In considering the daily tasks of a doctor, we could separate them into three different fire types.
A garden fire, for example, an inpatient that has rapid deterioration or a patient which need a scan yesterday but is on a long waiting list. The second type is the fire down the road, wider challenges that come with delivering outpatient care which is causing unacceptable delays or the issue of ensuring there is enough staff for minimal viable care. Finally, there are the fires that are far away – priorities which tend to be in the distance. It is in this category that we tend to see the most service improvement. The introduction of new technology, such as AI tends, to fall into this category as it comes in after patient care (and rightly so). Adam Kay’s ‘This Is Going To Hurt’ does a fabulous job of painting a real picture of what life as a doctor is really like. If you would like to know more about what it is like to work in the system, Henry Marsh’s ‘Do No Harm’ shows the many challenges that consultants face. Each of these books show the way that doctor is driven to provide patient care and the systems that need to be in place for them to do this.
Not Paying Heed to Sensationalism
The fact that patients need to have priority is, of course, very true. However, workforce limitations result in a delay in large-scale digital transformations. There are only a limited number of doctors who are communicating on this and it is not going to be possible to advance patient care if this continues. An intervenience from healthcare IT consultants may be the solution to speed up the process.
It is true that the popular press does tend to sensationalise AI somewhat, however, according to a recent survey, healthcare executives and organisations do have a more realistic view of the way it can help. One quote noted that operational areas which do not have the same potential to cause anxiety to clinicians, as well as patients, are coming up tops from clinical function when it comes to adopting systems. An approach like this one is wise and could play a role in limiting the disappointment phase which often happens when new technology is sensationalised too much.
As well as this, clinical responsibility can’t be assigned in full to what machine can do. It is neither possible from a technical viewpoint nor is it ethical from an implications viewpoint. Clinicians receive excellent training from their professional bodies and it is simply not possible to have a machine to do the same thing. There is no plan to allow an algorithm to control our clinical decisions. Certainly, human error does come into play and there is an expectation (not necessarily a right one) that machines should not do this. In the meantime, there is a need for clinical AI to learn and improve from humans while at the same time working to minimise patient risk. What we are talking about is an augmented intelligence rather than artificial intelligence.
We could describe this as someone who is looking for a job for the first time and needs experience to be employable but can’t get experience as nobody is taking on employees without it. How can the health systems adopt AI when doctors are already pushed to their limits since AI has to be trialled and needs the help of clinicians to teach the machines?
We could never expect that a doctor would give priority to AI instead of patient care, however, we do need to facilitate engagement and inclusion of ideas that come from a wide range of doctors rather than a limited number. A lot of doctors have clinics that are booked out with patients who are finding it difficult to understand their disease. It is hardly helpful nor realistic to expect that such an efficient care team would be replaced by an AI robot.
What is the Solution?
What about the idea to find ways to improve the clinic. Perhaps some of the appointments could be carried out through telemedicine? Which ones would be right for this? What are the digital tools that patients can make use of? How is the workforce equipped to use digital tools? Analytics are needed for insights on the experience both for the patient and the workforce.
Let’s make use of data and insights to put out the flames of some of those immediate fires. This is going to free up more time for the health workforce to use their time with their patients.