Two 2018 trends underlie the drive toward upgrading the patient experience. At GCR in 2017, we’ve seen that:

1. Patients increasing move towards managing their own health decisions, and take more responsibility for their health decisions rather than solely relying on the advice of their primary doctor.

2. Clinics & hospitals are struggling to meet the increasing expectations for an online patient experience.

Attracting and maintaining a quality, high-level of patient flow means finding ways to attract those patients who increasing resolve their medical decisions on their own, quickly and conveniently. In that context, implementing the right patient tools and processes is more important than ever before.

Technological improvements are the future of the new patient experience, but technology on its own is rarely the right answer in healthcare. Clinics will need to pick the right mix of technologies for their own needs and implement them effectively.

In this article, I’ll review the broad new patient trends and the technologies that will shape their way we communicate with patients in the years to come.

2018 trends in patient communication

More messaging

2017 saw a continuation in the rise of messaging applications across the internet. Facebook, Twitter, and WhatsApp all announced plans for their services to become explicit customer service channels for businesses. (this will then apply to patient support channels for clinics as well).

Whether you choose to use those particular tools or not in your medical practice, patients will increasingly expect messaging-style support options from the clinics and hospitals they decide to contact and have treatment with.

While personally visiting the clinic or using the telephone continues to hold globally as the no.1 choice of choosing and booking a treatment appointment, email communication is in fast decline and 2018 will be the year that messaging starts to integrate and become seamlessly interwoven using 3rd party software with all of the other communication channels businesses are using to talk to potential and current patients.

CRMs increased their capabilities

Help desk tools, chat systems, and knowledge base searches have so far been isolated sets of data. By combining that data through patient relationship management tools, clinics will be able to deliver more personalized patient support experiences.

Those CRM capabilities may be built into existing clinic software systems, or they may come through deeper integrations. For example, a well-integrated patient support system could be aware of:

– The patient’s current stage of treatment

– Their past medical history in the clinic and previously with other clinics

– Prior conversations with the doctors and medical team.

– Their test results and diagnostic results

Patient support tools will use that context to make informed assumptions about what the patient needs next to see and how to prioritize the information for them, rather than relying on the patient to provide all that contextual information each time.

Personalization in clinics will be delivered in the form of customized help information or treatment plans, or even through AI agents in chats.

Increasing use of video in patients communication and support

Globally, online video consumption increases year over year, driven by better internet access and the adoption of smartphones. Wistia reported in 2016 that “People spent on average 2.6x more time on pages with video than without.”

People also engage more with video than with text, and patient communication video is an efficient way to explain complex or confusing issues to patients under stress.

New tools enabling patient support teams to quickly create and share videos will mean a big jump in video usage in patient communication. To get started, consider these two options:

– Soapbox from Wistia

– Loom

Increased digital collection of patient treatment outcomes

GCR along with a few other healthcare organizations has moved from simply collecting patient reviews (subjective) to collecting patient outcomes (objective).
Previously doctors and teams found it difficult to follow-up with previous patients on a continual basis, track the outcome of treatment and then implement changes into their treatments to improve the outcomes for future patients.

Now that digital advancements allow a patient to report outcomes in the clinic and on their own device, we’ve seen clinics tracking and submitting this data to the GCR. This will mean that patients in mid-2018 will move from choosing clinics on factual results rather than reviews or simple referral.

If you’d like to pilot the collection of treatment outcomes in your clinic this year, just contact us to test our software free of charge.

Near-Future Technological changes in patient support

Looking forward to 2020 and beyond, I see artificial intelligence underlying almost all the technological advances in patient support and communication. As a field of study, AI is incredibly broad. I am not trying to cover everything here, here’s how I see AI be applied to our patients over the next few years…

Natural language processing and speech recognition

Natural language processing (NLP) is how our machines are able to “understand” written human languages. As humans, we tend to speak in ambiguous, imprecise ways, and the field of NLP enables computers to turn that language into something they can process and act upon.

That means a patient can ask for an appointment “next Tuesday” and have a computer translate that into a nicely formatted YYYY-MM-DD that can be added to the clinic calendar.

A common challenge of patient communication tools is that the information the patient needs is probably not written down anywhere and if it is they aren’t able to find or access it. Improvements in NLP and speech recognition will make it simpler for a computer to correctly interpret what the patient needs.

With Amazon, Apple and Google all enabling voice commands and search in our phones, devices, and cars, it’s only a short step until you start seeing it used in the worlds top clinics.

Machine learning

Machine learning is a term sometimes used interchangeably with AI, but in truth, it is just one application of AI technology. The idea is that we should be able to give machines access to sources of data and have them “learn” without being explicitly programmed.

Patient support is a natural application for AI, because it tends to generate huge amounts of data with so many patients asking questions, and medical teams answering those questions.

Machine learning will allow computers to read all of that information (using technology like natural language processing and sentiment analysis), and train themselves on how to answer patient questions.

In 2017 we began to see clinics exploring machine learning applications. For most clinics, it is still too early for machines to realistically handle most of their patient support and treatment planning, but every team would do well to identify which parts of their patient support workload should be automated first.

Read more here:
https://www.healthcatalyst.com/clinical-applications-of-machine-learning-in-healthcare
https://www.techemergence.com/machine-learning-in-pharma-medicine/
https://www.techemergence.com/machine-learning-healthcare-applications/

Chatbots, virtual agents, and human support

Will robots replace our doctors? Not yet, but clinics will continue applying AI technologies like NLP, machine learning, and sentiment analysis to patient support and treatment. The reality of a completely independent, highly competent and flexible AI-powered, robot doctors is a long way off yet.

I personally see the greatest value in AI supplementing, not replacing doctors and medical teams. AI elevates clinics to increase their impact, and improve their ability to treat and change the lives of patients.

Once AI can understand a patients needs – it can then allocate most appropriate treatment plan, apply global knowledge, and ultimately lead to increased treatment outcomes, the fastest possible solution and best experience for the patient – and reduce clinical work by humans.

But identifying which work could be automated away and the places a real medical professional can make the biggest impact will be critical as AI tools are rolled out over the next few years.

Preparing your clinic for the future of patient support

The future of improving patient support is better technology, thoughtfully applied and integrated into clinics to give the patient faster access to better information and treatment with less effort.

In 2018, we will see AI and related technology applied more widely, but for most use cases, fully automated support is still a very long way off. Using AI to make your patient support team faster, smarter, and more effective is the best way forward this year.

To prepare your clinical team for the future, begin by building a model of your patient support experience, and identify places where technology or processes could be inserted to save time and effort.

That way, as the technology improves and becomes more widely available, you can make informed decisions about how and where to integrate it into your patient experience.