With margin-pressure, patient attrition, and dwindling census numbers all top-of-mind, leading CFOs are turning to the retail sector for an engagement tool: Artificial Intelligence (AI) chatbots.

In today’s consumer-centric healthcare environment, patients have a variety of ways to compare and contrast providers. From word-of-mouth to online reviews, today’s patients are tech-savvy, and less likely to frequent a health system that is unable to provide a seamless, easy, healthcare experience.

The truth is, patients are shopping for care, and few health systems are prepared to meet the demands of the new environment.

Though precision medicine has improved with new therapies and greater access to clinical trials, the customer service experience has lagged behind. So how do health systems get ahead of the trend? By managing patient expectations, and delivering personalized communication across the care continuum. This means evaluating every patient touchpoint to identify communication gaps where patients are most likely to get frustrated, and turn to a competitor for care.

With margin-pressure, patient attrition, and dwindling census numbers all top-of-mind, leading CFOs are turning to the retail sector for an engagement tool: Artificial Intelligence (AI) chatbots.

As the retail sector well knows, customer experience is at the heart of building brand loyalty, yet providing support at scale can be costly. That’s why AI chatbots deliver a critical service, by reaching consumers where they are, on their mobile phones without the need to download an app. Better yet, the average consumer has previously interacted with AI chatbots in some capacity, leading to higher adoption rates. Airlines text flight delays, and banks use opt-in text messages for credit card fraud alerts. The business sector has enlisted chatbots to rapidly service consumers.

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Today, the healthcare industry has followed suit, with a few major improvements.  With the help of machine learning, we’ve developed AI chatbot software that takes a page from the retail playbook, with a conversational approach. Not only does the patient receive relevant care information, they are able to respond and ask questions. The AI chatbot experience improves upon the limited information delivered by business brands, and translates Chatbot technology into a powerful communication tool for care delivery outside of the clinical setting.

While healthcare facilities pour millions of dollars into patient portals and hospital branded apps, we found that the common denominator between 18 year-old patient and the 80 year-old are that they both use text messaging. Administrators overestimate how long a patient is willing to spend trying to download an app. Within the four or five minutes it takes to log-in or recover a password, health systems employing AI chatbots have completed a robust conversation with patients via text, and delivered critical information in less time.

The truth is, patients are shopping for care, and few health systems are prepared to meet the demands of the new environment.

However, to truly operationalize trust and improve patient satisfaction takes a combination of the right work-force combined with next-generation technology. In the hands of a skilled Navigator, AI chatbots deliver customizable conversations, strengthening communication between patients and care teams. This is especially true for redundant information, like directions to the healthcare facility, and pre-op care plans. Automating redundant processes not only removes the guess-work for patients, but also frees care teams to work top-of-license.

Kyle Cooksey

With AI chatbots, Navigators are also able to connect with patients in real-time in the emergency department. During care episodes when patients are increasingly vulnerable and disoriented, chatbots provide the added support to improve a notoriously stressful experience. Reassuring the patient from check-in to discharge is a powerful tool, and with a Navigator in control, care teams can proactively intervene if a patient needs face-to-face guidance. AI chatbots in this respect reduce Left Without Being Seen (LWBS), and other metrics that greatly affect reimbursement. Even after discharge, a chatbot conversation can lead to a follow-up call from a Navigator to ensure care plan adherence, and schedule referral appointments.

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For outpatient care the technology creates a two-way street where patients can communicate with their clinical teams, and alert their providers to acute care episodes that may have otherwise gone unnoticed. Via text-messaging, an elderly patient can text their provider that they have had a fall or are experiencing back-pain without having to make a phone call or an appointment. Breaking down barriers to care and closing care gaps with AI chatbot technology leads to more engaged patients, and better health outcomes.

Since all chatbot conversations are logged, the qualitative and quantitative data is a treasure trove of actionable intelligence to better understand a health system’s patient population. Machine learning allows AI to rapidly scan a data set and augment the efforts of clinical teams to better nurture the populations they serve.

With the shift from fee-for-service to value-based care, coupled with the rise of consumer-centric patients, developing a strategy for patient engagement is an imperative. AI chatbots put the power in the hands of clinical teams to address common care gaps that if not closed, can lead to a stream of patients falling through the cracks.

 

Kyle Cooksey is president is president of CareThrough, a provider of managed care services.

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