Where do you stand on the impact to-date of self-diagnostics technology on healthcare and patient engagement?
Some take the position that “knowledge is power,” democratising access to information and empowering individuals to take greater charge of their health.
Others subscribe to the view that “a little knowledge is a dangerous thing” with patients poorly placed to fully understand the possible diagnosis they are being presented with.
Either way, self-diagnostics technology is a rapidly growing field that we must all work to develop along the lines of improving health outcomes, reducing healthcare costs and making healthcare more accessible to people around the world.
Advancing capabilities
In their most primitive form commoditised methods for self-diagnosis can be traced all the way back to paper books, a papyrus scroll or even cave paintings.
These tools enable people to readily self-diagnose, but they are crude in the extreme.
More recently we have all became familiar with the concept of “Doctor Google”.
Entering our symptoms into our search engine of choice and seeing what it churns out.
Typically, one would look up a condition of interest or perhaps flick through a few conditions and select those that seem most relevant.
One would then run through a series of “yes” and “no” questions about relevant symptoms.
The technology has made the process much more accessible, and it is undoubtedly powerful.
But it is still very basic in terms of its sophistication.
There is no collaboration with trained medical professionals, with no attempt to evaluate the accuracy of the self-diagnosis obtained to inform future suggestions.
Now, we’ve entered the age of generative AI aiming to help individuals to make sense of their symptoms.
ChatGPT launched on 30 November 2022.
By January 2023, it had become the fastest-growing consumer software application in history with over 100 million users.
Google, Microsoft, Baidu and Meta all launched competing products: Bard, Bing Chat, Ernie and LLaMA respectively.
These large language model trained generative AI chatbots had become almost immediately commoditised.
That is to say, the latest technology has become part of everyday life.
And, of course, users are now able to use these systems for self-diagnosis for health-related purposes.
They can ask free-form questions and be much more nuanced and probing and, dare I say, more human in interaction.
However, concerns are being raised as the models used are not specifically trained for health care; they are, by definition, general models trained on general data.
This general data is wide ranging, and some may be of questionable scientific merit either intentionally or unintentionally.
Increased specialisation
Just as in standard medical training there is a place for general practice and a place for specialisation.
In a recent study from May 2023 published in JMIR Human Factors, the findings were that ChatGPT had satisfactory explanatory power and positive risk-reward, and it was generally a positive experience for users.
The study concluded that rather than discouraging the use of these tools that they should be improved by adapting them for healthcare applications.
It seems to me that the next step in technology for self-diagnosis is large language model trained generative AI chatbots trained on sound healthcare data.
There are significant rewards on offer – both financial and societal – for those companies who can meet the associated challenges.
That could be in developing AI that provide more accurate diagnoses.
It could be in building personalised self-diagnostics tools that take an individual’s unique healthy history and factors into account.
Or in integrating self-diagnostics tools with electronic records in such a way that medical professionals are alerted and available to interpret results at the right time.
Reddie & Grose has a wide breadth of experience in protecting innovation relating to self-diagnostics, medical devices and healthcare related inventions.
We stand ready to put the intellectual property strategies in place that are required to incentivise continued innovation in this field.
