This episode reviews a nationwide survey of 2,509 Australian adults using two discrete choice experiments to quantify public preferences and the monetary value placed on genomic newborn screening (gNBS), and to identify preferred implementation features such as consent model and result delivery.
0:00Welcome to Base by Base, the paper cast that brings genomics to you wherever you are. Thanks for listening, and don't forget to follow and rate us in your podcast app. So imagine, for a moment, the very 1st 48 hours of a newborn's life.
0:12Oh man. The hospital room is quiet. You're just, you know, heavy with exhaustion. Right. And amidst all of that, there is a tiny, almost imperceptible heel prick. I mean, that single drop of blood has been a standard part of pediatric care for decades.
0:29Yes, absolutely. It's standard. We know it usually looks for, um, immediate biochemical red flags just to catch severe treatable conditions early. But what if we took that exact same drop of blood, and instead of just a basic biochemical snapshot, it unlocked a vast, comprehensive genomic map of that child's entire health future.
0:48Wow. I mean, that is a profound shift. It really is. How could this change how we parent? And more importantly, what really happens when parents are handed the power to foresee 100s of potential genetic conditions.
0:58Well, you're talking about moving from a system that asks a very immediate practical question like, uh, is there a chemical imbalance right now to one that asks an incredibly heavy long-term question? Yeah, like what's hidden in this DNA?
1:13Exactly. What is hidden in this child's DNA that might not show up for years or, you know, even decades? Which brings up the core of what we're exploring today. Are we actually ready for that kind of foresight?
1:25It's a huge debate. And today we celebrate the work of Ricardo Peters, Zornita Stark, Elise Cornitis, and their colleagues at the University of Melbourne and Australian Genomics, who have advanced our understanding of public preferences for genomic newborn screening.
1:39Yeah, and we should note that this research comes straight from the July 2025 issue of the American Journal of Human Genetics. Right. And to really grasp why this work is so groundbreaking. I mean, we have to look at the leap from standard newborn screening to genomic newborn screening.
1:54Or GMBS. Yeah, GMBS. Because traditional screening is a global public health success story. They use mass spectrometry to measure biochemical markers right after birth. But that only detects conditions with known biochemical markers, right?
2:07Exactly. But with GNBS, the jump is that you are sequencing the DNA itself. You're suddenly looking at 100s of genes associated with rare diseases simultaneously. Hundreds? I mean, that's just wild to think about, but identifying a pathogenic variant isn't a simple clinical diagnosis, is it?
2:24No, not at all. It raises huge ethical, practical, and social questions. Like, which genes do we even look at? What about secondary findings? Okay, let's unpack this. Because balancing the immense diagnostic power of GNBS with the potential for massive parental anxiety?
2:41And honestly, healthcare system overload is the central tension here. It really is. Because if you're a new parent holding this data, You might assume a genetic mutation is definitive sentence. Right, but biology doesn't work like that.
2:53Far from it. We have to consider, well, a concept known as reduced penetrate. Penetrance. Penetrance is basically a measure of how often a specific genetic trait actually shows up in a person who carried the gene for it.
3:04So it's essentially like having the blueprint for a leaky roof. Just because the blueprint says the roof has the, you know, a structural flaw that might cause a leak, it doesn't mean it's going to rain today or tomorrow or, well, ever.
3:17That is a perfect analogy. But as a parent holding that blueprint, you're constantly staring at the ceiling, waiting for the 1st drop of water. Exactly. And that visualizes the psychological burden perfectly.
3:29The dilemma becomes about boundaries. Do we only look for conditions that are guaranteed to happen and have a cure. Or do we look for everything, even conditions that might never develop or worth conditions we have absolutely no medical treatments for?
3:43Right. And to figure out how the public truly feels about this, the researchers had to move beyond simple surveys. Because if you just ask people, hey, do you want more health information about your baby?
3:53Almost everyone instinctively says yes. Oh, 100%. So the researchers used a methodology called a discrete choice experiment or a DCE. The DC. Yeah. It's not a simple yes or no survey. It forces respondents to make really difficult, agonizing trade-offs between different hypothetical scenarios.
4:13Oh, I see. It's like building a custom car online. If you wanted the premium sound system, you might have to sacrifice the leather seats or, you know, pay a massive premium. Yes, exactly. The researchers force participants to, quote unquote, buy their ideal screening program to see what they truly value when resources or even emotional bandwidth are limited.
4:33So they're in 2 separate, massive surveys, right? Involving, what, over 2500 representative members of the Australian public? Yeah, 2,509 people to be exact. What's fascinating here is how they used specialized software called den gene to generate these complex choice tasks.
4:49It's gene. Okay, so it wasn't just a basic questionnaire. No, it was highly sophisticated. And they didn't just average the answers out. They used a statistical tool, a panel error component, mixed logic model, and latent class analysis.
5:02Whoa, okay, that's a mouthful. Latent class analysis. Yeah, think of it like a sorting hat. It looks at 1000s of messy, seemingly contradictory human choices and groups them into hidden tribes of people who share the exact same underlying anxieties and priorities.
5:17Even if they don't consciously realize it themselves. Exactly. It ensures that the public, the actual taxpayers and end users are the ones guiding the health economics. That's incredible. So the 1st survey, the value DCE, had about 1500 people, right?
5:32Right. Right. 5504 people. And they had to assess the value of different GNBS features. Like the severity of the conditions, the certainty, treatment availability, and accuracy. Yeah, and out of pocket cost, which range from 0 all the way up to 2500 Australian dollars.
5:49But then there was the 2nd survey, the implementation DCE, with about a 1000 people. Exactly. Because if people say yes to the screening. You have to figure out how the server should actually be delivered.
5:59Who tells you, when, and how? Right, without breaking the healthcare system in the process. So let's look at the key findings. The headline numbers are pretty staggering. They really are. A massive 90% of respondents showed an interest in genomic newborn screening.
6:1590%. And the estimated uptake rate was over 87%, right? And this is a big, but cost was the absolute biggest driver in their decision making. Which makes sense. But beyond the cost, the tradeoffs are the real crux of this paper.
6:28Definitely. On one hand, people broadly want more diagnoses. They're willing to accept the inclusion of mild or moderate conditions to get them. But there's a massive disutility for certain things, right?
6:39Disutility being the economic term for a really strong dislike. Yes. There is huge disutility for including conditions with less effective treatments or no treatments at all. And conditions with reduced penetrants where they might never actually get sick.
6:52Exactly. Let's do a deep dive into the data here. If you look at the crossing value curves in the source. this part blew my mind. Right. So the economic value of a highly restrictive program one that only looks for profound, highly certain curable conditions scales up significantly.
7:09Yeah, as the diagnosis rate increases in that restrictive program, the value jumps from $4600 Australian dollars to $5700 per newborn. Because people see massive value in finding and fixing a severe problem.
7:23But then you have the non-restrictive program, the one that includes conditions with, you know, 50% chance of developing or no current treatments. And what happens to the value there? It just flatlines.
7:33It stays completely flat at around $5,400. It doesn't matter how many more diagnoses you add. Exactly. That flat line proves that the crushing weight of that uncertainty and anxiety literally cancels out the benefit of the extra testing.
7:47That is wild. The psychological toll just erases the diagnostic triumph entirely. Yeah, it does. And that toll varies heavily across different demographics. Using that latent class analysis, the sorting hat we mentioned, they broke the public into 4 classes.
8:01Right. And class one, which was about 13% of the population, actively disliked GMBS. Yes. They showed a negative preference overall. And demographically, they tended to be older, had lower education levels and had less genetic knowledge.
8:15Meanwhile, the classes that were highly eager to adopt it were generally younger or already familiar with genetics. Wait, so people are saying, give me all the answers, but only if they are 100% certain and totally fixable.
8:28Isn't that asking genomics to be a magic wand rather than a scientific tool? This raises an important question about the reality of genetics. Pathogenic variants don't equal clinical destiny. The public's desire for absolute certainty, just heavily clashes with biological reality.
8:44We don't have cures for everything, and penetrance is rarely perfect. Which is such a difficult reality to communicate. So transitioning from what people value to how they want this complex info delivered.
8:57What did the implementation DCE find? Well, first, when it comes to who introduces the screening, people strongly prefer GPs or obstetricians over midwives or nurses. Wow. That a 13.2% important score.
9:11But returning the results is even more critical. Right, absolutely. Who returns high chance result is the number one most important factor overall. It carried a 24% important score. 24%? Yeah. The public insists it must be a genetic health professional, not a GP.
9:25Though they were okay with in-person telehealth or phone as long as it was an expert. Okay, but what about the low chance results? Like when everything is all clear. Surprisingly, people preferred to receive even those low chance results in person.
9:40Really? Not just like through a secure on-less portal. Nope. They want a human to tell them in person. Here's where it gets really interesting. Currently, midwives handles standard newborn screening consent.
9:51But if the public demands that GPs and obstetricians handle the introduction and specialized geneticists handle the results, how on earth does a national healthcare system afford or staff that bottleneck?
10:03That is the massive policy implication here. To roll this out, massive workforce upscaling is desperately needed, especially for primary cure physicians. They need to understand genetics well enough to counsel parents, which is not standard training right now.
10:17Exactly. And we also have to note the study's limitations. This is stated preference, which is hypothetical. Right. It is not revealed preference. Filling out a survey is vastly different from sitting in a room with your newborn.
10:29Very different. Also, they had to exclude reproductive carrier screening from the survey entirely. Why is that? Because the cognitive load of adding another variable was just too high for the participants to process.
10:42Wow, just the thought of it was too much data to weigh, which kind of mirrors the real world problem of giving parents all this genomic data at once. Exactly. So you need massive digital support tools and specialized staff to make this work.
10:56So what does this all mean? I'd say the central insight is this. The public overwhelmingly values the diagnostic power of genomic newborn screening, but expects these programs to be highly accurate, focused on treatable conditions and guided by specialized human experts.
11:13For healthcare systems to successfully transition from basic heel pricks to genomic sequencing. They must dramatically rethink their service delivery models and workforce training to meet these high expectations.
11:23It's a massive undertaking. And it brings up such a profound philosophical thread. Consider the ethics here. Does a child have a right to an open future? Right, a life free of predetermined genetic expectations.
11:37Exactly. And how does that collide with a parent's desire to prepare for every possible medical outcome? It's a lot to weigh. What does this mean for the future of your family's healthcare? This episode was based on an open access article under the CCBY 4.0 license?
11:53You can find a direct link to the paper in the license in our episode description. If you enjoyed this, follow or subscribe in your podcast app and leave a 5 star rating. If you'd like to support our work, use the donation link in the description.
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