The Corona pandemic has pushed the healthcare industry almost to its breaking point. The massive influx of Covid-related phone calls, a large number of tests, and a growing number of hospitalizations are draining healthcare resources. Innovative solutions are needed to ease the workload of healthcare professionals.
A coronabot is a conversational chatbot linked to a time-booking system. All coronabots have one thing in common: a function called a symptom checker. A symptom checker is a set of questions whose answers recommend a course of action. Some coronabots are also linked to a lab-testing system and send a text message to citizens who have negative test results. All of this happens automatically, while the testing and lab work still need to be done manually by healthcare professionals.
In healthcare systems without coronabots, a healthcare professional takes the Covid-19 call, books the time for the test, and reports the negative results manually. This takes ten to fifteen minutes of work per case. A coronabot cuts that time to zero. For 10,000 monthly Covid-19 calls, the saving is equal to the workload of about ten full-time professionals.
But the savings materialize only if citizens know about and use the service. Luckily they are doing so and in high numbers. Coronabots are about as close as you get in the software industry to a perfect match between need and solution.
Using a coronabot’s symptom checker requires fewer digital skills than writing a text message or attaching a photo to Facebook. There is no waiting in line, it is available 24/7, and it costs close to nothing to run. A coronabot is also more private than a phone call, and you can use it almost anywhere.
Coronabots are the first mass-use symptom checker applications that are integrated to care processes and systems. They will pave the way for a wider range of integrated symptom checkers and change the way primary healthcare is provided for high-volume ailments with mild symptoms.
Matti is an expert in customer feedback management, marketing automation, predictive marketing analytics, and how to use data and machine learning to automatically trigger customer interactions. Before joining TietoEVRY, Matti worked for a customer feedback analysis company Etuma and before that Nokia in the U.S.