This article was prompted after this article, where we called for a rethink of the healthcare system. We like to tackle the small problems
Anecdote
I want to start this one with an anecdote. My grandpa went to a GP some years ago when he was having a routine check-up. As part of that routine check-up, they took his blood pressure. The GP had an automatic desktop blood pressure machine and he put it on my grandpa and inflated it, but the machine declared an error and they couldn’t work out what the issue was. They then decided to do a manual test, which one of the nurses conducted. When they did the blood pressure test, they said that his blood pressure was high but normal – let’s say 140 / 100 which was not unexpected for someone of his age so he went home and was told there was nothing to worry about.
But a couple of days later, he had chest pains and was admitted to the hospital. They then took his blood pressure and it was extremely high – let’s say 190 / 140. But he had just been to the GP and they told him it was fine!
Later when the dust settled, he went back and told the GP what happened. After some investigation, they decided that the blood pressure was too high for the desktop BP unit, so it couldn’t read and threw an error. And then the nurse, when she was taking the blood pressure took the low blood pressure reading (the diastolic instead of the systolic), as the high reading and didn’t actually close off the veins properly at all.
Can We Do Better? Or Should We Just Live With It?
We all make mistakes, it was a busy waiting room. It’s going to happen. But as a medical device engineer, this reminded me of a lot of discussions that I was having with clinicians at the time. I knew as medical device engineers we created highly precise devices which could give readings on very precise measurements on the patients, and I knew this because I regularly tested and calibrated them.
But one of the first things we learn as an engineer is the difference between precision and accuracy. And I believe this is a failure when we talk about gold standards in the medical device environment. We talk about gold standards of getting the most precise measurement of a patient at a particular set point in time. But my argument that I had with a number of nurses and clinicians was,
‘Is that really precise measurement and accurate estimation of the patient’s health and well-being?’
The issue with a precise measurement is that if you only take it once or twice, like a yearly check-up or when they present to a hospital. Is that really a precise measurement of the patient’s well-being? And my argument is no and it’s not because I didn’t trust the machines – but because there are so many different factors that can affect highly precise measurements. For instance:
– White Coat Syndrome (shown to impact heart rate and blood pressure)
– Fluctuations in the body’s reaction to disease
– Poor technique
– Different techniques between clinicians
– Environmental issues (such as too much light when taking SpO2 readings)
– Patient-specific issues (such as wearing nail polish when taking SpO2 reading)
We place far too much reliance on these precise measurements, which are never as precise as we are led to believe. Also,
one-off measurements don’t give us any context about the patient or their specific requirements.
There are numerous instances where a patient presents, their measurements are taken and deemed to be outside of the normal ranges. But that is because they are an outlier rather than there being anything wrong with them. As a side note, we are also finding male-orientated data sets as the dataset wasn’t properly diversified.
Is there a role for wearables in healthcare?
So it is our belief at Goldilocks, that the new gold standard for medical devices should focus far more on holistic measurements rather than single precise measurements.
We should be looking for accurate measurements and getting an understanding of the patient’s context, rather than over-relying on a single highly precise measurement.
Wearables, such as the FitBit and Apple watch often get mocked for their lack of precision. They may not be as precise, but can they provide a much more accurate indication of the patient’s well-being?
Hear me out here – the readings from wearables allow us to look for trends, it provides context and trending data. Continuous measurement also us to remove factors like clinician technique, whitecoat syndrome, and numerous other patient-specific and environmental issues that might impact single-point measurements. Continuous measurements allow us to build trending and indicative data and provide a much more realistic understanding of the patient’s health and well-being and so it’s the clinician and patient’s downfall to disregard wearable data too quickly.
Perhaps there is a role for wearables in healthcare after all…
Is anyone doing this?
At Goldilocks, we believe that continuous measurement should be the gold standard for any symptom or diagnosis. Continuous monitoring is far more beneficial to the clinician in providing recommendations and treatments which are required. It is not something that’s taught in medical school, the difference between accuracy and precision. It’s something that we teach engineers, but it is really something that we probably should teach doctors because it has a massive impact on how they process the data they receive and the confidence with which they can make recommendations.
continuous measurement once implemented can lead to many novel and unexpected discoveries.
For us, the continuous measurement of skin and core temperature has allowed us to track things like circadian rhythms, making our sleep measurements more accurate. Being able to detect the irritation and comfort levels of the baby. Detecting the baby’s feeding and fluid intake. Determining how much the parent is picking them up and holding them. So simple continuous measurements allow us to offer so much more insight into the baby’s behavior and thus helps us provide more holistic and valuable insights to carers and loved ones. And we haven’t even touched on early detection and prevention of disease.
We Need To Act Now!
The future of healthcare is data-driven and requires doctors to have a better understanding of data and the statistical significance of data points. The continuous monitoring capabilities we have now, call for a rethink on what we call ‘The Gold Standard’. Medical device engineers need to be honest in their design of medical devices and need to take habits of the real-world environment into account when talking about the accuracy of their devices. And of course, continuous monitoring is something that could have helped my grandpa and many other patients.
