1 00:00:00,040 --> 00:00:03,120 Speaker 1: Funny SIXFM as we watch the Tumbland Dice of Life 2 00:00:03,960 --> 00:00:06,360 Speaker 1: roll in front of us. So if in fact, right 3 00:00:06,400 --> 00:00:08,160 Speaker 1: now Lisa is one person we could talk to. We 4 00:00:08,200 --> 00:00:10,639 Speaker 1: came up with a name with so much, so many 5 00:00:10,680 --> 00:00:12,720 Speaker 1: questions to be asked and so much curiosity, and it 6 00:00:12,800 --> 00:00:16,400 Speaker 1: is the wa AMA president almost a year in the job. 7 00:00:16,440 --> 00:00:18,280 Speaker 1: I believe it was June of last year. Doctor Mark 8 00:00:18,320 --> 00:00:19,959 Speaker 1: Duncan Smith's online Morning. 9 00:00:19,720 --> 00:00:22,680 Speaker 2: Doty, Good morning, Morning, good morning. 10 00:00:22,920 --> 00:00:24,360 Speaker 3: We've got a couple of things we want to talk 11 00:00:24,360 --> 00:00:29,560 Speaker 3: to you about today. First of all, these rats the tests. 12 00:00:29,840 --> 00:00:33,279 Speaker 3: I have been hearing a lot of chatter about the 13 00:00:33,320 --> 00:00:35,960 Speaker 3: government issued saliva ones, the ones they sort of refer 14 00:00:36,000 --> 00:00:38,000 Speaker 3: to as the lollipop ones where you swipe it around 15 00:00:38,040 --> 00:00:39,800 Speaker 3: the inside of your mouth and pop it into the test. 16 00:00:40,080 --> 00:00:43,919 Speaker 3: A lot of people are saying that they're finding those ineffective, 17 00:00:44,280 --> 00:00:46,919 Speaker 3: Like they're doing one of those that's coming up negative 18 00:00:47,000 --> 00:00:49,479 Speaker 3: and then they're doing a up the nose one and 19 00:00:49,520 --> 00:00:52,240 Speaker 3: it's lighting up like a Christmas tree. Have you heard 20 00:00:52,360 --> 00:00:55,480 Speaker 3: anything along these lines? And is it user error? 21 00:00:55,880 --> 00:00:59,880 Speaker 2: Are we doing it wrong? Look any tests as false positives, 22 00:01:00,120 --> 00:01:01,880 Speaker 2: false negatives, And when you need to talk about a test, 23 00:01:01,880 --> 00:01:06,759 Speaker 2: you've got to talk in terms of sensitivity specificity, positive 24 00:01:06,760 --> 00:01:09,720 Speaker 2: predicted value, negative predicted value to really evaluate a test, 25 00:01:09,760 --> 00:01:12,319 Speaker 2: but to really get around all that because it took 26 00:01:12,319 --> 00:01:15,440 Speaker 2: me ages to understand it myself. Look, rats are not 27 00:01:15,520 --> 00:01:17,960 Speaker 2: as accurate as PCR. Rats are sort of, if you 28 00:01:18,000 --> 00:01:20,160 Speaker 2: want to talk in very general terms, sort of eighty 29 00:01:20,200 --> 00:01:24,640 Speaker 2: to ninety percent accurate, whereas rat appeal about ninety ninety 30 00:01:24,720 --> 00:01:27,520 Speaker 2: eight percent accurate. Plus you've got to look at the 31 00:01:27,560 --> 00:01:30,680 Speaker 2: actual setting. The advantage of rats is that they can 32 00:01:30,720 --> 00:01:33,959 Speaker 2: be rolled out to the compute community, a community community, 33 00:01:34,000 --> 00:01:36,760 Speaker 2: person or people can just do it themselves and the 34 00:01:36,800 --> 00:01:39,760 Speaker 2: results there in fifteen minutes, as opposed to a PCR 35 00:01:39,920 --> 00:01:43,120 Speaker 2: that has to have a professional do this well, but 36 00:01:43,200 --> 00:01:46,920 Speaker 2: has to have a healthcare professional duty analysis takes hours, 37 00:01:47,720 --> 00:01:52,120 Speaker 2: needs specific laboratory, so there's not scalability in a PCR test. 38 00:01:52,120 --> 00:01:55,440 Speaker 2: So both tests have their place. Now, Yes, I haven't 39 00:01:55,440 --> 00:01:58,440 Speaker 2: heard anything specific about certain types of tests, but all 40 00:01:58,520 --> 00:02:01,400 Speaker 2: tests are meant to be TGA, so they should reach 41 00:02:01,440 --> 00:02:04,240 Speaker 2: certain parameters. Yeah, a lot of situations where you get 42 00:02:04,240 --> 00:02:08,440 Speaker 2: a false negative may be that the sample sampling area. 43 00:02:08,480 --> 00:02:10,520 Speaker 2: As you say, I mean, ultimately, if you take the 44 00:02:10,600 --> 00:02:12,880 Speaker 2: RAT and stick it in your armpit, then you're not 45 00:02:12,960 --> 00:02:16,160 Speaker 2: going to get a good result. But you certainly need 46 00:02:16,200 --> 00:02:18,480 Speaker 2: to read the instructions very very very carefully, and. 47 00:02:20,160 --> 00:02:22,519 Speaker 3: I do feel it's a little there's a little element 48 00:02:22,560 --> 00:02:25,280 Speaker 3: of mickey mouse about it in terms of we're not nurses, 49 00:02:25,360 --> 00:02:26,880 Speaker 3: we're not doctors, and it all of a sudden we're 50 00:02:26,919 --> 00:02:29,040 Speaker 3: doing all our own testing and things, and that the 51 00:02:29,120 --> 00:02:32,120 Speaker 3: instructions could be a little clearer. I think they're fairly 52 00:02:32,200 --> 00:02:35,840 Speaker 3: loose when you've got so bright. 53 00:02:38,720 --> 00:02:41,080 Speaker 2: When you've got a mass outbreak and a pandemic like this. 54 00:02:41,200 --> 00:02:44,560 Speaker 2: Though the benefit of the RAT is a screening tool 55 00:02:45,440 --> 00:02:48,000 Speaker 2: and it is scalable, so so you know you've got 56 00:02:48,320 --> 00:02:50,920 Speaker 2: you know, thousand and tens of thousands, hundreds of thousands 57 00:02:50,880 --> 00:02:53,240 Speaker 2: of people out there having a RAT, whereas the PCR 58 00:02:53,320 --> 00:02:55,800 Speaker 2: system can't handle that. You're also going to take it 59 00:02:55,840 --> 00:02:58,600 Speaker 2: in context. If you're a close contact with someone and 60 00:02:58,639 --> 00:03:00,600 Speaker 2: you've got a couple of sniffles and you're getting a 61 00:03:00,600 --> 00:03:03,680 Speaker 2: negative RAP, well you probably should be assuming that you're 62 00:03:03,680 --> 00:03:05,120 Speaker 2: positive and go out and get a PCR. 63 00:03:06,240 --> 00:03:10,400 Speaker 1: Just beense he's been worried for you. If you're positive enough, 64 00:03:10,520 --> 00:03:11,600 Speaker 1: sticking it under your armpit. 65 00:03:11,720 --> 00:03:16,080 Speaker 2: But it's a pretty dirty armpit. 66 00:03:16,280 --> 00:03:19,440 Speaker 1: Yeah, okay, Mark, with what's going on? Mark masks, So 67 00:03:19,520 --> 00:03:21,440 Speaker 1: we put them back on everywhere, not just in hospitals. 68 00:03:21,480 --> 00:03:22,880 Speaker 1: What do you think I've. 69 00:03:22,680 --> 00:03:25,920 Speaker 2: Not taken mine off, continued, I've continued to wear mine 70 00:03:26,000 --> 00:03:30,520 Speaker 2: indoors as per the previous restrictions. I think it is 71 00:03:30,639 --> 00:03:34,480 Speaker 2: absolutely crazy that we're not wearing them now. A week 72 00:03:34,520 --> 00:03:36,760 Speaker 2: and a half ago is when the premiere took off 73 00:03:36,800 --> 00:03:40,200 Speaker 2: the masks stopped the mandate. It takes about a week 74 00:03:40,200 --> 00:03:42,720 Speaker 2: before a public health measure either has effect or its 75 00:03:42,760 --> 00:03:47,640 Speaker 2: effect is seen, and almost almost the day with massive upswing. 76 00:03:48,480 --> 00:03:51,600 Speaker 2: This was predictable. The restrictions were reduced when we were 77 00:03:51,600 --> 00:03:54,080 Speaker 2: in a plateau phase, and if anything, the plateau phase 78 00:03:54,120 --> 00:03:56,760 Speaker 2: had a very slight incline as you have a look 79 00:03:56,760 --> 00:03:59,480 Speaker 2: at the rolling seven day average. We all heard about, 80 00:03:59,680 --> 00:04:01,560 Speaker 2: you know, flatten the curve. That's why we need to 81 00:04:01,560 --> 00:04:04,120 Speaker 2: do all these things in the early days. Well, what 82 00:04:04,160 --> 00:04:06,680 Speaker 2: happens when you do something and reduce a measure that 83 00:04:06,760 --> 00:04:10,800 Speaker 2: is flattening the curve or the line, is when you're 84 00:04:10,840 --> 00:04:13,400 Speaker 2: on a plateau phase, well it goes up. And that's 85 00:04:13,680 --> 00:04:16,000 Speaker 2: that's what we've seen now. Now the scary thing from 86 00:04:16,000 --> 00:04:19,680 Speaker 2: My point of view is as night follows day, hospitalizations 87 00:04:19,760 --> 00:04:23,640 Speaker 2: follow new cases. So in the next week. I mean, 88 00:04:23,640 --> 00:04:25,839 Speaker 2: it's a horrible day today as a storm out there, 89 00:04:26,120 --> 00:04:28,040 Speaker 2: but this isn't This isn't the only storm we're going 90 00:04:28,080 --> 00:04:29,000 Speaker 2: to get in the next week. 91 00:04:29,520 --> 00:04:34,039 Speaker 3: Yeah, forty percent increase is fairly significant. And should we 92 00:04:34,160 --> 00:04:37,679 Speaker 3: be particularly concerned with heading into winter? Is that a factor? 93 00:04:38,520 --> 00:04:45,760 Speaker 2: Absolutely? Winter is coming. Y, thank you, thank you, thank you. 94 00:04:47,839 --> 00:04:49,960 Speaker 2: We do need to be worried about that. Now, what 95 00:04:50,040 --> 00:04:53,680 Speaker 2: I'm worried about with hospitalizations isn't the hospitalizations today, it's 96 00:04:53,680 --> 00:04:56,360 Speaker 2: the hospitalizations in a week now from now, which is 97 00:04:56,360 --> 00:04:59,559 Speaker 2: where we're going to see that seventeen thousand cases now. Also, 98 00:05:00,160 --> 00:05:03,599 Speaker 2: rolling three day average is way up now at thirteen 99 00:05:03,640 --> 00:05:06,440 Speaker 2: thousand day cases a day, So this is not a 100 00:05:06,440 --> 00:05:09,200 Speaker 2: one off number. This is a real increase that we're 101 00:05:09,240 --> 00:05:11,560 Speaker 2: actually seeing. Now. We'll see a dip over the weekend 102 00:05:11,560 --> 00:05:14,360 Speaker 2: as we normally do, and then you know, hopefully we'll 103 00:05:14,360 --> 00:05:16,359 Speaker 2: get back into a plateau next week, but we don't know, 104 00:05:16,440 --> 00:05:18,000 Speaker 2: and we'll just have to see where that goes. 105 00:05:18,200 --> 00:05:20,920 Speaker 1: Yeah, we've heard in the news throughout the morning your quotes, Mirk, 106 00:05:20,960 --> 00:05:23,000 Speaker 1: and you're pleading to the premium. But does a premier 107 00:05:23,000 --> 00:05:24,520 Speaker 1: listen to you? Do you have a meeting with him? 108 00:05:24,520 --> 00:05:25,239 Speaker 1: What happens now? 109 00:05:26,320 --> 00:05:28,520 Speaker 2: No, I no, we don't have regular meetings or anything 110 00:05:28,600 --> 00:05:31,719 Speaker 2: like that. Look at I have a good relationship with 111 00:05:31,760 --> 00:05:35,560 Speaker 2: the Health Minister and we have I have regular meetings 112 00:05:35,600 --> 00:05:38,400 Speaker 2: with the Health Minister. But it is just a concern 113 00:05:38,480 --> 00:05:40,320 Speaker 2: of where we're heading. And as you say, with winter 114 00:05:40,360 --> 00:05:42,920 Speaker 2: coming with the flu season, but demand on beds, we're 115 00:05:42,960 --> 00:05:45,480 Speaker 2: already in a bad place. And my point about all 116 00:05:45,480 --> 00:05:47,720 Speaker 2: this is our medical system did not have a lot 117 00:05:47,720 --> 00:05:50,920 Speaker 2: of reserve when we started this pandemic, and we don't 118 00:05:50,960 --> 00:05:52,920 Speaker 2: have a lot of reserve now. People say, oh, there's 119 00:05:52,920 --> 00:05:55,880 Speaker 2: only ten people in ICU, Well, those ICUs are already 120 00:05:55,920 --> 00:05:59,960 Speaker 2: full from business as usual. So you know, elective search 121 00:06:00,200 --> 00:06:03,120 Speaker 2: was canceled at one of the public hospitals last week 122 00:06:03,200 --> 00:06:06,400 Speaker 2: because I see you as full. So it's I see 123 00:06:06,520 --> 00:06:08,240 Speaker 2: is not sitting there empty. They've got the full of 124 00:06:08,240 --> 00:06:09,160 Speaker 2: people already. 125 00:06:10,000 --> 00:06:12,880 Speaker 3: On another note, and this is something ambulance ramping is 126 00:06:12,920 --> 00:06:15,080 Speaker 3: something that's really it's not something that I've just heard 127 00:06:15,120 --> 00:06:16,719 Speaker 3: about in the last couple of years. It's gone on 128 00:06:16,760 --> 00:06:18,560 Speaker 3: for as long as I can remember, and there's been 129 00:06:18,560 --> 00:06:20,960 Speaker 3: a lot of talk about ambulances and ramping again recently, 130 00:06:20,960 --> 00:06:23,000 Speaker 3: and people being encouraged not to call for one or 131 00:06:23,040 --> 00:06:26,440 Speaker 3: less absolutely necessary, which seems obvious to me. But I mean, 132 00:06:26,520 --> 00:06:29,599 Speaker 3: I cannot believe some of the people that front to 133 00:06:29,640 --> 00:06:33,559 Speaker 3: the emergency department, let alone call an ambulance for things 134 00:06:33,600 --> 00:06:35,640 Speaker 3: that they really shouldn't be calling them for. When an 135 00:06:35,640 --> 00:06:39,279 Speaker 3: ambulance shows up to one of these cases, do they 136 00:06:39,720 --> 00:06:42,800 Speaker 3: are they within their rights to say, listen, you don't 137 00:06:42,839 --> 00:06:46,600 Speaker 3: need us call your doctor in the morning and you know, 138 00:06:47,279 --> 00:06:50,039 Speaker 3: or or do people have the right to demand that 139 00:06:50,080 --> 00:06:52,039 Speaker 3: they've be taken to hospital in the ambulance with their 140 00:06:52,120 --> 00:06:52,880 Speaker 3: stub toe. 141 00:06:53,440 --> 00:06:54,920 Speaker 2: I don't think they've got a right. I think that's 142 00:06:55,279 --> 00:06:58,440 Speaker 2: really a question for Saint John's. But if you really 143 00:06:58,480 --> 00:07:00,920 Speaker 2: look at that issue of the g P patients that 144 00:07:00,960 --> 00:07:03,720 Speaker 2: go to EDS, they're not they're not the patients that 145 00:07:04,120 --> 00:07:06,120 Speaker 2: the biggest problem because they get seen and they go home. 146 00:07:06,680 --> 00:07:09,080 Speaker 2: It's actually the patients, it's they're not the actual cause 147 00:07:09,120 --> 00:07:11,720 Speaker 2: of ramping. Ramping is caused by patients going to ED 148 00:07:11,840 --> 00:07:13,480 Speaker 2: that need to go into hospital and the hospital is 149 00:07:13,480 --> 00:07:16,600 Speaker 2: already full. So this is this is again a little 150 00:07:16,600 --> 00:07:18,800 Speaker 2: bit of a furfy in a little bit of a diversion. 151 00:07:20,400 --> 00:07:22,560 Speaker 2: I've said this before. The top three causes of ramping 152 00:07:23,160 --> 00:07:26,040 Speaker 2: lack of beds, lack of beds and lack of beds. 153 00:07:26,760 --> 00:07:28,960 Speaker 2: The mcgau and government over the last five years has 154 00:07:29,040 --> 00:07:32,320 Speaker 2: not invested in increasing the capacity of the medical system, 155 00:07:32,720 --> 00:07:36,000 Speaker 2: and ramping has increased from when they took over five 156 00:07:36,200 --> 00:07:38,800 Speaker 2: times on a steady increase. So it's not like this 157 00:07:38,880 --> 00:07:40,480 Speaker 2: is a big surprise in COVID all of a sudden 158 00:07:40,520 --> 00:07:42,920 Speaker 2: has gone smack and caused all this. This has been 159 00:07:43,200 --> 00:07:45,520 Speaker 2: this has been a under investment in the system over 160 00:07:45,560 --> 00:07:48,120 Speaker 2: five years by the McGowan government and now and now 161 00:07:48,160 --> 00:07:51,239 Speaker 2: we're reaping the rewards of that under investment, not rewards. 162 00:07:51,560 --> 00:07:54,520 Speaker 1: And it sounds like Domino's can cause it thing all 163 00:07:54,560 --> 00:07:55,200 Speaker 1: the way down the line. 164 00:07:55,200 --> 00:07:57,840 Speaker 2: They might. It's becoming a perfect storm. I'm afraid. 165 00:07:57,920 --> 00:08:00,520 Speaker 3: All right, well, I think we'll have to really are 166 00:08:00,560 --> 00:08:04,720 Speaker 3: out of time. Always absolutely fantastic to talk to you, 167 00:08:04,800 --> 00:08:05,920 Speaker 3: doctor Mark Duncan Smith. 168 00:08:06,240 --> 00:08:07,560 Speaker 2: Great, have a great day. Thank you. 169 00:08:07,840 --> 00:08:08,320 Speaker 1: Thanks mate.