Maintaining Successful Patient Engagement with Algorithmic Empathy

by March 10, 2020 0 comments

Today, the healthcare sector is increasingly leveraging AI-powered chatbots that are able to respond to patients with queries abruptly. However, in case of managing successful patient engagement with these AI-enabled bots, there is a need for emotional appropriateness of the responses to patients’ answers, something which is called algorithmic empathy, according to an article by Erik Birkeneder in Forbes.

Maintaining patient engagement through empathy can lead to more customers and better outcomes. But if a patient comes with queries like they have cancer and in response an AI bot gives an answer with just saying “That’s too bad”, it might reduce engagement. Despite, if the bot gives a more emotionally response, this will make patients continue the chat that will ultimately improve engagement.

GYANT, a San Francisco based AI-driven care navigation company, found that engagement was increased when patients are given the right feedback, as the right feedback reflects listening and understanding, which builds trust.

 

Mimicking Empathy in Healthcare

The human touch is an integral part of practicing medicine as it enhances the relationship between patient and doctor. With an appropriate human touch, patients can feel they are taken care of by a fellow human being, and they are not alone in need. However, as the need of healthcare services is rising, shortages of doctors are also increasing as the WHO estimates a shortage of 4.3 million physicians, nurses and other health workers globally.

At the same time, medical virtual assistants, healthcare chatbots or humanoid robots with a pinch of empathy grasp the moment and claim their places as new assistants of medical professionals.

In one report, patient loyalty consistently boiled down to three factors, including communication, care coordination, and empathy. By shifting to patient-centric health care and consumerism among patients, patient satisfaction is becoming more significant than ever to the bottom line of providers.

So, to augment patient satisfaction, many care providers are leveraging bots to interact with patients and provide on-demand access and answers. However, they are also faced with the challenge of humanizing these bots.

In a book, Deep Medicine, Eric Topol, a cardiologist and director of the Scripps Research Translational Institute in La Jolla defines hype and threat about AI in healthcare. The book also illustrates a future in which AI helps to re-establish empathy and trust between doctors and patients. The book further provides a broad survey of how AI is applied in medicine.

Just like AI is being applied in radiology to read X-ray films, in pathology to detect tumour cells and in dermatology to diagnose skin lesions, Eric describes a similar approach in ophthalmology where algorithms can detect diabetic retinopathy, and in cardiology, where it is to reveal cardiac arrhythmias such as atrial fibrillation by tracking data from wrist-based sensors.

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