How Chatbots Helped One System Reduce COVID-Related Call Volume

A few hospitals and health systems have been using chatbots for several years, but they came into more widespread use last year to help deal with the high volume of phone calls and emails they received about COVID-19.

One such system was Intermountain Healthcare in Salt Lake City, Utah. According to a news release from Gyant, a San Francisco-based company that develops virtual assistants for the healthcare industry, it worked with Intermountain to develop the COVID-19 Screener and Emergency Response Assistant (COVID-19 SERA).

The online tool uses information from the Centers for Disease Control and Prevention (CDC) and Intermountain infectious disease clinicians to screen users for COVID-19 symptoms and risk factors, and directs them to appropriate medical settings.

More than 157,000 people used COVID-19 SERA in the first 2.5 weeks it was available. That corresponded with a 30 percent decrease in call center volume, according to the news release.

While this is unquestionably a great result, chatbots have limitations. If you’ve tried to converse with a chatbot more than once or twice, you’ve probably had the exasperating experience of not being able to make it understand you. Perhaps you asked it a question and the chatbot responded with an unrelated answer. Or maybe your question sent the chatbot into a tizzy, and it just took you back to where you started.

The bottom line is that chatbots can be effective for some uses, but they are ineffective for other, more complicated applications. And as the use of chatbots increases within the healthcare industry, artificial intelligence’s (AI) ability to understand and interpret what your customers are saying becomes more critical every day.

Read the full article now and learn more: Do Chatbots Speak Your Patients’ Language?

Best regards,
Matt Humphrey
President