Latest / The SOM Podcast / SOM MINI CPD: Modernizing Spirometry in OH with Z Scores with Rebecca Burton

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SOM MINI CPD: Modernizing Spirometry in OH with Z Scores with Rebecca Burton · The SOM Podcast

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  Speaker 1: This podcast is sponsored by Orchid Live. Hello and welcome
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  Speaker 1: to the SOM podcast. I'm Steve Randall and this episode
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  Speaker 1: is one of a monthly series to help you as
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  Speaker 1: an occupational health professional with your CPD as we invite
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  Speaker 1: specialists to share an overview of some of the topics
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  Speaker 1: you've told us you'd like to find out more about.
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  Speaker 2: I'm Rebecca Burton. I'm a qualified occupational health advisor that
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  Speaker 2: I've been doing for over 11 years and also a
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  Speaker 2: clinical trainer as well. I work still as an occupational
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  Speaker 2: health advisor, but I also do freelance training for Dietec,
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  Speaker 2: doing their spirometry training. Okay.
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  Speaker 1: Well, welcome, Rebecca, to the SOM podcast. And we're talking
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  Speaker 1: about spirometry and particularly ZED. I'm going to say ZED
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  Speaker 1: scores because we're British. Perhaps you can give us sort
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  Speaker 1: of an overview of what you do.
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  Speaker 2: So spirometry in occupational health, we use it as a
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  Speaker 2: screening tool. And for us, it measures the capacity of
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  Speaker 2: the lung and of how much of that they can
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  Speaker 2: blow out in the first second. That's what the spirometer
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  Speaker 2: measures and it gives us a predicted value set that
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  Speaker 2: has been taken from a huge global data set built
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  Speaker 2: on healthy people. It's worldwide and it matches what they
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  Speaker 2: are predicted to blow, match to their age, their height
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  Speaker 2: and their sex at birth. So Z scores are a
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  Speaker 2: way of looking at what we would say is the
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  Speaker 2: lower limit of normal, of what somebody should be able
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  Speaker 2: to blow out based on that predicted set that I
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  Speaker 2: just talked about, their age, their height and their sex
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  Speaker 2: at birth. But for a long, long time and still
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  Speaker 2: in occupational health, when we look at those lovely data
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  Speaker 2: set that's been based on lots and lots of information,
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  Speaker 2: we then apply a fixed cutoff of some say 70%,
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  Speaker 2: some say 75%. This is how it's always been done.
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  Speaker 2: So we basically say that a 25-year-old five-foot-one female and
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  Speaker 2: a 65-year-old six-foot male, even though we know this is
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  Speaker 2: what you're going to be predicted to blow, we're then
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  Speaker 2: going to say, well, we're going to look at that
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  Speaker 2: result and say, well, you've got to reach 70% of
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  Speaker 2: the ratio of what you can blow out in the
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  Speaker 2: first second compared to, you know, divided by your whole capacity.
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  Speaker 2: When you think about it, if we apply that, it
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  Speaker 2: doesn't factor for things like the fact that lung function
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  Speaker 2: naturally declines with age. And also when you look at
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  Speaker 2: a fixed ratio, it doesn't factor in things like if
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  Speaker 2: someone's preterm birth, because they're going to always have a
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  Speaker 2: lower function. A 25-year-old female, if we apply a 70% cutoff,
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  Speaker 2: they're probably going to be over that because it's not
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  Speaker 2: got a scientific basis. There's a thing called GOLD guidelines,
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  Speaker 2: which they use to diagnose airway obstruction. And they use
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  Speaker 2: a 70% cutoff. And before that, the American Thoracic Society
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  Speaker 2: used a 75% cutoff. Generally, most people do use the 70%,
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  Speaker 2: but it's just flawed because you're not comparing apples with apples.
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  Speaker 2: You're literally saying everybody, regardless of age, height, sex at birth,
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  Speaker 2: should be able to blow this amount.
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  Speaker 1: A lot of things in life, and particularly where we
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  Speaker 1: talk about health and medicine, a lot of things were
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  Speaker 1: established many, many years ago. Much has been updated. Some
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  Speaker 1: things have been slower to be updated than others, and
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  Speaker 1: perhaps this is one of those, where Z-scores are coming
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  Speaker 1: in to update the way that things are measured.
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  Speaker 2: Medicine always defines normal ranges. They use what is called
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  Speaker 2: a bell curve and standard deviation, which is all a
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  Speaker 2: bit complex, but... and a lot of people seem to
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  Speaker 2: like this analogy, when babies are born, let's say every
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  Speaker 2: male baby who was born one month ago, we're going
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  Speaker 2: to weigh them today. If we took 100 of those babies,
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  Speaker 2: most of them would fit around an average, which would
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  Speaker 2: be classed as around, they call it the 50th percentile,
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  Speaker 2: so 50%. Most of them would sit around the average.
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  Speaker 2: Some would be slightly bigger than that. Some would be
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  Speaker 2: slightly smaller than that. Still completely normal. Some would be
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  Speaker 2: even a little bit bigger than that and some would
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  Speaker 2: be even a little bit smaller than that there's normal
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  Speaker 2: anatomical differences that with normal variations and that's absolutely fine
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  Speaker 2: but in medicine we've got to have a cut off
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  Speaker 2: the lower limit of normal now where are we saying
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  Speaker 2: well actually we need to maybe have a look at
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  Speaker 2: these people and see is there something going on the
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  Speaker 2: 50 50 percent mark is what we call the average person.
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  Speaker 2: And that would be plotted as zero. If zero is average,
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  Speaker 2: the 25th percentile is what? Minus one deviation from that
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  Speaker 2: normal standard deviation. And the 75th percentile or 75% would
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  Speaker 2: be plus one standard deviation from the average of normal.
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  Speaker 2: That's still fine. But in medicine, it was decided a
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  Speaker 2: long time ago that they would use the fifth percentile
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  Speaker 2: so five percent as this cut off for what is
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  Speaker 2: the lower limit of normal that happens to sit at
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  Speaker 2: minus 1.64 deviations from that zero that average backwards so
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  Speaker 2: basically that's what forms a z score anything below minus 1.64
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  Speaker 2: is below the lower limit of normal that's all the
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  Speaker 2: z score is it sounds really really difficult but it's
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  Speaker 2: not because what you're doing now is you're not saying
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  Speaker 2: Every single person has a cutoff of 70%. What you're
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  Speaker 2: saying is, okay, well, we've got this lovely data set
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  Speaker 2: that's all based on statistics. So now we're actually going
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  Speaker 2: to use mathematical statistics for the actual person and say, right,
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  Speaker 2: we're going to apply this to, you know, this male
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  Speaker 2: who is, you know, 65 and six foot one. And
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  Speaker 2: that's what the Z score does, as opposed to just
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  Speaker 2: applying the fixed cutoff. The problem is when you're using
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  Speaker 2: a fixed cutoff percentage, what's happening is that older people
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  Speaker 2: are being overdiagnosed. So they're being referred when the software
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  Speaker 2: will calculate a percentage and say, well, this person hasn't
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  Speaker 2: hit this 70% or 75, whatever it is that we
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  Speaker 2: look at. And then that person will be referred for
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  Speaker 2: further test. And actually, it's perfectly normal because if you
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  Speaker 2: look at it on their statistical analysis or their Z score,
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  Speaker 2: they'll be within a normal range. But more, if not
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  Speaker 2: so more importantly, is younger people. So say you have
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  Speaker 2: a 25-year-old female who is 5'2, say she works in
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  Speaker 2: a bakery, she's working with flowers, she's got lots of exposures,
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  Speaker 2: she's got symptoms. I mean, we should refer on that
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  Speaker 2: basis anyway. But if we've applied a fixed cut-off percentage
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  Speaker 2: based on, well, she should be able to score 70%,
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  Speaker 2: because she's young and fit, the chances are she would
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  Speaker 2: score over 70% and that would be reported on the
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  Speaker 2: spirometry software as normal. Whereas actually, when you then looked
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  Speaker 2: at her actual Z scores, which would be compared to
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  Speaker 2: females who were, I can't remember, 5'2 and 25 years old,
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  Speaker 2: that would actually show that she might be on the
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  Speaker 2: lower limit of normal.
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  Speaker 1: Hopefully, the outcome of this is that people who don't
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  Speaker 1: need further investigation, but the percentage model means that they
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  Speaker 1: get referred for further investigation, those cases should be fewer.
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  Speaker 1: There should be less false positives.
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  Speaker 2: Yes.
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  Speaker 1: And the Z scores will also mean that those people
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  Speaker 1: who may have just been, no problem there, you're perfectly normal.
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  Speaker 1: If there is an issue, that should be picked up easier.
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  Speaker 2: Absolutely. A lot of the software does have Z-scores on there,
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  Speaker 2: but we tend to still look at the percentage predicted
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  Speaker 2: because it wasn't really adopted. But when you look at
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  Speaker 2: the standards, the American Thoracic Society and European Respiratory Society,
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  Speaker 2: they do the guidelines for interpretation of spirometry. And actually,
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  Speaker 2: since 2022... those standards have formally replaced using a percentage
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  Speaker 2: predicted with Z-scores. ARTP also endorsed that in 2025. They're
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  Speaker 2: the kind of two standards within occupational health, particularly. There
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  Speaker 2: is going to be a changeover period, but what people
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  Speaker 2: need to be aware of is, number one, just because
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  Speaker 2: if the software says normal, because the software will give
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  Speaker 2: you an answer, you know, it will predict most software
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  Speaker 2: does and will say normal spirometry. But just be aware
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  Speaker 2: if this is you know, a younger person, and especially
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  Speaker 2: if they're exposed to things, it might actually not be normal.
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  Speaker 2: And conversely, at the other end, if you've got, I mean,
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  Speaker 2: we are getting lots more older people now coming through,
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  Speaker 2: you know, through occupational health, just be aware that just
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  Speaker 2: because they're under 70%, the software is saying, actually, this
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  Speaker 2: person has, you know, a mild obstruction. When you look
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  Speaker 2: at the Z scores, actually, they're perfectly normal and there
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  Speaker 2: isn't But you've also always, always got to, you know,
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  Speaker 2: match that with their occupational history, their current exposures, if
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  Speaker 2: they've got any symptoms, things like that. So, I mean,
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  Speaker 2: a normal spirometry should not negate referral if they have symptoms,
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  Speaker 2: for instance. So, you know, until everybody's really familiar with
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  Speaker 2: the Z scores, then you just need to be very,
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  Speaker 2: very aware that, number one, you know, if you're looking
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  Speaker 2: at a normal result, if they're younger or older, just
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  Speaker 2: be careful. And also... If you've got people who are
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  Speaker 2: new to it, that they might be just looking at
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  Speaker 2: that as well.
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  Speaker 1: What's your feeling on where adoption of Z scores are
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  Speaker 1: within OH at the moment?
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  Speaker 2: At the beginning.
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  Speaker 1: Really?
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  Speaker 2: Right at the beginning, 100%. Yeah, 100%. It is okay,
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  Speaker 2: but it's not the guidelines now. And you can see
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  Speaker 2: why it's not the guidelines now. You know, we've got
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  Speaker 2: to be very careful at the moment. The health and
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  Speaker 2: safety executive, as you probably know, have got a massive
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  Speaker 2: push on respirable silica.
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  Speaker 1: Yeah, something we've covered on this podcast.
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  Speaker 2: Exactly. And that is really, obviously within spirometry, that's really
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  Speaker 2: important that we're making sure that, you know, you might
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  Speaker 2: have young workers who have been working with this stuff
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  Speaker 2: for quite a long time who might have been exposed.
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  Speaker 2: You're doing a spirometry and you go, no, it's right.
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  Speaker 2: They blew above 70%. But actually... that's just that fixed cut-off.
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  Speaker 2: What you're not doing is comparing that to other people
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  Speaker 2: of their age, height and sex at birth because potentially,
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  Speaker 2: you know, you might see a difference there. And also,
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  Speaker 2: we've got to remember it's not just a one-off. You
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  Speaker 2: might have a younger person who blows normal, normal, normal, normal,
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  Speaker 2: but actually every year the drop is bigger than what
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  Speaker 2: you would expect for the normal expected age-related decline. So,
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  Speaker 2: the spirometry might still be saying normal because they can
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  Speaker 2: blow above that percentage. And even with the Z scores,
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  Speaker 2: they might still be able to be normal, but you've
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  Speaker 2: got to look at that longitudinal change. It's not just
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  Speaker 2: a one-off. It's not as complicated as it sounds, but
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  Speaker 2: it is just a change. When I do explain it
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  Speaker 2: and we've got all the charts and we actually do
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  Speaker 2: some practical work on it, most people sort of go, oh, okay, yeah,
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  Speaker 2: it's not that difficult. Oh, I get it now.
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  Speaker 1: Well, I'm sure that our listeners will go off and
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  Speaker 1: do some more research on this now because they're all
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  Speaker 1: focused on the best outcomes for the people they're working
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  Speaker 1: with and having the best tools in their toolkit and
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  Speaker 1: knowing all the things they need to know. That's why
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  Speaker 1: we do these mini CPD episodes. But how can people
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  Speaker 1: find out more about this topic?
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  Speaker 2: I would have a look at the ATS ERS guidelines.
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  Speaker 2: especially the updates that they did it was originally written
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  Speaker 2: in 2005 there was an update 2019 and.
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  Speaker 1: 2022 so rebecca a really fascinating conversation and i'm sure
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  Speaker 1: people will find out lots more about this and.
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  Speaker 2: Thanks so much for highlighting it thank.
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  Speaker 1: You This podcast is sponsored by Orchid Live. Orchid Live
• 12:36
  Speaker 1: is a specialist occupational health software used by a number
• 12:40
  Speaker 1: of SOM members to run every aspect of their occupational
• 12:43
  Speaker 1: health operations. They hold healthcare records for over 1 million
• 12:47
  Speaker 1: UK workers and work with both in-house OH teams and
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  Speaker 1: OH providers. You can find out more at orchidlive.com.