As we enter a new decade, Haidar Samiei, consultant in emergency medicine and clinical director at EMIS Health, takes us back to New Year’s Eve 1999 to reflect on how technology in healthcare has evolved.
Who remembers New Year’s Eve 1999?
For most it was a night of partying, for others a period of reflection, and for a few it was a time of uncertainty. We weren’t sure what the new millennium would bring, with crazy stories circulating that the world was going to end. Even if the apocalypse didn’t happen at midnight, the Millennium Bug might strike and we wouldn’t be able to turn on a computer.
As a junior doctor, I was working in A&E that night. I will have been an SHO 1 (FY2 in current terminology). It’s actually difficult to explain the intricate circumstances/interactions that show just how information poor life as a junior doctor was back then.
Not only was Google in its infancy, but the thought of using the internet to inform a decision on how to treat a patient was unthinkable.
We didn’t have an intranet brimming with up to date content either. Any specialist pathway or treatment regime had to be designed, photocopied, laminated, distributed and lord forbid should a pathway change, the whole process restarted.
Mobiles were not allowed in hospitals because, I don’t actually remember why. Wi-Fi wasn’t around then, so it can’t have been interference, but there was some way in which mobiles would almost certainly cause hospitals to blow up. I remember that, and the big posters everywhere.
When it comes to getting expert advice, we had the pager system. Our consultants left at 5pm, and our registrars at 10pm. After that, there was no one to ask for advice other than two fellow junior doctors. Specialists didn’t even carry phones. Imagine replacing your consultant, registrar, intranet, Google, mobile etc with a pager and some textbooks on a night shift, in a tertiary emergency department.
21st Century toys
When the iPhone was launched in 2007, I realised that the mobile phone, and more over mobile communication, would change the world, and that medicine couldn’t remain immune.
Using mobiles in a clinical setting came up against a lot of resistance, at first because of hospitals potentially blowing up, but after that just about any reason anyone could think of: battery life, infection control, wireless reception.
By 2010, myself and some colleagues created a phone app which helped clinicians give paediatric patients the right dose of the right drug at the right time, based on some basic information from the medical staff. At the time, doctors working out paediatric dosages needed to turn adult measures into a child’s manually, based on estimates of things like weight. Not ideal. That still happens in some places, and some places still solve the issue with laminates.
But more generally we have decision support tools now, and Advanced Nurse Practitioners (ANPs) in A&E do almost everything. That role could not have existed in 1999 because there wasn’t the technology to help them.
With clinical decision software we veer towards artificial intelligence (AI). We can streamline processes and use people with specialist skillsets. For example, back in 1999 when a patient came into A&E, every aspect of that person’s treatment was down to me as a junior doctor. I would be responsible for assessing them, taking bloods, making sure all the relevant tests were done and carrying them out.
Now, if for example a stroke patient comes in, thanks to good digital decision support, a nurse is on hand with specialist skills to assess and treat them, and the stroke consultant can come in at the very end.
In the hospital of the future, I see digital and AI technologies enabling on-demand interaction and seamless processes to improve patient care. For example, urine analysis is the second most common diagnostic test in the UK with 42 million tests annually, but a machine could just as easily do the job. A machine could do dipstick test and filter the results before they are checked by a human. It could also work with scans, blood tests, lab results and predictive scoring in, for example, cardiology.
True AI, where AI decides what it’s going to do, would have a place in the world of big data. Just below AI would be the high-level clinical decision support and warnings that would inform me that a patient is at risk of x or this antibiotic might be better for that patient.
As a junior doctor we rarely used scanners for diagnostics. For example, if I ordered a cancer scan it was because I could feel the tumour and needed to know its size and location so I could plan an operation. Now, we scan based on symptoms. Nurses or other staff members can do these diagnostics as the data is indisputable.
Our stethoscopes may become obsolete. (How will people know we are doctors?) Listening to the sound of blood as it passes through a narrow hole doesn’t provide as much information as an ultrasound scan.
As the cost of these tests decrease, we’re going to get more information from diagnostics.
There is scope for them to go much further in the future.
The pace of change in the last 20 years is unprecedented and there’s been a massive shift in thinking, and there’s no way of predicting what the next twenty years will bring.
But it’s quite something to look back at how far we’ve come!