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Could AI And Healthcare Chatbots Help Clinicians Communicate With Patients?

Posted on April 25, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

AI-driven chatbots are becoming increasingly popular for a number of reasons, including improving technology and a need to automate some routine processes. (I’d also argue that these models are emerging because millennials and Gen Z-ers have spent their lives immersed in online-based social environments, and are far less likely to be afraid of or uncomfortable with such things.)

Given the maturation of the technology, I’m not surprised to see a number of AI-driven chatbots for healthcare emerging.  Some of these merely capture symptoms, such as the diabetes, CHF and mental health monitoring options by Sense.ly.

But other AI-based chatbots attempt to go much further. One emerging company, X2ai, is rolling out a psychology-oriented chatbot offering mental health counseling, Another, UK-based startup Babylon Health, offers a text-only mobile apps which provides medical evaluations and screenings. The app is being pilot-tested with the National Health Service, where early reports say that it’s diagnosing and triaging patients successfully.

One area I haven’t seen explored, though, is using a chatbot to help doctors handle routine communications with patients. Such an app could not only triage patients, as with the NHS example, but also respond to routine email messages.

Scheduling and administration

The reality is that while doctors and nurses are used to screening patients via telephone, they’re afraid of being swamped by tons of electronic patient messages. Many feel that if they agree to respond to patient email messages via a patient portal, they’ll spend too much time doing so. With most already time-starved, it’s not surprising that they’re worried about this.

But a combination of AI and healthcare chatbot technology could reduce their time required to engage patients. In fact, the right solution could address a few medical practice workflow issues at one time.

First, it could triage and route patient concerns to doctors and advanced practice nurses, something that’s done now by unqualified clerks or extremely busy nurses. For example, the patient would be able to tell the chatbot why they wanted to schedule a visit, with the chatbot teasing out some nuances in their situation. Then, the chatbot could kick the information over to the patient’s provider, who could, with a few clicks, forward a request to schedule either an urgent or standard consult.

Perhaps just as important, the AI technology could sit atop messages sent between provider and patient. If the patient message asked a routine question – such as when their test results would be ready – the system could bounce back a templated message stating, for instance, that test results typically take five business days to post on the patient portal. It could also send templated responses to requests for medical records, questions about doctor availability or types of insurance accepted and so on.

Diagnosis and triage

Meanwhile, if the AI concludes that the patient has a health concern to address, it could send back a link to the chatbot, which would ask pertinent questions and send the responses to the treating clinician. At that point, if things look questionable, the doctor might choose to intervene with their own email message or phone call.

Of course, providers will probably be worried about relying on a chatbot for patient triage, especially the legal consequences if the bot misses something important. But over time, if health chatbot pilots like the UK example offer good results, they may eventually be ready to give this approach a shot.

Also, patients may be uncertain about working with a chatbot at first. But if physicians stress that they’re not trying put them off, but rather, to save time so they can take their time when patients need them, I think they’ll be satisfied.

I admit that under ideal circumstances, clinicians would have more time to communicate with patients directly. But the truth is, they simply don’t, and pressuring them to take phone calls or respond to every online message from patients won’t work.

Besides, as providers work to prepare for value-based care, they’ll need not only physician extenders, but physician extender-extenders like chatbots to engage patients and keep track of their needs. So let’s give them a shot.

Artificial Intelligence Can Improve Healthcare

Posted on July 20, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

In recent times, there has been a lot of discussion of artificial intelligence in public forums, some generated by thought leaders like Bill Gates and Stephen Hawking. Late last year Hawking actually argued that artificial intelligence “could spell the end of the human race.”

But most scientists and researchers don’t seem to be as worried as Gates and Hawking. They contend that while machines and software may do an increasingly better job of imitating human intelligence, there’s no foreseeable way in which they could become a self-conscious threat to humanity.

In fact, it seems far more likely that AI will work to serve human needs, including healthcare improvement. Here’s five examples of how AI could help bring us smarter medicine (courtesy of Fast Company):

  1. Diagnosing disease:

Want to improve diagnostic accuracy? Companies like Enlitic may help. Enlitic is studying massive numbers of medical images to help radiologists pick up small details like tiny fractures and tumors.

  1. Medication management

Here’s a twist on traditional med management strategies. The AiCure app is leveraging a smartphone webcam, in tandem with AI technology, to learn whether patients are adhering to their prescription regimen.

  1. Virtual clinicians

Though it may sound daring, a few healthcare leaders are considering giving no-humans-involved health advice a try. Some are turning to startup Sense.ly, which offers a virtual nurse, Molly. The Sense.ly interface uses machine learning to help care for chronically-ill patients between doctor’s visits.

  1. Drug creation:

AI may soon speed up the development of pharmaceutical drugs. Vendors in this field include Atomwise, whose technology leverages supercomputers to dig up therapies for database of molecular structures, and Berg Health, which studies data on why some people survive diseases.

  1. Precision medicine:

Working as part of a broader effort seeking targeted diagnoses and treatments for individuals, startup Deep Genomics is wrangling huge data sets of genetic information in an effort to find mutations and linkages to disease.

In addition to all of these clinically-oriented efforts, which seem quite promising in and of themselves, it seems clear that there are endless ways in which computing firepower, big data and AI could come together to help healthcare business operations.

Just to name the first applications that popped into my head, consider the impact AI could have on patient scheduling, particularly in high-volume hostile environments. What about using such technology to do a better job of predicting what approaches work best for collecting patient balances, and even to execute those efforts is sophisticated way?

And of course, there are countless other ways in which AI could help providers leverage clinical data in real time. Sure, EMR vendors are already rolling out technology attempting to help hospitals target emergent conditions (such as sepsis), but what if AI logic could go beyond condition-specific modules to proactively predicting a much broader range of problems?

The truth is, I don’t claim to have a specific expertise in AI, so my guesses on what applications makes sense are no better than any other observer’s. On the other hand, though, if anyone reading this has cool stories to tell about what they’re doing with AI technology I’d love to hear them.