The acceleration of digital transformation in the past two years has forced healthcare leaders to adopt new technologies. Digital tools like chatbots and online symptom checkers are no longer a novelty, and have demonstrated value to patients and providers throughout the pandemic. Virtual care has become so ubiquitous that the number of virtual-first health plans is expected to increase from one plan in 2019 to 15 plans in 2022.
Most of this change has been welcomed by consumer experience advocates, who have worked for years to drive digital adoption. Now we carry the burden of proof that these technologies actually make the experience better.
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Annie Haarmann Annie Haarmann is Head of Healthcare Strategy and Consulting at Reputation and works with healthcare organizations to improve experience, drive quality and enable access. Previously, Annie led digital consumer experience for the nation’s leading health system and has held roles leading digital strategy in nonprofit healthcare, pharmaceuticals and bioscience.
Better Insights for Faster Innovation
Many healthcare organizations are adopting design-thinking and agile principles to drive faster transformation. These methods require a deep empathy of the patient. Unfortunately, traditional methods of measuring patient experience are not enough to support innovation. CAHPS surveys are slow to collect enough responses for statistical significance, let alone the time it takes to analyze and draw conclusions. These surveys are also limited to a structured set of questions, meaning anything outside of that structure will be excluded. I often hear from healthcare executives that they are making major investments in changes based on a survey with a six percent response rate or even lower.
The answer for healthcare is a continued investment in Artificial Intelligence (AI). Specifically, a type of AI called Natural Language Processing (NLP) technology analyzes large swaths of human language comments for key patterns, both in structured surveys and in an increasingly important source of learning: feedback “in the wild.”
Feedback “In the Wild”
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
Unstructured feedback data can be collected from thousands of external sources such as a Google Review about a physician or a comment on a clinic location’s Facebook page. Incidentally, this feedback “in the wild” has become so important that healthcare consumers rank it as the third most important factor—after insurance and location—when selecting a physician.
In addition to collecting data from external sites like Google or Facebook, you can enrich your data set by building feedback mechanisms into each step of the patient journey. Such “listening posts” can be as simple as a “thumbs up/down” button to indicate the ease of online appointment booking, or a quick 5-star rating at the end of a symptom checker chatbot interaction.
Here is where Natural Language Processing is especially critical. It’s impossible for a human being to keep up with the vast amount of unstructured feedback that consumers leave in real time across the web. But Natural Language Processing makes it possible to constantly track data in the wild, especially sentiment, both positive and negative. That’s how providers can quickly learn and improve before issues mushroom into bigger problems.
Using a “Voice of the Customer” Feedback Hub
If you only analyze a single channel of feedback, you may not observe the significance of a particular issue. Even worse, if each department relies on a different source of feedback data, they are seeing a limited view of the patient experience. Healthcare leaders will only begin to understand the “voice of the customer” by bringing all sources of feedback data into a single hub. For example, by analyzing CAHPS, social media comments and call center surveys together, you may see a more complete picture. Only then can you prioritize where and how to make changes.
A burden of proof is nothing new to healthcare, where we require evidence to support treatments and develop standards of care. This evidence requirement should also apply to our rapidly changing patient experience and digital solutions. Feedback and NLP can help healthcare leaders take a more scientific approach to digital transformation in 2022.
Photo: designer491, Getty Images
Annie Haarmann is Head of Healthcare Strategy and Consulting at Reputation and works with healthcare organizations to improve experience, drive quality and enable access. Previously, Annie led digital consumer experience for the nation’s leading health system and has held roles leading digital strategy in nonprofit healthcare, pharmaceuticals and bioscience.
