WEBVTT
00:00:08.560 --> 00:00:12.880
Hello and welcome to this special episode of Tracky Talk.
00:00:13.039 --> 00:00:26.480
We're here in Bengaluru in the south part of India and I'm joined by Professor Sarah Wallace, OBE, who's a legendary speech and language pathologist that I'm sure many of you know.
00:00:26.800 --> 00:00:34.240
We're currently in the Holiday Inn near the race course in Bengaluru and we're very grateful to the staff for finding us this nice quiet space.
00:00:34.399 --> 00:00:48.719
We've got a bit of time to kill before we have to head home, so we thought it'd be a really good idea to spend a bit of time just reflecting on what we have observed and learnt, and some of the people that we've met and some of the things that we've seen in India.
00:00:48.880 --> 00:00:51.039
So I hope you find that useful.
00:00:56.399 --> 00:01:06.560
Lots of the research about tracheostomy care and changes and this multidisciplinary, multi-professional approach has come from University Commons, the West, hasn't it?
00:01:06.640 --> 00:01:06.719
Yeah.
00:01:06.959 --> 00:01:12.239
And obviously Australia have been strong players in the Global Tracheostomy Collaborative as well.
00:01:12.799 --> 00:01:21.120
And as you quite rightly say, it we need some data from this part of the world to reflect the challenges and the way that they manage things here.
00:01:21.519 --> 00:01:23.040
And they're different, they have different diseases.
00:01:23.200 --> 00:01:23.840
Yeah, different pathologies.
00:01:30.239 --> 00:01:39.439
They've got TB, lots of TB here, and other diseases that are uh pre more prevalent than than us, so different types of trachiosomy cohorts.
00:01:39.599 --> 00:01:39.760
Yeah.
00:01:40.079 --> 00:01:44.799
And at the head net cancers that we saw, as as you said, I mean that there's a lot of tobacco chewing.
00:01:44.959 --> 00:01:45.280
Yes.
00:01:45.519 --> 00:01:49.040
Which which I I sort of was aware of, but not aware of the scale of it.
00:01:49.280 --> 00:01:59.519
And uh, you know, some of the people met in the outpatient clinic were presented with pretty significant tumours, they'd sort of been ignoring them, they probably knew what it was, didn't want to see couldn't afford to.
00:02:04.079 --> 00:02:05.920
So very different populations.
00:02:06.319 --> 00:02:13.840
And uh, I mean, trying to get some data uh from this part of the world would be amazing, and it was great that all these hospitals that we visited.
00:02:14.159 --> 00:02:20.479
We talked a lot about the global trackers to be collaborative and and that way of trying to improve care through data.
00:02:20.560 --> 00:02:27.759
I mean, that that's how you know where you are, that's how you know where you're going, and that's how you know whether you're as good or different to other hospitals.
00:02:27.840 --> 00:02:34.319
And when you know that, you can then ask the hospital, okay, so what are you doing that I'm not, or the other hospitals say, Well, you're you're doing that really well.
00:02:34.560 --> 00:02:36.639
Can we take some information from you?
00:02:36.960 --> 00:03:05.039
Yeah, and I think I think we talked about the global south, didn't we, and how this it would be amazing if we could have that sort of um data to show you know what are the what are the future directions that people need to go in, and you know, they're already collaborating and they're already kind of recognising the you know many of the problems that patients with tracheostomies have, but you know, it's it's how do they use things like AI?
00:03:05.199 --> 00:03:08.639
Yeah, we went to that amazing art park as well, didn't we?
00:03:08.719 --> 00:03:09.840
Go on and tell them about that.
00:03:10.080 --> 00:03:23.120
So the art park is a centre for AI and and robotics, and uh it's like an innovation space, lots of work around AI applied to lots of different sectors, and and a relatively small chunk of their work was was in healthcare.
00:03:23.199 --> 00:03:27.840
But when we say that, when they told us about what they were doing, it's actually huge.
00:03:28.000 --> 00:03:51.280
Um, a lot of work in Covid, but what they've been able to demonstrate is they can access data sets, they're trying to get standardized data sets for certain things because there's lots of different pockets of data around India, but but there are some commonalities, and they were trying to piece things together and and then I mean it was predictive models we were talking about, in particular about uh dengue fever and sort of predicting outbreaks, things like that.
00:03:51.360 --> 00:04:17.680
But um, we we were then we were talking at St John's about they've got a real strong focus on uh AI in their research, and and the GTC database now has 20,000 uh cases in there with patients with tracheostomies, and that's right for applying these sort of artificially intelligent systems too to see if we can start to predict uh some of the some of the outcomes maybe or or predict which patients will benefit from certain things.
00:04:17.839 --> 00:04:32.879
Uh, but again, like you said, Sarah, and having sort of India or global south specific data in there, you know, will really help because you can't apply what we're up to in uh the north of England to what's happening in the south of India.
00:04:33.040 --> 00:04:35.360
But the you know the principles certainly were there.
00:04:35.519 --> 00:04:54.959
And I mean what I'll take away from this is you know the next steps is definitely collaboration, um, a lot of shared learning, and we were very clear to say to the guys, look, we're not here to tell you what to do, we're here to learn from what you're doing, and we're here to explain what we've picked up from working with and talking to lots of other people around the world.
00:04:55.040 --> 00:05:09.680
And that shared learning, you know, was was clearly very strong, and then that focus on you know research in this setting, collecting some data and really trying to understand what's going on now and how we can make some tweaks and see whether we can make any improvements.
00:05:10.480 --> 00:05:18.800
I wondered what your reflections were on you know the sort of the next steps perhaps for the for the speech and language therapy teams that you've met here.
00:05:19.120 --> 00:05:23.759
I think it's really exciting because I think um there was so much enthusiasm, wasn't there?
00:05:23.839 --> 00:05:31.680
Yeah, there's been so much enthusiasm everywhere we've gone for learning and for um pushing quality of care.
00:05:32.480 --> 00:05:35.199
Lots and lots of conversations about quality of care.
00:05:35.439 --> 00:05:42.240
But like you say at the moment, I think there's a just uh it's all a little bit of an unknown uh entity, isn't it?
00:05:42.319 --> 00:05:46.000
Around what is happening to patients, especially after hospital, yeah.
00:05:46.240 --> 00:05:52.959
Um, but even in the hospital, because many of them are not getting seen early enough or at all.
00:05:53.120 --> 00:06:13.759
Yeah, um, so I feel like um apart from the fact that we've built friendships and collaborations with people, I felt like in at Tata Memorial, that opportunity to get 250 people from all over India in one space, they were networking with each other as well.
00:06:14.000 --> 00:06:15.120
Yeah, it was really nice to see that.
00:06:15.439 --> 00:06:25.600
That was great to see because especially when so I did two presentations um jointly with, I'm gonna give a shout-out to Arun um Arun Balaji.
00:06:26.959 --> 00:06:59.600
Who is um the head of the speech therapy department in Tata, who has helped facilitate this whole thing, um, and he is he is incredible, but you know, I invited him to do presentations jointly because I can't give the Indian perspective, I can tell what we you know promote in terms of quality of care and communication and swallow, and he could then say, Um, you know, so this is how we translate this to India, and um and there was a you know a lot of people in the audience who were able to, we had a lot of panel discussions, didn't we?
00:06:59.680 --> 00:07:21.680
So there was some really what I took away most was the conversations we had in those panel discussions where people shared their setting, their challenges, but also lots of people saying, Oh, you know, I'm I'm working, I don't know, in um another part of India, you know, in Rajasthan or whatever, and you know, I I can I've actually got this, and other people saying, Oh, how did you get it?
00:07:21.759 --> 00:07:25.199
You know, how did you get that speaking variable because we can't get them?
00:07:25.279 --> 00:07:30.000
And so that I think it facilitated things to happen within India, I hope.
00:07:30.160 --> 00:07:45.279
Yeah, and you know, the support of of all of the leadership teams in these organizations has been incredible, and I think they really, really want, I feel like we've we've facilitated hopefully some some changes.
00:07:45.360 --> 00:07:46.720
Yeah, I hope.
00:07:47.040 --> 00:07:48.240
Hopefully empowering teams as well.
00:07:49.120 --> 00:07:50.000
We want to carry on, yeah.
00:07:50.240 --> 00:07:55.199
We're supporting them as with whatever they want to to do next, you know.
00:07:55.439 --> 00:07:59.360
I mean, yeah, we'll we'll just keep learning more, won't we?
00:07:59.839 --> 00:08:00.160
Absolutely.
00:08:00.480 --> 00:08:15.680
Yeah, but empowerment, I think, and and I think I can't imagine how how demoralized people would get working in in those settings where they are you know up against it all the time.
00:08:15.920 --> 00:08:27.360
I I was really struck um by how inspiring people were because they're working up against it and it could be quite demoralizing.
00:08:27.600 --> 00:08:46.080
You know, you can't get the piece of equipment you want, you know, you haven't got fees, or you want mobile fees, you could you have to do it in the clinic and you're stuck with that, or you've got to see 15 patients in a video phrosopy clinic in the morning, and yeah, you know, the the it it's a never-ending barrage of patients, isn't it?
00:08:46.320 --> 00:09:06.559
And you'd think it would get them down, yeah, but they were so positive, yeah, and so inspired, inspiring to me, yeah, but you know, they they just sort of get on with it and um and uh and and are making a difference to people's lives, and it you know, I find I found that inspiring personally.
00:09:06.799 --> 00:09:09.039
Yeah, no, I totally echo that, yeah.
00:09:09.200 --> 00:09:09.440
Yeah.
00:09:09.679 --> 00:09:18.480
So we've been in India for about 10 days, sadly, in about half an hour, we're off to the airport to go home, which will be um we've had our last curry.
00:09:18.639 --> 00:09:21.759
We have had our last curry, the last of probably about 30.
00:09:22.320 --> 00:09:22.799
Many.
00:09:24.240 --> 00:09:28.399
What will you take away from this trip, do you think, outside of the hospital stuff?
00:09:28.799 --> 00:09:33.600
I mean, a lot of the hospital staff have been with us for meals, and then we've been really well looked after, haven't we?
00:09:33.759 --> 00:09:36.080
But come on, give me some memories of of India.
00:09:36.320 --> 00:09:38.080
Well, this morning was fun, wasn't it?
00:09:38.879 --> 00:09:44.080
We uh we had um I think this is pretty much today has been our only day off, hasn't it?
00:09:44.240 --> 00:09:49.200
And uh we decided to go and uh to the market in um in the auto rickshaw.
00:09:49.279 --> 00:09:53.120
And the traffic of Bangalore is legendary, yeah, is it not?
00:09:53.360 --> 00:09:54.000
Yeah, it is, yeah.
00:09:54.080 --> 00:09:59.759
Um we thought Mumbai was busy, but the roads here, it's like all of Mumbai is on Bangalore's roads, isn't it?
00:10:00.240 --> 00:10:06.879
It's dodgems and it's noisy and it's like yeah, that that that's but to me I I find that fun.
00:10:07.039 --> 00:10:07.360
Yeah.
00:10:07.679 --> 00:10:10.080
Um probably wouldn't want to do it every day.
00:10:11.360 --> 00:10:22.240
But I just think Indian hospitality, yeah, of everyone you meet, um, and yeah, I'm just I'm just uh need time to process what we've seen in the hospitals.
00:10:22.559 --> 00:10:28.960
There's there's the scale of what the scale of the numbers of patients is still hard to grapple with, isn't it?
00:10:29.279 --> 00:10:29.759
I think.
00:10:30.000 --> 00:10:50.879
And just when you when I think back to Withenshore and you walk down a corridor and it's you know there are people, but yeah, not on the you know, literally no floor space everywhere, and people queuing up out, as you say, overspilling into the stairwells and sitting there and all day waiting to be seen for 15 minutes.
00:10:51.440 --> 00:11:07.279
Waiting really patiently, and waiting very patiently and quietly, and you know, it's just incredible, and um the the staff are working so very hard, and their work, yeah, their work ethic is is very admirable.
00:11:07.679 --> 00:11:12.080
Um, so yeah, I've learned I think that we can take some lessons from that, can't we?
00:11:12.480 --> 00:11:12.960
Absolutely, yeah.
00:11:13.039 --> 00:11:15.039
No, I've learned a lot, I've seen a lot.
00:11:15.200 --> 00:11:29.200
I think uh I probably need to just have a a day or two just chilling at home just to uh transition back from the the pace of what we've seen here, both in the hospitals, in the communities, and then just India itself.
00:11:29.279 --> 00:11:31.679
It's uh it's full on, it's a fascinating place.
00:11:32.240 --> 00:11:33.120
Sensory overload.
00:11:33.279 --> 00:11:35.840
Yeah, it is sensory overload, but in in a good way.
00:11:36.000 --> 00:11:37.360
In an exciting way, yeah.
00:11:37.440 --> 00:11:44.320
I mean I'm I kind of I find it I find it exhilarating, but probably not if I did it every day.
00:11:45.919 --> 00:11:46.399
Fantastic.
00:11:46.559 --> 00:11:48.960
Alright, well, Sarah, always a pleasure to talk to you.
00:11:49.120 --> 00:11:51.039
Thank you so much for your insights.
00:11:51.440 --> 00:11:52.240
Yeah, cool.
00:11:52.480 --> 00:11:54.559
So uh that's it for this episode.
00:11:54.639 --> 00:12:03.120
Uh, as ever, the opinions you just heard are our own opinions, they don't necessarily reflect the opinions of the organizations uh which pay our wages.
00:12:03.279 --> 00:12:08.320
Uh, you can find out lots more on our website, uh, you can follow us on our social media channels.
00:12:08.480 --> 00:12:10.960
Um, thanks for listening and see you next time.
00:12:11.200 --> 00:12:11.440
Bye.
00:00:08.560 --> 00:00:12.880
Hello and welcome to this special episode of Tracky Talk.
00:00:13.039 --> 00:00:26.480
We're here in Bengaluru in the south part of India and I'm joined by Professor Sarah Wallace, OBE, who's a legendary speech and language pathologist that I'm sure many of you know.
00:00:26.800 --> 00:00:34.240
We're currently in the Holiday Inn near the race course in Bengaluru and we're very grateful to the staff for finding us this nice quiet space.
00:00:34.399 --> 00:00:48.719
We've got a bit of time to kill before we have to head home, so we thought it'd be a really good idea to spend a bit of time just reflecting on what we have observed and learnt, and some of the people that we've met and some of the things that we've seen in India.
00:00:48.880 --> 00:00:51.039
So I hope you find that useful.
00:00:56.399 --> 00:01:06.560
Lots of the research about tracheostomy care and changes and this multidisciplinary, multi-professional approach has come from University Commons, the West, hasn't it?
00:01:06.640 --> 00:01:06.719
Yeah.
00:01:06.959 --> 00:01:12.239
And obviously Australia have been strong players in the Global Tracheostomy Collaborative as well.
00:01:12.799 --> 00:01:21.120
And as you quite rightly say, it we need some data from this part of the world to reflect the challenges and the way that they manage things here.
00:01:21.519 --> 00:01:23.040
And they're different, they have different diseases.
00:01:23.200 --> 00:01:23.840
Yeah, different pathologies.
00:01:30.239 --> 00:01:39.439
They've got TB, lots of TB here, and other diseases that are uh pre more prevalent than than us, so different types of trachiosomy cohorts.
00:01:39.599 --> 00:01:39.760
Yeah.
00:01:40.079 --> 00:01:44.799
And at the head net cancers that we saw, as as you said, I mean that there's a lot of tobacco chewing.
00:01:44.959 --> 00:01:45.280
Yes.
00:01:45.519 --> 00:01:49.040
Which which I I sort of was aware of, but not aware of the scale of it.
00:01:49.280 --> 00:01:59.519
And uh, you know, some of the people met in the outpatient clinic were presented with pretty significant tumours, they'd sort of been ignoring them, they probably knew what it was, didn't want to see couldn't afford to.
00:02:04.079 --> 00:02:05.920
So very different populations.
00:02:06.319 --> 00:02:13.840
And uh, I mean, trying to get some data uh from this part of the world would be amazing, and it was great that all these hospitals that we visited.
00:02:14.159 --> 00:02:20.479
We talked a lot about the global trackers to be collaborative and and that way of trying to improve care through data.
00:02:20.560 --> 00:02:27.759
I mean, that that's how you know where you are, that's how you know where you're going, and that's how you know whether you're as good or different to other hospitals.
00:02:27.840 --> 00:02:34.319
And when you know that, you can then ask the hospital, okay, so what are you doing that I'm not, or the other hospitals say, Well, you're you're doing that really well.
00:02:34.560 --> 00:02:36.639
Can we take some information from you?
00:02:36.960 --> 00:03:05.039
Yeah, and I think I think we talked about the global south, didn't we, and how this it would be amazing if we could have that sort of um data to show you know what are the what are the future directions that people need to go in, and you know, they're already collaborating and they're already kind of recognising the you know many of the problems that patients with tracheostomies have, but you know, it's it's how do they use things like AI?
00:03:05.199 --> 00:03:08.639
Yeah, we went to that amazing art park as well, didn't we?
00:03:08.719 --> 00:03:09.840
Go on and tell them about that.
00:03:10.080 --> 00:03:23.120
So the art park is a centre for AI and and robotics, and uh it's like an innovation space, lots of work around AI applied to lots of different sectors, and and a relatively small chunk of their work was was in healthcare.
00:03:23.199 --> 00:03:27.840
But when we say that, when they told us about what they were doing, it's actually huge.
00:03:28.000 --> 00:03:51.280
Um, a lot of work in Covid, but what they've been able to demonstrate is they can access data sets, they're trying to get standardized data sets for certain things because there's lots of different pockets of data around India, but but there are some commonalities, and they were trying to piece things together and and then I mean it was predictive models we were talking about, in particular about uh dengue fever and sort of predicting outbreaks, things like that.
00:03:51.360 --> 00:04:17.680
But um, we we were then we were talking at St John's about they've got a real strong focus on uh AI in their research, and and the GTC database now has 20,000 uh cases in there with patients with tracheostomies, and that's right for applying these sort of artificially intelligent systems too to see if we can start to predict uh some of the some of the outcomes maybe or or predict which patients will benefit from certain things.
00:04:17.839 --> 00:04:32.879
Uh, but again, like you said, Sarah, and having sort of India or global south specific data in there, you know, will really help because you can't apply what we're up to in uh the north of England to what's happening in the south of India.
00:04:33.040 --> 00:04:35.360
But the you know the principles certainly were there.
00:04:35.519 --> 00:04:54.959
And I mean what I'll take away from this is you know the next steps is definitely collaboration, um, a lot of shared learning, and we were very clear to say to the guys, look, we're not here to tell you what to do, we're here to learn from what you're doing, and we're here to explain what we've picked up from working with and talking to lots of other people around the world.
00:04:55.040 --> 00:05:09.680
And that shared learning, you know, was was clearly very strong, and then that focus on you know research in this setting, collecting some data and really trying to understand what's going on now and how we can make some tweaks and see whether we can make any improvements.
00:05:10.480 --> 00:05:18.800
I wondered what your reflections were on you know the sort of the next steps perhaps for the for the speech and language therapy teams that you've met here.
00:05:19.120 --> 00:05:23.759
I think it's really exciting because I think um there was so much enthusiasm, wasn't there?
00:05:23.839 --> 00:05:31.680
Yeah, there's been so much enthusiasm everywhere we've gone for learning and for um pushing quality of care.
00:05:32.480 --> 00:05:35.199
Lots and lots of conversations about quality of care.
00:05:35.439 --> 00:05:42.240
But like you say at the moment, I think there's a just uh it's all a little bit of an unknown uh entity, isn't it?
00:05:42.319 --> 00:05:46.000
Around what is happening to patients, especially after hospital, yeah.
00:05:46.240 --> 00:05:52.959
Um, but even in the hospital, because many of them are not getting seen early enough or at all.
00:05:53.120 --> 00:06:13.759
Yeah, um, so I feel like um apart from the fact that we've built friendships and collaborations with people, I felt like in at Tata Memorial, that opportunity to get 250 people from all over India in one space, they were networking with each other as well.
00:06:14.000 --> 00:06:15.120
Yeah, it was really nice to see that.
00:06:15.439 --> 00:06:25.600
That was great to see because especially when so I did two presentations um jointly with, I'm gonna give a shout-out to Arun um Arun Balaji.
00:06:26.959 --> 00:06:59.600
Who is um the head of the speech therapy department in Tata, who has helped facilitate this whole thing, um, and he is he is incredible, but you know, I invited him to do presentations jointly because I can't give the Indian perspective, I can tell what we you know promote in terms of quality of care and communication and swallow, and he could then say, Um, you know, so this is how we translate this to India, and um and there was a you know a lot of people in the audience who were able to, we had a lot of panel discussions, didn't we?
00:06:59.680 --> 00:07:21.680
So there was some really what I took away most was the conversations we had in those panel discussions where people shared their setting, their challenges, but also lots of people saying, Oh, you know, I'm I'm working, I don't know, in um another part of India, you know, in Rajasthan or whatever, and you know, I I can I've actually got this, and other people saying, Oh, how did you get it?
00:07:21.759 --> 00:07:25.199
You know, how did you get that speaking variable because we can't get them?
00:07:25.279 --> 00:07:30.000
And so that I think it facilitated things to happen within India, I hope.
00:07:30.160 --> 00:07:45.279
Yeah, and you know, the support of of all of the leadership teams in these organizations has been incredible, and I think they really, really want, I feel like we've we've facilitated hopefully some some changes.
00:07:45.360 --> 00:07:46.720
Yeah, I hope.
00:07:47.040 --> 00:07:48.240
Hopefully empowering teams as well.
00:07:49.120 --> 00:07:50.000
We want to carry on, yeah.
00:07:50.240 --> 00:07:55.199
We're supporting them as with whatever they want to to do next, you know.
00:07:55.439 --> 00:07:59.360
I mean, yeah, we'll we'll just keep learning more, won't we?
00:07:59.839 --> 00:08:00.160
Absolutely.
00:08:00.480 --> 00:08:15.680
Yeah, but empowerment, I think, and and I think I can't imagine how how demoralized people would get working in in those settings where they are you know up against it all the time.
00:08:15.920 --> 00:08:27.360
I I was really struck um by how inspiring people were because they're working up against it and it could be quite demoralizing.
00:08:27.600 --> 00:08:46.080
You know, you can't get the piece of equipment you want, you know, you haven't got fees, or you want mobile fees, you could you have to do it in the clinic and you're stuck with that, or you've got to see 15 patients in a video phrosopy clinic in the morning, and yeah, you know, the the it it's a never-ending barrage of patients, isn't it?
00:08:46.320 --> 00:09:06.559
And you'd think it would get them down, yeah, but they were so positive, yeah, and so inspired, inspiring to me, yeah, but you know, they they just sort of get on with it and um and uh and and are making a difference to people's lives, and it you know, I find I found that inspiring personally.
00:09:06.799 --> 00:09:09.039
Yeah, no, I totally echo that, yeah.
00:09:09.200 --> 00:09:09.440
Yeah.
00:09:09.679 --> 00:09:18.480
So we've been in India for about 10 days, sadly, in about half an hour, we're off to the airport to go home, which will be um we've had our last curry.
00:09:18.639 --> 00:09:21.759
We have had our last curry, the last of probably about 30.
00:09:22.320 --> 00:09:22.799
Many.
00:09:24.240 --> 00:09:28.399
What will you take away from this trip, do you think, outside of the hospital stuff?
00:09:28.799 --> 00:09:33.600
I mean, a lot of the hospital staff have been with us for meals, and then we've been really well looked after, haven't we?
00:09:33.759 --> 00:09:36.080
But come on, give me some memories of of India.
00:09:36.320 --> 00:09:38.080
Well, this morning was fun, wasn't it?
00:09:38.879 --> 00:09:44.080
We uh we had um I think this is pretty much today has been our only day off, hasn't it?
00:09:44.240 --> 00:09:49.200
And uh we decided to go and uh to the market in um in the auto rickshaw.
00:09:49.279 --> 00:09:53.120
And the traffic of Bangalore is legendary, yeah, is it not?
00:09:53.360 --> 00:09:54.000
Yeah, it is, yeah.
00:09:54.080 --> 00:09:59.759
Um we thought Mumbai was busy, but the roads here, it's like all of Mumbai is on Bangalore's roads, isn't it?
00:10:00.240 --> 00:10:06.879
It's dodgems and it's noisy and it's like yeah, that that that's but to me I I find that fun.
00:10:07.039 --> 00:10:07.360
Yeah.
00:10:07.679 --> 00:10:10.080
Um probably wouldn't want to do it every day.
00:10:11.360 --> 00:10:22.240
But I just think Indian hospitality, yeah, of everyone you meet, um, and yeah, I'm just I'm just uh need time to process what we've seen in the hospitals.
00:10:22.559 --> 00:10:28.960
There's there's the scale of what the scale of the numbers of patients is still hard to grapple with, isn't it?
00:10:29.279 --> 00:10:29.759
I think.
00:10:30.000 --> 00:10:50.879
And just when you when I think back to Withenshore and you walk down a corridor and it's you know there are people, but yeah, not on the you know, literally no floor space everywhere, and people queuing up out, as you say, overspilling into the stairwells and sitting there and all day waiting to be seen for 15 minutes.
00:10:51.440 --> 00:11:07.279
Waiting really patiently, and waiting very patiently and quietly, and you know, it's just incredible, and um the the staff are working so very hard, and their work, yeah, their work ethic is is very admirable.
00:11:07.679 --> 00:11:12.080
Um, so yeah, I've learned I think that we can take some lessons from that, can't we?
00:11:12.480 --> 00:11:12.960
Absolutely, yeah.
00:11:13.039 --> 00:11:15.039
No, I've learned a lot, I've seen a lot.
00:11:15.200 --> 00:11:29.200
I think uh I probably need to just have a a day or two just chilling at home just to uh transition back from the the pace of what we've seen here, both in the hospitals, in the communities, and then just India itself.
00:11:29.279 --> 00:11:31.679
It's uh it's full on, it's a fascinating place.
00:11:32.240 --> 00:11:33.120
Sensory overload.
00:11:33.279 --> 00:11:35.840
Yeah, it is sensory overload, but in in a good way.
00:11:36.000 --> 00:11:37.360
In an exciting way, yeah.
00:11:37.440 --> 00:11:44.320
I mean I'm I kind of I find it I find it exhilarating, but probably not if I did it every day.
00:11:45.919 --> 00:11:46.399
Fantastic.
00:11:46.559 --> 00:11:48.960
Alright, well, Sarah, always a pleasure to talk to you.
00:11:49.120 --> 00:11:51.039
Thank you so much for your insights.
00:11:51.440 --> 00:11:52.240
Yeah, cool.
00:11:52.480 --> 00:11:54.559
So uh that's it for this episode.
00:11:54.639 --> 00:12:03.120
Uh, as ever, the opinions you just heard are our own opinions, they don't necessarily reflect the opinions of the organizations uh which pay our wages.
00:12:03.279 --> 00:12:08.320
Uh, you can find out lots more on our website, uh, you can follow us on our social media channels.
00:12:08.480 --> 00:12:10.960
Um, thanks for listening and see you next time.
00:12:11.200 --> 00:12:11.440
Bye.
