency.” (Positive)
• “Excellent customer care but appointments need to be automated.” (Neutral)
• “I sat for hours on hold waiting to talk to a receptionist.” (Negative)

Patient sentiment analysis allows providers to collate such comments based on their frequency and intensity. This helps determine areas where the practice performs excellently, where there is a need for improvement, and where capacities are failing.

Enable effective sentiment analysis through communication hubs

Sentiment analysis depends on the analysis of text to detect positive or negative sentiment. This becomes one of sentiment analysis’s challenges, as the text that contains patient sentiments is splashed everywhere across the internet. It is available on multiple channels, such as social media, websites, forums, and many others.

In short, the raw material of sentiment analysis is spread far and wide. There is lots of it, and more of it appearing all the time. It’s difficult to get a handle on all of it. As a result, most healthcare providers have limited capacity to collect, organize, and synthesize patient sentiments.

Healthcare communication hubs address this issue by creating value through integration. Patient communication hubs unify the full lifecycle of patient interactions by delivering multilingual and conversational messaging to consumers’ preferred channels. Every single instance of patient sentiment delivered over SMS or message can be automatedly captured and logged.

Such sophisticated hubs facilitate advanced sentiment analysis benefits: patient health management, data analytics, and much-improved communication and engagement. Advanced communication hubs provide a logical, organized platform where providers obtain vital sentiments from their patients.

Unlike most EHRs that simply collect and retain data, advanced hubs act as sophisticated data repositories. Through methodical normalization and data mapping, they provide standardized, aggregated, and structured data sets ready for sentiment analysis methods that open doors to better patient care, potential ROI, and overall, greater efficiency.

Redefine marketing strategies through sentiment analysis

Information obtained through sentiment analysis in healthcare optimizes providers’ marketing strategies. Listening to consumers’ thoughts and opinions about your hospital or clinic helps in tailoring your processes and methods to consumer needs.

Bolstered with an accurate analysis of the patients’ sentiments, public-facing departments can personalize messaging and attract more patients. Sentiment analysis also allows healthcare organizations to provide better transparency and support through relevant and up-to-date information.

Finally, continuously monitoring discussions on the portals and social networks will also enable healthcare providers to mitigate brand damage. Crises can arise from poor service, or other social issues, such as environmental impact. If providers cannot deal with such issues immediately, negative patient sentiments may become viral, leading to brand damage. ♥