Speaker 1: Our health sector is in trouble, short staffed, under resourced,
Speaker 1: overwhelmed with patients who have complex and expensive needs.
Speaker 2: Our hospitals are among the least progressive in the Western
Speaker 2: world when it comes to digital health. Just as artificial
Speaker 2: intelligence shows potential to cut down ADMIN that sucks the
Speaker 2: life out of our doctors and nurses.
Speaker 3: So what can AI do for our health system.
Speaker 2: And what are the barriers that are preventing its uptake?
Speaker 1: On the Business Attack sponsored by two degrees Business this week,
Speaker 1: AI and how it could enhance public health if we
Speaker 1: can get our digital health house in order.
Speaker 4: When you talk to healthcare organizations across New Zealand at
Speaker 4: the moment and just ask the question of the board
Speaker 4: or the teams or even their chief Data and Digital officer,
Speaker 4: do you have an AI strategy? The answer is no.
Speaker 2: Doctor Will Reedy is on the EXTENTSI of New Zealand
Speaker 2: leadership team and part of the consulting firm's global health team. Now, Ben,
Speaker 2: your interview with will really get me one of the
Speaker 2: best overviews of where we're at with AI in health
Speaker 2: space in New Zealand. So everyone stick around for that.
Speaker 1: First though and keeping the health theme going. The Dyson
Speaker 1: Awards for Design Excellence are underway now, annual global awards
Speaker 1: where British inventor Sir James Dyson searches the world for
Speaker 1: the best young designers. The New Zealand winner has just
Speaker 1: been announced and Peter, I believe you were one of
Speaker 1: the judges.
Speaker 2: Yeah, they got me on just to run the ruler
Speaker 2: over it in terms of is this something that's going
Speaker 2: to connect with a big audience. We had health experts
Speaker 2: and other design experts. One of the top designers from
Speaker 2: Dyson was a judge as well. This was the first
Speaker 2: time I judged it, so it was really good. But
Speaker 2: the one that won was one of the most simple
Speaker 2: ones really, but was a design that we thought actually
Speaker 2: had a really addressable market. No one else was doing
Speaker 2: this and it's called the snapcap and a very simple
Speaker 2: device that really helps frontline health professionals deal with the
Speaker 2: containers that medicines come in, glass containers that need to
Speaker 2: be dismantled quickly on the frontline inwards and put in
Speaker 2: a sharpy bin to get rid of this stuff. You
Speaker 2: need a device to pull these things apart and break
Speaker 2: them open, and amazingly there wasn't one in existence.
Speaker 1: Yeah, it's a really cool looking device. It looks kind
Speaker 1: of like our twenty first century bottle opener.
Speaker 3: Very simple in.
Speaker 1: Design, very esthetically pleasing in design, and obviously much needed
Speaker 1: because I think in your interview you talk about the
Speaker 1: fact that frontline health professionals actually do get injuries from
Speaker 1: trying to open these little glass bottles.
Speaker 2: Yeah, they do, and it's just a reminder of how
Speaker 2: much our frontline health workforce have to do all sorts
Speaker 2: of little jobs you don't even think of that is
Speaker 2: up to them. So if we can make their lives
Speaker 2: easier and hopefully do it at a cheap price, that's great.
Speaker 4: You know.
Speaker 2: This was just one of about a dozen designs that
Speaker 2: we looked at. Some of the other stuff that was
Speaker 2: sort of like an exoskeleton that would replace a moon boot.
Speaker 2: There was insuls that can be customizable and three D
Speaker 2: printed for people who have problems with their feet if
Speaker 2: they've got potentially diabetes or something like that. There was
Speaker 2: a little sense so that you can put on the
Speaker 2: back of your shoulder if you're out jogging on a street.
Speaker 2: It will give you haptic feedback if it thinks that
Speaker 2: a car is getting too close to you or is
Speaker 2: potentially going to take you out, so great to see
Speaker 2: that creativity.
Speaker 1: I love the simplicity of the winning design, and listening
Speaker 1: to your conversation with the designer, Jack Pew gave me
Speaker 1: some really good insight into kind of how he got
Speaker 1: there and what he was thinking and the balance of
Speaker 1: talent and pragmatism that led him there. So let's have
Speaker 1: a listen to that interview.
Speaker 2: Now, Jack Pugh, Welcome to the Business of Tech, and
Speaker 2: congratulations on winning the New Zealand Dyson Awards. You were
Speaker 2: crowned the best design off about a dozen. I was
Speaker 2: under the actual judging panel, so I saw all of
Speaker 2: these dozen or so designs. Tell us a little bit
Speaker 2: about yourself, Jack, Where are you from? How did you
Speaker 2: get into design?
Speaker 5: Thanks Peter. So, I'm from christ Church, originally going to
Speaker 5: sort of come up to the Capital to study at Messy.
Speaker 5: I've always been quite interested in design when I was little.
Speaker 5: Any when you ask would tell you that I always
Speaker 5: wanted to be an inventor. So it's really cool to
Speaker 5: be able to sort of do this and have some
Speaker 5: recognition for it.
Speaker 2: You've won this award. Take us through your winning design.
Speaker 2: It's called the cap Snap what did you set out
Speaker 2: to achieve with the cap snap and what is it?
Speaker 5: Well, it's a simple tool for a simple problem in
Speaker 5: the theory, a medical ball opener for health professionals working
Speaker 5: with medications where they'd look to recycle them by taking
Speaker 5: off the aluminium crimpsy your caps, or to open these
Speaker 5: little glass vials which old medication called ampules. There's some
Speaker 5: safety risks associated with both, and so this tool kind
Speaker 5: of lets them do it in a real quick and
Speaker 5: easy way.
Speaker 2: Yeah, it looks like a bottle opener, and essentially it
Speaker 2: is a bottle opener. Yeah, functionally, because you know, just
Speaker 2: to try and visualize it, and unfortunately, I've got a
Speaker 2: lot of experience of this now visiting sick relatives in hospital.
Speaker 2: You'll see a medicine bottle. It's got some in this
Speaker 2: in the case, i know, immunotherapy liquid drug in it.
Speaker 2: It's a glass bottle, it's got an aluminium cap which
Speaker 2: is snug on it. You've got to separate those two
Speaker 2: things to recycle these materials. You also have, as you say, amples,
Speaker 2: these little sort of sealed glass containers that you have
Speaker 2: to crack open literally to get the liquid out of them.
Speaker 2: But they're really damn fiddly. And what I loved about
Speaker 2: your design. You've got one little device that probably doesn't
Speaker 2: cost that much to make, and it does both. It
Speaker 2: removes that aluminum casing from the top of the glass
Speaker 2: bottle and you can insert the ampule into the bottom
Speaker 2: of it and crack it in half. So the big
Speaker 2: benefit I saw from it is cutting down on the
Speaker 2: potential for nurses and doctors to hurt themselves going through
Speaker 2: that process cutting themselves on glass or on aluminium or
Speaker 2: a tool trying to take that off. It does both
Speaker 2: of those purposes.
Speaker 5: Yeah, that's right. The ways that people are currently getting
Speaker 5: around both those issues is they're using kind of makeshift
Speaker 5: solutions alcohol pads to step ampules, so at least if
Speaker 5: it does shedd in an unpredictable way, the glass will
Speaker 5: go into the air instead. And with those aluminium's caps,
Speaker 5: they're real fiddly. If you ever see someone tri tech
Speaker 5: one off, they don't have good tools suited for it,
Speaker 5: so they're using kind of four steps and kind of
Speaker 5: straining their hands to be able to pull them off.
Speaker 2: Yeah, it's dangerous. And you know what I love is
Speaker 2: the simplicity of this. Take us through your your design
Speaker 2: approach to this. This is a very specialized piece of equipment,
Speaker 2: So what work did you go through sort of talking
Speaker 2: to frontline health practitioners to inform the design of cap snap.
Speaker 5: Kind of things started off just kind of as a
Speaker 5: conversation on what are the issues, kind of what are
Speaker 5: they doing at the moment, and then from there tried
Speaker 5: to think of kind of a range of solutions. What
Speaker 5: would something handheld and quick and easy look like. First,
Speaker 5: maybe something mounted to the wall, or like a mix
Speaker 5: of both, something that's kind of a bit of a hybrid.
Speaker 5: And I kind of drew up some ideas and sat
Speaker 5: down with a member of the team and we kind
Speaker 5: of talked through some of the ideas and we ended
Speaker 5: up deciding that something that was real quick and small
Speaker 5: and portable to be able to be moved around if necessary,
Speaker 5: would be the kind of the best way forward. And
Speaker 5: then from there I kind of springboard into a bit
Speaker 5: of antive process, found some studies overseas looking at similar things.
Speaker 5: We kind of developed into well, it's a bottle with
Speaker 5: a cap, how about a botopner. We'll keep it super
Speaker 5: super easy. And then some of the issues that came
Speaker 5: up with one size kind of we couldn't have a
Speaker 5: one size fits all approach to have it be real functional,
Speaker 5: So we looked at what if we had a bollopner
Speaker 5: that could sort of adjust and through that kind of
Speaker 5: linear motion, we could incorporate that really seamlessly into the
Speaker 5: ampule snapping function.
Speaker 2: It's interesting this was not, by any means the most
Speaker 2: elaborate or sophisticated design that we came across the judging
Speaker 2: panel for the dice and awards. There were all sorts
Speaker 2: of quite elaborate designs that were probably required a lot
Speaker 2: more design forinesse. But what I loved about this one
Speaker 2: is that when I did research about it, no one
Speaker 2: was really doing this. Why do you think no one
Speaker 2: in the health profession has come up with something like this?
Speaker 5: Yet you get these things like the ampules or the
Speaker 5: crimseal caps, and then the job has to be done,
Speaker 5: so you come up with a workaround and you kind
Speaker 5: of that's just what you do. And then in a
Speaker 5: good and bad way, people don't make a lot of
Speaker 5: noise about it. And so we've got all this potential
Speaker 5: for interesting design solutions or just simple little fixes for
Speaker 5: these health staff we're having to do all these workarounds
Speaker 5: on a kind of a daily basis that just sort
Speaker 5: of someone needs to have a look at and try
Speaker 5: to come up with something.
Speaker 2: And that's exactly what you've done. You know, Sir James
Speaker 2: Dyson is famous for being a real iterative designer. Did
Speaker 2: you go through numerous iterations and either future obvious ones
Speaker 2: you see for this device to make it even better?
Speaker 5: Yeah, So a real fun part of the process is
Speaker 5: going through the iterations. So we went through a few
Speaker 5: different iterations looking at how I can keep it as
Speaker 5: simple as possible and reduce kind of them the number
Speaker 5: of mechanical parts in it. There are kind of two approaches.
Speaker 5: One kind of looked like a claw, if that makes sense,
Speaker 5: and that would allow it to be able to open
Speaker 5: a bunch of different sizes without having to use that
Speaker 5: slighter function. But the issue we kind of ran into
Speaker 5: with some of those prototypes is that it wasn't sort
Speaker 5: of snappy and intuitive. If you looked at it, you
Speaker 5: wouldn't know what you're looking at, and that was a
Speaker 5: real big part of the design is making it just
Speaker 5: super straightforward that you can look at it and pretty
Speaker 5: much figure out how to use it without any instruction.
Speaker 5: There's so little time to teach people about new things
Speaker 5: when a new tool comes in kind of in these busy,
Speaker 5: bustling environments that that's kind of what you want from
Speaker 5: a tool that's going to do just this quick and
Speaker 5: simple job.
Speaker 2: Yeah, Because it literally looks like a bottle opener, so
Speaker 2: instantly you have that recognition. You go, oh, I've got
Speaker 2: a bottle here, This must go around the neck. And
Speaker 2: then you've got the sort of the hidden compartment on
Speaker 2: the bottom of it, which is for breaking the ample
Speaker 2: as well. So I guess it's a bit of education
Speaker 2: required so that people know to use that. You're sitting
Speaker 2: in your lab as we talk here, you've got a
Speaker 2: three D printer behind you. Was that useful? Do you
Speaker 2: do a lot of iterations and design work and prototyping
Speaker 2: using three D printing?
Speaker 5: Yeah? So three D printing was a huge enabler for
Speaker 5: this project. That and water jet cutting was another super
Speaker 5: useful part in sort of smashing out these prototypes. I
Speaker 5: tried to kind of reduce the amount of plastic that
Speaker 5: I used where I could, so I tried to make
Speaker 5: my prototypes I can kind of hot swap between the
Speaker 5: different inserts to try the different geometries to see what
Speaker 5: was kind of the best and most effective fit when
Speaker 5: kind of figuring out some of the measurements. So yeah,
Speaker 5: definitely super pivotal and being able to quickly run through ideas.
Speaker 2: So design was only sort of part of the criteria
Speaker 2: for winning this award. A big part of it was
Speaker 2: the real world application and the potential for this to
Speaker 2: actually go on and be used. It's all well and
Speaker 2: good to design something that just never leaves the labor
Speaker 2: with the prototyping stage, and we did see some sort
Speaker 2: of designs like that. What are the next steps for you?
Speaker 2: Is this something that you'd like to pursue potentially as
Speaker 2: a business that the Snapcap try and get it out
Speaker 2: there into hospitals and clinics around the world.
Speaker 5: I would like to see it in people's hands and
Speaker 5: just making their lives a little bit easier for those tasks.
Speaker 5: So I'm able to put it a little bit of
Speaker 5: time in to be able to work up the design
Speaker 5: a little bit further. I've got some help from some
Speaker 5: awesome people at a couple of the other hospitals around
Speaker 5: the country been able to kind of cast the net
Speaker 5: a little bit wider see how the same issues are
Speaker 5: sort of getting received across those different sites. We're hoping
Speaker 5: to be able to work it into something that we
Speaker 5: can get into people's hands.
Speaker 2: The judges we're talking about this, we sort of thought
Speaker 2: this is great, and you submitted a video literally off
Speaker 2: a nurse who was I think snapping an ampool who
Speaker 2: actually cut herself.
Speaker 5: It wasn't scripted, but we had to use that tape.
Speaker 2: Well, that illustrates it very well. But we were thinking,
Speaker 2: why don't you just I mean, you need to break
Speaker 2: the ampull, but in terms of taking the aluminum cap
Speaker 2: off the bottle, why don't you just chuck it all
Speaker 2: in a bin and automate that later.
Speaker 5: That was an idea that we kind of tossed around
Speaker 5: at the start. But the kind of reality of kind
Speaker 5: of this product is that it'd be all well and
Speaker 5: good to make something real, awesome and automated, and I
Speaker 5: actually going into this project that's kind of what I
Speaker 5: was going to look to do. But then talking with
Speaker 5: the people and like hearing about the issues and then
Speaker 5: learning about the ampuel side of things, we've sort of
Speaker 5: determined that while technically it could be considered a band
Speaker 5: aid solution, it would be on the fastest track to
Speaker 5: be able to have this issue kind of be sold.
Speaker 2: That's what we loved about it, the simplicity of it.
Speaker 2: I mean, presumably this, if you get this into production,
Speaker 2: it wouldn't be a super expensive device to create either.
Speaker 5: Yeah, we're hoping to well, we're working to get the
Speaker 5: part count down as much as possible. Engineers in christ
Speaker 5: Church I've had some great input on on clever ways
Speaker 5: to really simplify that mechanism to even just three or
Speaker 5: four parts.
Speaker 3: Tops.
Speaker 2: Where are you working at the moment?
Speaker 5: So I'm working out of Wellington Regional Hospital, part of
Speaker 5: the Futtow Water Improvement team based out of here, so
Speaker 5: day to day I'm sort of looking at other issues,
Speaker 5: but it's still we're able to work on some innovative
Speaker 5: solutions sort of within the hospital, which is a really
Speaker 5: exciting sort of opportunity.
Speaker 2: Well, brilliant, you're in exactly the right place and they're
Speaker 2: lucky to have this design brain on the team there.
Speaker 2: So good luck for the next phase. And he's hoping
Speaker 2: we see snapcap in hospital wards before too long.
Speaker 1: Well hat fingers crossed, great young talent, Jack Pugh. Great
Speaker 1: to have those kinds of people coming through New Zealand,
Speaker 1: so big well done to him and look forward to
Speaker 1: seeing what he does next. So that's innovation and health hardware,
Speaker 1: and our topic of focus this week is AI in healthcare.
Speaker 1: Doctor Will Reedy is one of the country's leading experts
Speaker 1: in digital health. He joined Accentua around a year ago
Speaker 1: and is still a practicing doctor one day a week
Speaker 1: in the county's Monaco area.
Speaker 2: He's a lot of experience helping with the rollout of
Speaker 2: digital health systems all over the world, so he's pretty
Speaker 2: well placed to compare and contrast our preparedness and progress
Speaker 2: in the digital health space compared to the likes of Europe,
Speaker 2: the US and Australia, where he's also worked.
Speaker 3: Will's also really interested in the potential to reduce health
Speaker 3: inequities using digital health tech, that is, if we can
Speaker 3: trust machine learning and large language models to get it right.
Speaker 2: So here's Ben's interview with Accentures doctor Will Reedy.
Speaker 3: Good, Hey, Will, how are you great? Thanks?
Speaker 1: Ben good, Welcome to the Business of Tech podcast. Thanks
Speaker 1: for joining us. As so, why don't we start with
Speaker 1: if you could just give us a very quick summary of.
Speaker 3: Who you are, what you do, and a little bit
Speaker 3: about your background.
Speaker 4: So yeah, look, it's pleasure to be chatting with you
Speaker 4: this morning. So I guess my full time job is
Speaker 4: working for Accenture, is their how order health and wellness
Speaker 4: lead here in New Zealand with the goal to help
Speaker 4: the health system transform given some of the real challenges
Speaker 4: that many of us aware of at the moment in
Speaker 4: the health system. And then one day a week I
Speaker 4: do a shift in the surgical services at Middlemore so
Speaker 4: that can be in the emergency department and the clinics,
Speaker 4: in the wards and sometimes in theater. So I guess
Speaker 4: that keeps it real in terms of understanding the pulse
Speaker 4: of the health system at the clinical front line. But
Speaker 4: I guess ultimately the passion is to try and transform
Speaker 4: health systems with technology and things like AI.
Speaker 1: It must be quite start going from in Accenture talking
Speaker 1: about the latest and greatest worldwide AI this, and then
Speaker 1: you go into a hospital and very different story.
Speaker 3: I'd imagine, Yeah, it is.
Speaker 4: It's really interesting and it's generally accepted that in our
Speaker 4: hospital system, not so much in our GP systems or
Speaker 4: primary care systems. We are the least digitized hospitals now
Speaker 4: in the developed world. So it is a little bit
Speaker 4: of a change in terms of the global work that
Speaker 4: I do and seeing what's going on in terms of
Speaker 4: transformation and how far some other countries are ahead of us.
Speaker 4: Also being quite digital my day job at Accenture and
Speaker 4: then you know, having to use a pen and paper
Speaker 4: on Fridays pretty much.
Speaker 3: Yeah.
Speaker 1: But also I guess conversely, that also just helps you
Speaker 1: to understand the potential for change, right, and that actually
Speaker 1: how far we can go when we start to implement
Speaker 1: modern tech.
Speaker 4: Yeah. I think it's easy to kind of look at
Speaker 4: the I guess, the lower level of digitization and tech
Speaker 4: enable transformation in the New Zealand health system today. But
Speaker 4: it's also an opportunity, and my words are an opportunity
Speaker 4: to kind of leap frog some of the approaches and
Speaker 4: the thinking. So I do I'm quite optimistic about some
Speaker 4: of those opportunities for New Zealand just to go, hey,
Speaker 4: where are we trying to get to? What would we
Speaker 4: do differently? Could we leap frog ahead of some of
Speaker 4: the other jurisdictions.
Speaker 1: Yeah, it's interesting you use that term leap frog. That
Speaker 1: seems to be kind of a relatively common New Zealand
Speaker 1: experience where we kind of fall behind a little bit
Speaker 1: and then we go, oh, let's catch up, and in
Speaker 1: doing so we kind of go ahead and really hit
Speaker 1: that cutting edge again. Is that kind of what you're
Speaker 1: seeing happening at the moment?
Speaker 4: I guess, I see the opportunity and it's really interesting
Speaker 4: to share with you. It's funny how some of the
Speaker 4: AI technologies are becoming quite pervasive in healthcare. And a
Speaker 4: colleague of mine has been leading the way in gp
Speaker 4: Land all it or primary care in driving the adoption
Speaker 4: of a product called Nabler, which allows you, with the
Speaker 4: permission of the patient, to record the voice around the
Speaker 4: interaction with the patient and then convert that to text
Speaker 4: and then put it into the GP system. And our
Speaker 4: GPS I think about ranked about third in the world
Speaker 4: in terms of their levels of digitization. And that's been
Speaker 4: kind of the same kind of I guess measurement that's
Speaker 4: been in place for about twenty years. So primary care
Speaker 4: in New Zealand's actually been I guess at the forefront
Speaker 4: of tech for some time. And then you know, what
Speaker 4: he's seeing is first and foremost the patients and they're
Speaker 4: farno who are in the room with him, are seeing
Speaker 4: some benefits around more eye contact not turning around and
Speaker 4: typing stuff in the computer and in terms of the
Speaker 4: fifteen minute consult that is common in primary care. The
Speaker 4: other side that he's finding really interesting is efficiencies within
Speaker 4: the consult around typing everything down because we often paraphrase
Speaker 4: what the family or the patients say to us given
Speaker 4: the time limit. But what he's also finding, as our
Speaker 4: colleagues across about one dred and one hundred and fifty
Speaker 4: practices in New Zealand, is that the cognitive load, that
Speaker 4: the mental load is a lot less because you're having
Speaker 4: to recite and think things through. So piece of technology
Speaker 4: came along relatively recently and it's been adopted in about
Speaker 4: three hundred practices across New Zealand, which is about fifteen
Speaker 4: percent of the GP practices. So it's really interesting around
Speaker 4: that leap frog concept. Grab an idea and go with it. Yep.
Speaker 1: It is an interesting idea and it is one that
Speaker 1: has you know, it could have been earlier probably, but
Speaker 1: the reality is is that the technology that we have
Speaker 1: now around AI has just made it super accessible.
Speaker 3: Are there other.
Speaker 1: Areas that you're seeing that trend that the modern AI
Speaker 1: tools that we have now in the last couple of
Speaker 1: years have made things possible suddenly that would have seemed
Speaker 1: really onerous in the past.
Speaker 4: Yeah, look, it's interesting. I'll probably give some broader contexts.
Speaker 4: So one of the challenges in the health system at
Speaker 4: the moment is how do you adopt AI? And I
Speaker 4: guess people translate AI to generative AI at the moment,
Speaker 4: so it's just careful to be specific about that. And
Speaker 4: so the adoption piece is and I'll get down to
Speaker 4: some of the use cases shortly but effectively, when you
Speaker 4: talk to healthcare organizations across New Zealand at the moment,
Speaker 4: and just ask the question of the board or their
Speaker 4: exec teams or even their chief Data and Digital officer,
Speaker 4: do you have an AI strategy? And the answer is no,
Speaker 4: which is really interesting. And then the second question you
Speaker 4: ask in the context of adoption of AI, if you
Speaker 4: went down that path, is do you have a policy
Speaker 4: around how you'll adopt AI as an organization? And generally
Speaker 4: speaking not many have that either. But then you go, okay,
Speaker 4: put that to one size. You don't have a strategy,
Speaker 4: you don't have a policy. What are the core use
Speaker 4: cases that you've been thinking about that you'd like to
Speaker 4: get into your organization? In the next twelve months and
Speaker 4: again that's where it opens up interesting conversations. And so
Speaker 4: when we ran a leadership summit earlier in the year
Speaker 4: with the Chief Medical Officer for Health New Zealand and
Speaker 4: the head of the AI Advisory Group, the most common
Speaker 4: use case was surfacing genitive AI experiences to patients or
Speaker 4: family or FANO, so things like education CHAP as an example,
Speaker 4: I've just been diagnosed with diabetes. What can I expect
Speaker 4: and how do you get repeatable advice to patients where
Speaker 4: doctor or nurse isn't available as an example.
Speaker 1: That's kind of very similar to the recent announcement around
Speaker 1: GOVGBT right where it's the ingesting a bunch of government documents,
Speaker 1: government pages and then being able to chatbot style ask
Speaker 1: questions and get information about this governments.
Speaker 4: And I think I think in New Zealand, you know,
Speaker 4: the health systems around the world, particularly in socialized health
Speaker 4: systems like New Zealand, Australia in the UK, is everything's
Speaker 4: quite fragmented. So if you've got a consistent education piece
Speaker 4: experience for patients where no matter what question they ask,
Speaker 4: they are a consistent answer, it's actually a big benefit
Speaker 4: in terms of patients being empowered to manage a chronic
Speaker 4: I guess condition like diabetes. So yeah, we are quite
Speaker 4: surprised that everybody is going, how do we surface stuff
Speaker 4: to patients? Which is really interesting, So that's open up
Speaker 4: a new world. The second kind of area, broadly was
Speaker 4: what we call the clinical or the front line or
Speaker 4: the front of office, and so lots of use cases
Speaker 4: around voice detext and reducing the burden of me using
Speaker 4: pen and paper as an example, some benefits around managing inboxes,
Speaker 4: around lab results coming in because a lot of lab
Speaker 4: tests that we order for patients, we're kind of trying
Speaker 4: to rule something out and we want it to be
Speaker 4: if it comes back normal, then we don't really need
Speaker 4: to process that forget where I'm coming from. And then
Speaker 4: the back of office piece around workforce management and finance,
Speaker 4: procurement and supply chain. So those are the broad areas.
Speaker 4: So the reason I explain those broad areas around use
Speaker 4: cases is people are understanding there is potential to apply
Speaker 4: in particular generative AI to those use cases. It's just
Speaker 4: where are they going to get the biggest impact around
Speaker 4: healthcare in New Zealand. So I guess your question was, Hey,
Speaker 4: are people's eyes being opened up. Yes, they are because
Speaker 4: they're learning around use cases against offshore at the moment
Speaker 4: and going, hey, that could easily be applied here in
Speaker 4: the New Zealand context.
Speaker 1: Yeah, sticking with the generative AI theme, you know, I've
Speaker 1: often looked at the health of Fire website as it's
Speaker 1: now called, and just that that's such a huge corpus
Speaker 1: of information and data, like it seems like a great
Speaker 1: opportunity for something like an educational chatbot, But there is
Speaker 1: a lot of risk with that. Where chatbots are known
Speaker 1: to want to please people, they're known to kind of
Speaker 1: sometimes make things up if they're relying heavily on those
Speaker 1: LLAM models in the background. How are people in the
Speaker 1: health sector thinking about those risks considering the sensitivity.
Speaker 4: Yeah, it's a really good question. I think the interesting
Speaker 4: context is do healthcare organizations need to adopt genai or not?
Speaker 4: And the general trend overseas is they're all adopting it
Speaker 4: to see what the potential is, but not necessarily to
Speaker 4: roll it out at scale. And the reason they're doing
Speaker 4: that is it a competitive advantage? Does it deliver a
Speaker 4: better service? Those types of things. So one of the
Speaker 4: things I've seen In New Zealand. We have six and
Speaker 4: a half thousand healthcare organizations, of which one is Health
Speaker 4: New Zealand. It is the biggest, but that's the wider context.
Speaker 4: So organizations need to think about AI from a responsible perspective.
Speaker 4: And the biggest concern slash barrier is exactly what you
Speaker 4: just articulated, which is hallucinations. I think the soft words
Speaker 4: are unreliable outputs, and so I think a lot of
Speaker 4: that has to be un understood. Choosing our use case,
Speaker 4: learning about the use case, having the governance and leadership
Speaker 4: in place to go. Actually, we've tried this in a
Speaker 4: small use case. We have actually looked at what's happening
Speaker 4: overseas and these use cases do actually add value, but
Speaker 4: you'd got to go on the journey around I guess
Speaker 4: the hallucination side of things. The other thing that's interesting
Speaker 4: in New Zealand, in Health New Zealand as an example
Speaker 4: of starting to do it, is they need to get
Speaker 4: all their data in one place to run the GENAI
Speaker 4: lms across the top of it. And so there's definitely
Speaker 4: one that's the strategy for Health New Zealand, and they've
Speaker 4: started investing in something called National data platform, so they
Speaker 4: can put their data all in one place, whether it's
Speaker 4: clinical data, workforce data, finance data, and then they can
Speaker 4: start training the GENAI tools on top of their own
Speaker 4: data and then managing that piece. You still have hallucinations,
Speaker 4: don't get me wrong around data quality, but at least
Speaker 4: you're doing it on the data that you have governance
Speaker 4: over a couple of things to share with you. In
Speaker 4: terms of New Zealand's text for GENAI adoption, mass of
Speaker 4: concerns around liability. So if I have run a GENAI
Speaker 4: tool and I've surfaced it to a patient and it's
Speaker 4: given them some advice and something doesn't go as well
Speaker 4: as it would have liked, and there's more risk in
Speaker 4: terms of patient care, who's liable Is it the clinician
Speaker 4: or is it the GENAI And how does it actually work?
Speaker 4: So he's a little bit of maturity around what I
Speaker 4: would call regulation and compliance to think through, because at
Speaker 4: the end of the day, most healthyic organizations have a
Speaker 4: clinical obligation around the safety of the care that they provide.
Speaker 4: And if you introduce AI alongside the clinician, how does
Speaker 4: it actually work and what are the implications? And the
Speaker 4: last year that's really interesting is privacy and security of
Speaker 4: the data. So you might bring it all in, but
Speaker 4: you know, how do you actually control it in the
Speaker 4: world of more cyber attacks, particularly in health systems around
Speaker 4: the world. So those are kind of the core barriers.
Speaker 4: But the number one is obviously the hallucinations piece.
Speaker 1: Yeah, so you know, I guess part of that is
Speaker 1: having the confidence to experiment and trial and go at it,
Speaker 1: but also having the confidence to say, actually, in this case,
Speaker 1: the risks are too high, the technology is not there
Speaker 1: yet or may not be, and so we're going to
Speaker 1: choose to not make this a customer facing or patient
Speaker 1: facing thing. Keep it for doctors or healthcare providers and
Speaker 1: they can be the intermediary between the chatbot that's getting
Speaker 1: a lot of information and the patient at the other end.
Speaker 1: Is that kind of how thinking is going, Yeah.
Speaker 5: It is.
Speaker 4: It's an interesting piece because if you're wanting to experience
Speaker 4: an experiment and dip your toes and genitive AI, I
Speaker 4: think that the two pieces of conversation we're having in
Speaker 4: New Zealand at the moment is so, what are the
Speaker 4: use cases at a gathering momentum offshore and generally speaking
Speaker 4: in the healthcare context using GENAI to re platform, recode
Speaker 4: old applications, and New Zealand has a problem at the
Speaker 4: moment around that we've got a lot of legacy applications
Speaker 4: being used, particularly in the public health system. The second
Speaker 4: area is around contact center experience, and the third one
Speaker 4: is that voice to text that I talk about. So
Speaker 4: those are the three broad areas. The other thing that
Speaker 4: we've packed up offshore, which is interesting to share with you,
Speaker 4: is generally speaking, most of the GENAI use cases have
Speaker 4: been done on top of platforms. They're leveraging Salesforce, Microsoft,
Speaker 4: our electronic medical record platforms where genitive AI is being
Speaker 4: built in as a feature if you like, in these platforms.
Speaker 4: So the hallucinations piece isn't as big a risk because
Speaker 4: it's built into a platform. It's well tested, So I
Speaker 4: think it's a fine balance. But it's just interesting to
Speaker 4: see what the trends are in terms of the practical
Speaker 4: elements of gen AI, the hype versus in reality what's
Speaker 4: going on.
Speaker 1: Yeah, absolutely, that's kind of a lot about primary care,
Speaker 1: and we talked about how that's really advanced. What about
Speaker 1: in the hospital world.
Speaker 4: Yeah, Again, it's an interesting discussion around looking what happens
Speaker 4: off sure, and I think there's a couple of contextual things.
Speaker 4: So as a practicing clinician, when I think about technology
Speaker 4: like genitive AI, I think of it as another tool
Speaker 4: in my clinical practice, like over stethoscope around my neck.
Speaker 4: Most of the younger generation clinicians, I'm I'm a I
Speaker 4: guess I called a veteran these days because they've been
Speaker 4: around the health system for twenty five years. But if
Speaker 4: I look at some of the newly trained doctors and nurses,
Speaker 4: they all expect if you like, generative AI to be
Speaker 4: available for some of the use cases around again that
Speaker 4: voice detext piece, and we haven't done anything in New
Speaker 4: Zealand at the moment, but in Australia, the first use
Speaker 4: case is using voice to text and busy theaters to
Speaker 4: drive through throughput so you can hit health targets around,
Speaker 4: you know, like the waiting lists for hypophens and things
Speaker 4: like that. So there is a willingness for in that
Speaker 4: surgical operating theater for surgeons, anetheists, theater nurses to use
Speaker 4: those technologies to be more efficient in terms of through
Speaker 4: put through the theater because they're not writing notes after
Speaker 4: an operation. It's been done real time, so yes, there
Speaker 4: is potential, just not quite happening at the moment, and
Speaker 4: I guess that's the clinical frontline piece. Really interesting report
Speaker 4: that we did with Microsoft recently for New Zealand looking
Speaker 4: at how genitive AI could be applied to the nursing
Speaker 4: workforce and based on using some of the Microsoft technologies
Speaker 4: voice to texts predictive analytics around patients becoming unwell because
Speaker 4: they have temperatures gone up or their blood pressures dropped.
Speaker 4: They said, if you put on these common tools, you'd
Speaker 4: get a productivity increase of around nine to ten percent
Speaker 4: for each nurse across the country. So that's proven offshore,
Speaker 4: done a little bit of analysis around how I guess
Speaker 4: nursing workforce works the New Zealand today and our public hospitals.
Speaker 4: You apply these technologies and process improvement augmentation around genitive
Speaker 4: AI would actually lift productivity ten percent, which I guess
Speaker 4: you know eight to twelve hour shifts is you know
Speaker 4: one to one and a half hours, which does make
Speaker 4: a big difference.
Speaker 1: It does, especially if you're looking at you know, a
Speaker 1: shortage and if ten percent is saying you have the
Speaker 1: equivalent to ten nurses that have nine nurses on shift.
Speaker 3: That actually does make a difference end of the day.
Speaker 4: It does, and you know, we've got to you know,
Speaker 4: as you've heard in the media, we've got to adopt
Speaker 4: a shortage of nursing shortage and in some areas what
Speaker 4: I would call an allied health professional shortage BUZZIO is
Speaker 4: occupational therapists. The biggest year actually at the moment is
Speaker 4: anesthetic technicians. So that's actually preventing some of the through
Speaker 4: put in private and public hospitals where there's just enough
Speaker 4: of anesthetic technicians while you're sleep to look after you.
Speaker 4: It's really interesting at the moment.
Speaker 1: What about the casting forward into the future. Do you
Speaker 1: see it, as you know, potentially being a kind of
Speaker 1: first point of contact for patients to be able to
Speaker 1: say instead of just pushing a button waiting for a
Speaker 1: nurse pushing a button and saying, oh, I think my
Speaker 1: leg's really hurting and I'm not sure, and so then
Speaker 1: that can automatically go into like a database and be
Speaker 1: triaged and get the nurses to who needs to. Like,
Speaker 1: it strikes me there is a fair bit of potential
Speaker 1: in that first line of support for generative AI in
Speaker 1: the future.
Speaker 4: Yeah, look, I totally agree with you. So I think
Speaker 4: technologies like unit of AI we often talk about in
Speaker 4: the current health system of New Zealand, we've got to
Speaker 4: transform it generally. That means you spend in the next
Speaker 4: five years trying to change the reality is we need
Speaker 4: to ask New Zealanders, you know, what's your experience like
Speaker 4: in terms of their most recent interaction with a healthcare
Speaker 4: professional or a period of care and hospital. So my
Speaker 4: view is first and foremost is that's where things are going.
Speaker 4: I guess it's probably called consumerism and what do people
Speaker 4: expect in terms of their health experience and how do
Speaker 4: they compare it to other experiences like banking just to
Speaker 4: use it? And I guess at parallel so I do
Speaker 4: think one our customers, patients like you and I, will
Speaker 4: expect a better level of experience and driven by digital
Speaker 4: touch points, of which GENAI will power some of them.
Speaker 3: It's number one.
Speaker 4: The next question is do New Zealanders want it? And
Speaker 4: the other that is yes. So about seven or eight
Speaker 4: years ago a survey was done that I was involved
Speaker 4: and where we went around the country asking patients what
Speaker 4: their expectations were around digital tools to manage their disease
Speaker 4: and illness if they had something like diabetes, or their
Speaker 4: health and wellness where they're trying to prevent themselves from
Speaker 4: getting diabetes, and the overwhelming response was yes, we want
Speaker 4: a digital experience. I think the last piece to share
Speaker 4: with you, and it's a really interesting thing to think through,
Speaker 4: is we've got these workforce shortage challenges, which is a
Speaker 4: big problem to solve. But one of the things in
Speaker 4: other health systems have reimagined what healthcare could look like
Speaker 4: in terms of a journey for patients and their families
Speaker 4: is it's an interesting concept where there's kind of they
Speaker 4: have the capacity if you empower the right cohorts to
Speaker 4: manage their health and wellness to take some of the
Speaker 4: burden off doctors and nurses if they've got the right
Speaker 4: tools in front of them, or they can manage their
Speaker 4: diabetes themselves. So I think the other thing that's coming
Speaker 4: is we enable more digital journeys, patients and their families
Speaker 4: and farnes will take more control over their health and
Speaker 4: wellness and that'll take some of the burden off the
Speaker 4: health system and it waits up all the workforce shortage problems.
Speaker 4: Will help in terms of at the moment, you probably
Speaker 4: got demand, but they can meet that with their own capacity.
Speaker 4: It's a funny way of thinking about things, but definitely
Speaker 4: that's the general trained off shore at the moment.
Speaker 1: The other thing that strikes me is as not generative
Speaker 1: AI specifically, but machine learning based tools, the kind of
Speaker 1: classic AI as I kind of refer to it in
Speaker 1: my head. The application of that is becoming so much
Speaker 1: more capable and so much more broadly applied that actually
Speaker 1: some of these widgets may not necessarily be needed where
Speaker 1: they definitely were before.
Speaker 3: And I'm thinking of things.
Speaker 1: Like taku eyes take a photo of your eye to
Speaker 1: get certain diagnoses. That strikes me as a way that
Speaker 1: AI is helping us directly move towards some level of
Speaker 1: equity because you don't need to have as much equipment
Speaker 1: in order to be able to actually address or monitor
Speaker 1: in some ways.
Speaker 3: Are you seeing that as well?
Speaker 4: You see the channel you know, I probably call that
Speaker 4: democratization of health and wellness, right, It's a really interesting story.
Speaker 4: So yeah, I've been involved with Tokui since the start
Speaker 4: Spark Health in my previous role provide U some innovation
Speaker 4: funding to get them using aws on the cloud to
Speaker 4: run their algorithms around the email that you just talked about.
Speaker 4: So and again, that's a little bit of that of
Speaker 4: a consumer customer experience piece where you gather a photo
Speaker 4: of the retina. How you gather it can be multiple
Speaker 4: different ways, and then you teaching this algorithm to kind
Speaker 4: of go, have you got diabetic retinopathy or hypertensive retinopathy?
Speaker 2: Yes?
Speaker 4: Or no? No, don't worry about it. Come back in
Speaker 4: a year and get screened. Oh yes, you do set
Speaker 4: up the referral path. So and I guess that's that's
Speaker 4: one people like tokuais going, hey, we need to unlock, democratize,
Speaker 4: provide better X this provide better experience. I definitely see
Speaker 4: that coming. It's an interesting area because, as you have alluded, so,
Speaker 4: it's diagnostics, right, and again my views medicine traditionally is
Speaker 4: you come and see me, I take a history from you,
Speaker 4: I run a whole lot of tests, and we work
Speaker 4: out what your diagnosis is. With the sophistication of diagnostics
Speaker 4: these days, you almost do the diagnostic first to help
Speaker 4: you get to the diagnosis, because sometimes it's the gold
Speaker 4: standard and you don't necessarily need to take the history
Speaker 4: of how you've been feeling. Those types of things so
Speaker 4: from my perspective, I think diagnostics are going to get better.
Speaker 4: One of the real challenges that's happened off shore is
Speaker 4: when patients engage in those diagnostic type tools. If it's right, great,
Speaker 4: if it's kind of a little bit on the fence
Speaker 4: around what your diagnosis is and how do you kind
Speaker 4: of enter into the system to get it clarified. Because
Speaker 4: there's the science of medicine that I talked about before,
Speaker 4: and there's the art of medicine. And sometimes what you
Speaker 4: find and a diagnostic is that it can be one
Speaker 4: diagnosis or sometimes it can mean three or four other
Speaker 4: diagnoses and you need to do further diagnostic tests to
Speaker 4: kind of rule bring out till you get to the one.
Speaker 4: So it's a little bit a little bit to think
Speaker 4: through there. But I agree with you in terms of
Speaker 4: companies like toku Wai's kind of setting the standard around
Speaker 4: machine learning and changing the access to those types of services.
Speaker 1: I imagine, you know, maybe ten twenty years, You've got
Speaker 1: somebody at home and it's like our time for my
Speaker 1: medical checkup, and they get out their smartphone and they
Speaker 1: take some photos of various things part of their body,
Speaker 1: and they say some words and they you know, maybe
Speaker 1: get a smart cheap smart watch and it takes some
Speaker 1: stuff like that, and then that can feed into an
Speaker 1: algorithm which can be sent to a GP to go,
Speaker 1: oh yep, it all looks okay, Like we can give
Speaker 1: you the medical tick really, like you said, democratizing it
Speaker 1: but also taking it out of urban centers as well
Speaker 1: and allowing people who may not have as much access
Speaker 1: to primary healthcare to really receive the early intervention care
Speaker 1: that can actually make a big difference.
Speaker 4: Yeah, yeah, look, I totally agree with you. One of
Speaker 4: the things I was going to share with you today
Speaker 4: is being some more and I'm involved in Martin and
Speaker 4: PACIFICA getting into digital health tech. And the reason I'm
Speaker 4: bringing this up is there's an element of driving kind
Speaker 4: of a national way of working rural or urban around healthcare.
Speaker 4: But the other thing that's really interesting is sometimes communities
Speaker 4: need to solve for themselves. So they understand the business
Speaker 4: problem or the health problem. They've got some tech that
Speaker 4: they could use, but they actually come together as a
Speaker 4: community around how they solve some of these problems. So
Speaker 4: I think what we'll see in the future in terms
Speaker 4: of what I'm trying to cover here is you'll have
Speaker 4: national ways of working around these health checks that might
Speaker 4: work for eighty percent of New Zealanders, but it doesn't
Speaker 4: work potentially behaviorally for twenty percent. And I'll follow this
Speaker 4: through So in the PACIFICA communities, it's really really hard
Speaker 4: to get Pacifica to engage with the health system, and
Speaker 4: so how do you engage with them? And if you're
Speaker 4: offering this tooling, how digitally enabled are my mum, she's
Speaker 4: saw them on Chinese she's seventy five, not particularly digitally enabled.
Speaker 4: But if you had the tool to do a health
Speaker 4: check remotely, who would go and do that with her?
Speaker 4: And it's probably been me or one of my three
Speaker 4: younger brothers actually facilitate the processes. They've been independent enough
Speaker 4: to do it. So there's a few but the technology
Speaker 4: is enabled, but how do you practically get people to
Speaker 4: use the tech to do the remote health and wellness
Speaker 4: checks on an annual basis with the GP So there's
Speaker 4: some of that. And the reason I'm showing that with
Speaker 4: you is is once you understand the opportunity the technology,
Speaker 4: it's really interesting to see how communities solve for how
Speaker 4: they practically get the adoption of the tech to improve
Speaker 4: health and wellness outcomes, and I think that's awesome. And
Speaker 4: the other side of that is I think in my
Speaker 4: experience at Accenture that the work we're doing in our
Speaker 4: words around mary Indigenous people of New Zealand, some of
Speaker 4: the problems you're trying to solve in New Zealand at
Speaker 4: the moment, we're ahead of other parts of the world.
Speaker 4: So I think about the Native Indian in America, I
Speaker 4: think about Aboriginal and Tory Straight Islanders in Australia. Some
Speaker 4: of the things we're doing in New Zealand already around
Speaker 4: machine learning junior of AI sometimes through that EWI actually
Speaker 4: is ahead of everybody else. So there's a little bit
Speaker 4: around what we do in New Zealand. If we get
Speaker 4: it right and get the adoption, we can kind of
Speaker 4: show the world how you can improve equity for Formardi
Speaker 4: pacifica as some examples.
Speaker 1: Can you share a kind of an example of what
Speaker 1: you mean by that? What are some of the interventions? Y?
Speaker 4: Yeah, so no, it's really interesting to share with you.
Speaker 4: So probably two places to start. One of the things
Speaker 4: that I think, you know, what does the future of
Speaker 4: health and wellness look like in New Zealand and it's
Speaker 4: a really interesting to think thing to share with you
Speaker 4: that there's this this concept called social determinants of health.
Speaker 4: And effectively, if you digitize you every experience in the
Speaker 4: health system, from a GP through to physio through to
Speaker 4: beteen a hospital doctor, you'd only get one fifth of
Speaker 4: the data that determines yours and my health and wellness outcomes.
Speaker 4: Then the number one data items your post code and
Speaker 4: where you live. But there's a whole lot of behavioral
Speaker 4: stuff around do you exercise, do you smoke, do you drink?
Speaker 4: What are your family what's your family history. I've got
Speaker 4: a strong family history of a schemic heart disease in
Speaker 4: my family. Where do you live, how educated are you?
Speaker 4: As your house warm or cold? Those types of things.
Speaker 4: So one of the opportunities in New Zealand is to
Speaker 4: have that holistic approach to social atterminans of health. It's
Speaker 4: called now in Martyrdom, there's another concept called tafade Tapafa
Speaker 4: and that looks at your emotional health and wellness, your
Speaker 4: physical you're spiritual and your mental health and wellness and
Speaker 4: so some of the things that you're doing around how
Speaker 4: they're applying the tech to that whole person. In the
Speaker 4: community is actually having better health and wellness outcomes and
Speaker 4: just doing a health system response. So coming back to
Speaker 4: some of the use cases that happening at the moment,
Speaker 4: So there's a lot of the communities in a number
Speaker 4: of EEHE where they're collecting data around all those things
Speaker 4: mental health, I guess, general physical health and well being,
Speaker 4: emotional and spiritual health and wellbeing, and is starting to
Speaker 4: algorithms across the top of that and so and that
Speaker 4: helps them do care plans as an example for that
Speaker 4: are not just about you know, take your high blood
Speaker 4: pressure medication, will walk for thirty minutes today, it's around
Speaker 4: thinking about the holistic person. So, and they're using genai
Speaker 4: to link that outcomes and drive insights. And they're also
Speaker 4: using a bit of email around predictive analytics. And it
Speaker 4: comes back to innovation in New Zealand thinking about health
Speaker 4: and wellness differently, and then those models of delivering health
Speaker 4: and wellness I think where things are going to go globally.
Speaker 1: That's really interesting because it's moving away from this concept
Speaker 1: that population aggregated data is the best way of assessing
Speaker 1: a population's health and saying well, if you can actually
Speaker 1: take data from specific populations and you can really dynamically
Speaker 1: split it out by post code, by you know, ethnic background,
Speaker 1: and run analysis really quickly and easily over different areas.
Speaker 1: And that is directly a result of modern digital data tools.
Speaker 2: Right.
Speaker 1: It wouldn't have been possible even twenty years ago because
Speaker 1: everything was so slow and difficult to actually to do.
Speaker 1: But the result of being able to do it dynamically
Speaker 1: and quickly means that you can really look at areas
Speaker 1: where it is most needed and make targeted interventions that
Speaker 1: are taking consideration more than just you know, high blood pressure.
Speaker 4: Here's your medicine, Yeah, exactly, And so you know, to
Speaker 4: share with you, we've started a conversation with the Ministry
Speaker 4: of Social Development and with and also with bai Kaha,
Speaker 4: the ministry of disabled people that got broken off from
Speaker 4: the health system as part of the reforms, and with
Speaker 4: ACC and the context for that conversation is in communities
Speaker 4: where health and wellness is a real challenge, how will
Speaker 4: you bring insights health social disability in some case is
Speaker 4: injury prevention perspective, focusing on an individual or the healthhold
Speaker 4: they live in or the community they live in. And
Speaker 4: so there's an enabling policy. I'll call it from the
Speaker 4: DIA at the moment in Wellington around sharing identity across
Speaker 4: those government agencies. So NHI in the hospital context or
Speaker 4: health context and acc have a unique number for us
Speaker 4: as well, so you know, so they can link my
Speaker 4: record from the health system to I guess a shoulder
Speaker 4: dislocation I had a few years ago and I was
Speaker 4: playing rugby from an accident perspective. So there's enabling policy
Speaker 4: to share identity so you can have a single view
Speaker 4: of somebody. Then the second bit of that is what
Speaker 4: data can be shared, and the third part of that
Speaker 4: is what are some of the GENAI use cases you
Speaker 4: can run across the top of health data, social services data,
Speaker 4: disability data, and so there's real buy in across these
Speaker 4: four agencies to kind of look at what the art
Speaker 4: of the possible is in bringing together these agencies and
Speaker 4: sharing data and a entity. Then once you've got that data,
Speaker 4: how can you improve the experience for these some of
Speaker 4: these communities that are affected in those contexts. So early
Speaker 4: doors at the moment for us, but something that we
Speaker 4: do offshore a lot, which is, hey, how do you
Speaker 4: get these government agencies to think about the total picture
Speaker 4: of social permanence of health and how do you bring
Speaker 4: them together to offer new experiences and what opportunities does
Speaker 4: genetve Ai bring. So it's a fascinating project that we've
Speaker 4: started about three months ago, and then we're about to
Speaker 4: get those agencies to look at the ard of the
Speaker 4: possible of some of the things we're doing off sure again,
Speaker 4: coming back to part of the conversations day, the Genai
Speaker 4: conversation opens up these conversations around thinking about reimagining health
Speaker 4: and wellness.
Speaker 1: Is there anything that you would like to add, anything
Speaker 1: that important you think we haven't covered.
Speaker 4: So something I've been doing for some time is wearing
Speaker 4: auring and it's really interesting. It started off as just
Speaker 4: I Guess a tool to collect health and fitness data,
Speaker 4: and with Genai coming along and now takes that data,
Speaker 4: runs algorithms and goes measures mental resilience and it measures
Speaker 4: whether I should not go and exercise today because I'm
Speaker 4: not ready to do that. So I use that every
Speaker 4: day and it also has a I Guess a health
Speaker 4: coach based on the data. So just to share with
Speaker 4: you right now, my level of daytime stress based on
Speaker 4: the ring and the algorithms to me and what I've
Speaker 4: been like for the last five years, I'm relaxed, So
Speaker 4: that Ben, you must be running a good into you today.
Speaker 3: Yeah.
Speaker 4: Then it measures my heart health and tells me how
Speaker 4: old my heart is relative to my age. So according
Speaker 4: according to the app, I'm fifty one, and according to
Speaker 4: the app, my heart's forty seven. And so I guess
Speaker 4: what I'm sharing with you is coming back to some
Speaker 4: of these experiences over time, and that consumerism trend I
Speaker 4: see generally speaking Kiwi's you know, we'll get some of
Speaker 4: these experiences where they manage their health and wellness leveraging
Speaker 4: machine learning, generative AI, and then and then when they
Speaker 4: think they need the intervention of the health system or
Speaker 4: to navigate the health system, then they'll touch the health system.
Speaker 4: So right now I wouldn't get where I'm coming from.
Speaker 4: But if my heart health went the other way, or
Speaker 4: my pulse is getting higher, or I was getting my
Speaker 4: mental resilience wasn't so good, I'd consider potentially, you know,
Speaker 4: going and seeing my family GP.
Speaker 1: And I guess even if you couldn't put an awring
Speaker 1: on every finger in New Zealand, you could have them
Speaker 1: in digital check up spots and churches and might I
Speaker 1: and you know, a GP clinic where you can just
Speaker 1: pop in and get that done really easily and dynamically
Speaker 1: and without and linking that back to your health data
Speaker 1: so that it can directly feed and maybe flag something
Speaker 1: at your GP if there's something wrong.
Speaker 4: Yeah, and look being a really important thing you just
Speaker 4: packed up upon that I should have talked about before,
Speaker 4: which is the data in the future is going to
Speaker 4: be a mixture of what I put in as a
Speaker 4: provider about you, but it also should include the information
Speaker 4: you put in about you. I see that trend coming,
Speaker 4: but pragmatically, do people want it? And I think the
Speaker 4: answers over time yes, if they start learning about some
Speaker 4: of the capabilities, but they need to be empowered to
Speaker 4: manage the health.
Speaker 1: I have to say I thoroughly enjoyed that interview. I
Speaker 1: thought Will was really great in the content and the
Speaker 1: specificity that he went into around the use of AI
Speaker 1: and healthcare, right from generative AI into kind of the
Speaker 1: Toku Eyes style machine learning and everywhere in between.
Speaker 3: I thought it was really interesting.
Speaker 2: He was great, you know, and obviously Accentua is heavily
Speaker 2: involved in what's going on in the health sector. They're
Speaker 2: helping out the government and probably earning a lot of
Speaker 2: good consulting fees. But it was a real sort of,
Speaker 2: I think, frank and upfront sort of assessment of where
Speaker 2: we're at, and a real takeaway for me is what
Speaker 2: we're coming from behind. Not on the primary health I
Speaker 2: was surprised, you know, Will suggested that we're maybe the
Speaker 2: third best in the world when it comes to GP
Speaker 2: clinics and that offering digital health service. So my experience
Speaker 2: off it hasn't been particularly great with patient portals and
Speaker 2: literally watching doctors punching stuff into their computer while I'm
Speaker 2: paying for them to do that. But I think we
Speaker 2: all know that in hospitals, our systems have not been
Speaker 2: great at evolving to meet the modern needs of the population,
Speaker 2: and he's definitely put his finger on that. So I
Speaker 2: was surprised and pleasantly surprised to hear a lot of
Speaker 2: the experimentation and innovation that's already going on with population
Speaker 2: health data and that and applying machine learning to it.
Speaker 2: So that's great. There's some really cool pilots and stuff
Speaker 2: going on with medical devices and people's homes, and then
Speaker 2: all of that data eventually could be used in conjunction
Speaker 2: with AI for predictive health. So there's a lot of
Speaker 2: good stuff going on, but some big barriers. There's well,
Speaker 2: we're way behind, We're struggling with a funding crisis in
Speaker 2: health so and the data is not yet in a
Speaker 2: state where frankly it's going to be reliable enough to
Speaker 2: feed into AI system. So a heck of a lot
Speaker 2: of work to do.
Speaker 1: Yeah, project here wants an embattled, difficult project is now dead.
Speaker 1: Project another failed attempt to conglomerate this healthcare data into
Speaker 1: something national and consistent. But we have to get there
Speaker 1: at some point. I have to believe that at some
Speaker 1: point we're going to need to figure it out. And
Speaker 1: maybe trying to create something from the ground up is
Speaker 1: just hubris. Maybe we need to figure out a better
Speaker 1: kind of glue wear approach or something. But whatever it is,
Speaker 1: we need to unlock this data and start enabling it
Speaker 1: the sharing between ACC and hospitals and GPS and like
Speaker 1: will said in the interview, figuring out how people can
Speaker 1: actually input their own data through their wearable where that's
Speaker 1: Aora ring and Apple watch or a glucose monitoring system
Speaker 1: or whatever else, it will really take us a step
Speaker 1: forward and ahead of a lot of other countries if
Speaker 1: we can manage to get there.
Speaker 2: Yeah, one of the barriers he mentioned there, which I
Speaker 2: was a little bit surprised about, is massive concerns about liability.
Speaker 2: So we might need some regulation and compliance tweaks to
Speaker 2: give health providers the confidence to use AI and not
Speaker 2: be worried about getting sued. I thought that would have
Speaker 2: been a bigger deal in a place like the US.
Speaker 2: And actually last week was a visiting expert in AI
Speaker 2: came through New Zealand and she told me exactly that
Speaker 2: she's working with doctors and radiographers and that using AI
Speaker 2: and machine learning to try and improve testing and analyzing
Speaker 2: test results. And she said the senior doctors in particular
Speaker 2: are really pushing back because they're worried about getting sued
Speaker 2: and getting their clinic or their hospital suit as well
Speaker 2: by making a wrong diagnosis. So that's clearly an issue
Speaker 2: here as well. So having that confidence to be able
Speaker 2: to put some trust in these systems is going to
Speaker 2: be key, and maybe we don't have quite the regulatory
Speaker 2: environment to allow that.
Speaker 1: Yeah, just putting those policies in place so that you
Speaker 1: know it's not going to be ramp and AI and
Speaker 1: making misdiagnoses all over the place. They are going to
Speaker 1: be in conjunction with good diagnosticians as well, so they're
Speaker 1: being checked and human in the chair and all that
Speaker 1: good stuff.
Speaker 2: Yeah. And the other interesting thing that will point it
Speaker 2: out when he goes out and talks to hospitals and
Speaker 2: clinicians and that sort of thing, a lot of them say, no,
Speaker 2: we don't actually have a policy or even a strategy
Speaker 2: around using AI. And this is I think we see
Speaker 2: just about in any area of industry and business at
Speaker 2: the moment, people immediately jumped to the use case. So
Speaker 2: I haven't got a strategy for it, but I know
Speaker 2: my customers want this. And when it comes to healthcare,
Speaker 2: it's using generative AI to surface experiences for patients. So
Speaker 2: giving them a chatbot that they can query about sensitive
Speaker 2: health related issues and they'll get reliable information. It's that
Speaker 2: sort of stuff that actually the health sector thinks is
Speaker 2: the frontline of the generative AI revolution.
Speaker 4: Yep.
Speaker 3: It's a big revolution and it's coming. We've just got
Speaker 3: to make sure we're ready for it.
Speaker 2: Absolutely. So thanks to doctor Will Reedy for coming on
Speaker 2: the Business of Tech, and we'll have more episodes coming
Speaker 2: in this ongoing series about how AI is impacting various
Speaker 2: sectors and industries across a tea.
Speaker 1: Show notes in the Tech section of the Business Desk
Speaker 1: website and the podcast is available on iHeartRadio, well your
Speaker 1: favorite podcast platform.
Speaker 2: Let us know what you think of the show and
Speaker 2: drop us a line with suggestions for future gare email
Speaker 2: Ben on benat Businessdesk dot co, dot MZ, or you
Speaker 2: can find both of us on LinkedIn and x.
Speaker 1: Next Thursday, we'll be talking mergers and acquisitions and the
Speaker 1: complex technical decisions relating to digital infrastructure that need to
Speaker 1: be made when businesses come together.
Speaker 2: Until then, have a great week.