Patient Voice is the practice of analyzing patient feedback by the healthcare industry. Many organizations such as clinics, hospitals, and doctor’s offices take this data and analyze it to improve safety, quality of care, and patient experience. Patient feedback, opinions, and feelings are captured using sources such as post-appointment surveys, in-clinic questionnaires, feedback web forms, and phone calls. Healthcare providers are exploring the best methods to understand the patient voice and evaluate their service quality to offer a more positive patient experience.
Healthcare providers understand the importance of patient feedback analysis, and how it can enhance their experience of care efforts. Yet a lot of organizations are relying on slow and imprecise methods to extract the data they need to better understand what their patients are trying to say.
By measuring experience with new Patient Voice methods, communities such as hospitals, and even health insurance companies, can gain valuable insights into where in their organization they are doing a good job, and where they might need some work. In addition, they can use analytics tools to unlock the “why” they are performing well or not. This patient insighting doesn’t have to be manually tedious. Automated, machine-learned text analytics tools can be used to extract relevant content, perform sentiment analysis on the feedback, and then compile the results according to topic classification, aspect base granularity, or named entity recognition.
Innovative healthcare organizations look to engage their patients in dialogue during various stages in the patient journey. They also use outreach to gather and listen to the stories their patients are telling about their care. This outreach can consist of marketing campaigns, text messages, emails, patient portals, and even mobile apps. Creating dialogue, and listening to patient voices, has proven to drive engagement, improve the experience of care, and deliver higher overall healthcare satisfaction. Along with specific outreach, some wellness vendors have even started using social media listening and opinion mining to gather patient insights from Twitter and Google reviews to better gauge their progress in offering a more positive, holistic patient experience.
Patients with a better experience during a particular encounter have been proven to have less healthcare utilization and fewer complications after that visit. Establishing Patient Voice, while measuring and tracking its progress, will assist your healthcare organization in better meeting the needs of your patients.
Unfortunately, one of the biggest challenges experienced by the healthcare industry is taking all this unstructured patient data, and then quickly and efficiently making it more analytical, tangible, and actionable.
This is where Repustate's text analysis API can help.
Sentiment Analytics is the practice of using Natural Language Processing or NLP techniques to identify patient sentiments and opinions. By combining text analysis with machine learning, Repustate’s text analytics API can help you to quickly and accurately establish Patient Voice across strategically important topics and aspects in your healthcare experience delivery.
While Patient Voice surveys collect feedback from their answers to survey questions, sentiment analysis goes a step further. By gathering feedback from patient voice notes, surveys, reviews, and social media, you can take what your patients are saying in their surveys and understand where improvements are needed by gauging whether their experiences have been positive, neutral, or negative. When you combine sentiment analysis with patient voice, you’re gathering the emotional feedback of your patients.
The power of a great feedback solution is well known in many industries. Couple the benefits of a Patient Voice tool with sentiment analytics, and you’ve now got access to insights that will make your healthcare organization more data-driven and confident in its strategic decisions to improve the patient experience.