Don’t see player?
LISTEN HERE
TRANSCRIPT
Rick Harp: Welcome to Infectious Questions, a public health podcast from the National Collaborating Centre for Infectious Diseases. I’m Rick Harp. Once again, we’re talking tuberculosis with NCCID’s Shivoan Balakumar. Hey, Shivoan.
Shivoan Balakumar: Greetings, Rick.
Harp: Now, Shivoan, the conversation you’re about to share is another example of a connection you made at End TB 2017, a meeting of the North American region of the International Union Against Tuberculosis. Who is this episode’s “TB Talk” guest?
Balakumar: Dennis Falzon is a Medical Officer with the Stop TB department at the World Health Organization in Geneva. We met briefly in Vancouver at End TB 2017, where we agreed to reconnect once he got back to Switzerland.
And that conversation began with him outlining the rationale for the WHO’s End TB strategy.
Falzon: The End TB strategy is a joint WHO and partners’ agreement on the way forward to reduce TB globally to levels which are now only seen in developed countries. And, to achieve that in the space of 20 years after 2015, we need to employ a lot of different tools and a lot of new ones, and new ways of doing things which we have been doing up to now.
So this is where digital technologies—which is basically the technologies that we know about in eHealth or mHealth, using mobiles or using electronic methods a bit more efficiently—could help out in different aspects of the efforts that people and programs and donor institutions are putting in place to try and curb the global threat of tuberculosis in the world.
Just to remind the listeners that tuberculosis today still causes an estimated 10.4 million new TB cases every year. We have close to 600,000 cases every year emerging with drug-resistant forms of tuberculosis which are very difficult to treat and which are still transmissible. They can spread through other people and they do spread.
So, all efforts that can be put in place to prevent the disease from spreading further and from causing avoidable death would be worth entertaining, and this is the interest in the last few years that WHO is having on these rapidly advancing technologies which can assist in a number of different ways.
Balakumar: Again, that’s Dr. Dennis Falzon with the Stop TB department at the WHO in Geneva. My next question for Dr. Falzon sought his thoughts on the state of evidence regarding the monitoring of tuberculosis therapy through such new technologies as text messaging (also known as SMS), VOT (or video observed therapy) and electronic medication monitors.
Falzon: Let me maybe recap a little bit about these three types of interventions.
First of all, they are technologies which are easily available in both rich and poor settings, right. These are—at least the SMS and the video observed therapy (the VOT or VDOT)—are technologies which are feasible even with your standard smartphone and even for SMS you can have it on any form of phone.
As a result of this, they are more likely to be used, and to be used at large scale, right. And this has stimulated a number of workers to mount studies upon these. So they have … I think there are randomized control trials now for all of these three technologies.
So the randomized trials for SMS have more or less up to now given negative findings for SMS when used as a simple reminder. So you send an SMS every morning to a patient to tell them ‘Take your TB medicines.’ That does not seem to be very productive in that it does not increase your chances of having a cure. Now, one of the reasons maybe is that the treatment of tuberculosis is long. Okay, it’s at least six months in its simplest form so we can imagine that if you receive an SMS everyday it starts to run out of novelty after a few weeks. So the likelihood is that the SMS will not be effective in the long run.
That sort of finding is stimulating people to look a bit more closely at what SMS can do apart from, let’s say, sending a one direction kind of message to your patient. They’re exploring more about this bidirectionality of a two-way function that SMS can work, so it can combine, let’s say, sending an SMS to the patient and asking them to phone you up or to send you an SMS, and that has been shown to be more effective, at least in patients who are having antiretrovirals or other drugs. That the bidirectionality of SMS is something which is worth exploring in future. So that’s, maybe in a nutshell, about SMS.
With regards to video observed therapy, there have been some, a couple of observation studies done in the US and Australia, looking at this in the last few years. They have not come up with significant changes in the likelihood or the chances that you improve your outcomes, but when you think about replacing hospital or visits to the clinics by a patient, right, who has to commute everyday to see the nurse—if you can replace that, even not throughout the treatment, but for some period of your treatment, if you can replace that with a virtual discussion, right, where the health care worker can visualize the patient taking the medication and can interact, okay, because sometimes you can interact directly on the video or else send a video which is pre-recorded. There are two ways of doing that. This allows at least the patient some flexibility on not having to visit the clinic everyday with all the associated troubles that they have to go through and exertion, and the possible disclosure of their identity, and so on and so forth.
So there is benefits: if you say that video observed therapy is as good as direct in-person observation or treatment, there’s already a gain to be made over there. There are randomized control trials which have been done, or which are in process, for video observed therapy and one of them has been completed and the outcomes of that trial should be published soon. So that’s about video observed therapy.
In terms of the electronic monitors, there is some evidence—not from trials—which show that they can work, okay, at least from one setting. There is also a big randomized control trial in China which shows that their contribution to improve use of the drugs is there, however, in terms of changes in the final outcomes, it was not shown and I think they’re going to mount another study to see, to explore whether that effect is really there.
Balakumar: My final question for the WHO’s Falzon focused on best practices and new technology. Does the rapidly changing nature of the one make it hard to produce relevant versions of the other?
Falzon: I think the best practices are very helpful because they give you inputs and insights into the implementation which you don’t always get from a randomized trial which has been run under particular controls—conditions which are not always easy to replicate under normal routine conditions.
So I think best practices have been written up already on a number of things. So for instance, if you are talking about the implementation of an electronic system to handle better the data for patients, then you can read it up about in India or in China, or in many other places these have been written up. And I think presenting the experience with these systems, both the upside and downside and the problems, is very helpful for the prospective implementer.
A number of these technologies, the way that they are applied, are not easy to study in the sense that many things are changing at the same time that these are being implemented. And sometimes the whole notion of how we think about things may change and, for instance, the whole concept of precision medicine which is coming in, as well as, let’s say, the concepts of artificial intelligence and machine learning—these are really expected to revolutionize certain aspects of health care if not most, I would dare say, because they could replace a number of things in which the human element has up to now predominated.
So, for instance, when you are thinking about machines which can improve and which can recognize patterns in a much more refined way than the human eye, then aspects of medicine which are heavily dependent upon a professional or expert recognizing a particular pathology, such as an abnormality in an x-ray, or in a microscopy slide, or on the skin of a patient, those can be now starting to be sort of replaced by machines, and machines which learn as well. So when they make mistakes, those mistakes are fed in to improve your next interpretation.
So, these things are going to change the way we practice medicine and we approach patient care in a much sort of revolutionary manner than, let’s say, having more effective databases, right, or more effective way of e-learning. So it’s really sort of changing the goalposts of clinical practice and public health care.
Balakumar: Some promising closing thoughts there from Dr. Dennis Falzon with the Stop TB department at the WHO in Geneva.
Harp: Appreciate this, Shivoan.
Balakumar: You’re welcome. And as you know, Rick, the questions we asked this episode were based on those submitted to us by public health practitioners. So thanks to them for sharing as well.
Harp: And thanks for listening to Infectious Questions, a production of the National Collaborating Centre for Infectious Diseases.
Production of this podcast has been made possible through a financial contribution from the Public Health Agency of Canada. Note that the views expressed here do not necessarily represent those of the Agency.
The host organization of the NCCID is the University of Manitoba. Learn more at nccid.ca.