Learning From pan-Canadian Health Data Strategy - What's Next to EHDS? (Eric Sutherland)

[00:00:00] Dear listeners, welcome to Faces of Digital Health, a podcast about digital health and how healthcare systems around the world adopt technology with me, Tjasa Zajc.

[00:00:15] The European Health Data Space is around the corner. The legislation is confirmed. How do we get to the next steps?

[00:00:23] Today you'll hear a discussion with Eric Sutherland, Senior Health Economist and Digital Health Lead at OSD, who worked on the pan-Canadian health data strategy before his current role.

[00:00:35] We discussed the upcoming implementation of the European Health Data Space, what needs to happen next in terms of defining data standards, how do we involve the public, encourage trust in data sharing and also build capacity for digital health implementation.

[00:00:53] We're moving into the era of new required data professionals, not just data analysts but also data controllers, data stewards and more.

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[00:01:29] Eric, hi and thank you so much for joining me for a discussion for Faces of Digital Health where we are going to talk about a little bit of digital health economics, healthcare indicators, development in the OSD countries

[00:02:00] and what you have found out so far as the digital health lead with the OSD. You actually have a very long history in the digital health space, you moved from Canada to Europe.

[00:02:15] You definitely have a lot of knowledge to share and I actually wanted to start with your history and your past work.

[00:02:21] So basically you worked on the pan-Canadian health data strategy before moving to Paris to join OSD and the reason I think this is important is because in Europe we're also now striving to create this European health data space.

[00:02:39] The legislation is out. Going back to Canada, what is the pan-Canadian health data strategy and how is it impacted by the fact that Canada is divided into two countries.

[00:02:51] Canada is divided into provinces and territories.

[00:02:54] Thank you. It was a frequent comment that I made when I was working on the pan-Canadian health data strategy. I looked at Europe and I would say we can't get our 10 provinces in three territories to work together on data collaborations.

[00:03:11] And then I look at Europe and at least they have one privacy act or data protection act with the GDPR. They have one approach around AI. They're moving towards one approach around a European health data space.

[00:03:23] So from a Canadian perspective we often looked at Europe with envy because realizing that many of the capabilities of cooperation were being driven through a European lens and activities and that wasn't as strong from a Canadian perspective.

[00:03:40] Having said that, by way of background at the beginning of the pandemic we worked out that we were from a Canadian perspective there were challenges in collecting data meaningfully to actually provide a coherent policy response to the pandemic.

[00:03:56] And because of that the policy makers recognized that we needed to have an overall approach to our health data.

[00:04:06] Literally we were at a point in Canada where we were using fax machines for communication between people who are collecting data, doing contact tracing and people who are counting the number of caseloads etc.

[00:04:17] In the 21st century relying upon fax machines seemed more than antiquated.

[00:04:22] There was a movement to create a pan-Canadian health data strategy an expert group was struck, which I was the secretary of four as well as bringing together the provincial and territorial thought leaders in digital health and really try to channel the information for the experts around what we should do and convey it directly to the policy leaders about what practically could actually be done.

[00:04:47] So having both of the theory and the practicality really bringing those together as quickly as we can.

[00:04:53] And fundamentally where we landed on it was on a few core principles.

[00:04:59] One is around data stewardship, the importance of ensuring timely access to quality data that there are harms from both the use of data and there are harms in the non-use of data.

[00:05:12] And so with that how do we actually foster this approach that ensures the data are used in the public's interest.

[00:05:20] So that was one aspect.

[00:05:21] The second aspect was actually engaging with the public directly.

[00:05:25] It is in a Canadian perspective there was a legal ruling back in 1997 that the public owned their health data.

[00:05:32] So that the question of ownership is already definitively decided in a Canadian perspective.

[00:05:39] And based on that it's like how do we meaningfully engage with the public to ensure that their data are meaningfully being used to protect themselves as well as to protect their communities and ensuring that those data are protected and maintain privacy and security protections on it at the same time.

[00:05:57] And so with that how do we actually meaningfully engage with the public to actually understand what they require for trustworthiness and how do we break that forward.

[00:06:07] And then the third other area that I would really call out was recognizing the importance of interoperability.

[00:06:13] So it's the how do we ensure that the data and data flows are able to communicate between the various systems across networks but it's not just around the technical standards and the semantic standards.

[00:06:27] It allows the data to be exchanged.

[00:06:28] It's also the compatibility of health policies and data policies to allow data to be shared across borders for various uses for individual uses or for uses of the community in and of itself.

[00:06:40] All of this was packaged in one document that was referred to as a Canadian health data charter, which is actually endorsed by health ministers last fall so long after I had left Canada.

[00:06:53] But they agreed that this effectively think of it as a many bill of rights but it's more it's a charter saying this is a declaration of how we're going to be operating health data within Canada going forward.

[00:07:07] And like that in itself having now come to Europe certainly has been inspiring my activities here.

[00:07:15] And how do you see that these efforts had the impact on the initial aim, which was to enable clinicians to provide better care to give people access to their own health data and to support the use of health data to improve health care public health and population health.

[00:07:36] So what are the actual results.

[00:07:39] Yeah, so the fundamental like the first thing I'll call out is the definitive vision for the use of health data and digital tools and technologies, which was really framed as an integrated person centered learning health system, which is to say that establishing

[00:08:01] the data flows and protocols and the digital tools and technologies that allow for when data are collected in the first place that those data are made available across the network to provide care for the individual.

[00:08:13] And those data are available for research purposes for population public health purposes, in order to actually find out new new innovations that can help public find new public health measures and population health measures that would actually improve the care for individuals

[00:08:30] and creation of algorithms that are actually inserted back at the point of care to actually drive improved care on a go forward basis so really linking the use of data from the point of care through the secondary uses of data and then those insights back to the point of care to actually continuously

[00:08:50] improve things.

[00:08:53] In terms of practically what's actually happening on the ground.

[00:08:57] The movement in Canada is strongly toward a governance approach that is based on what's called collective impact.

[00:09:06] Recognizing that data supply chains are the action of using data often involves multiple organizations that don't have direct accountability to each other think primary care hospital primary care facilities hospital facilities public health agencies, each of whom are

[00:09:25] working together in a data supply chain to ensure that their policies and processes are designed to actually work together more coherently.

[00:09:36] So, in terms of recognizing what those data supply chains are the governance structure really brings together this idea of collective impact and collective impact says that there should be a

[00:09:45] backbone organization that brings together these collective organizations that are trying to work together. There should be common measurement of the effectiveness of the network of all the different players also reflective of the respect for the capabilities that all those individual organizations

[00:10:05] bring to the table, and there should be strong communication amongst all those different players in terms of where they're going in terms of what they're actually doing. All of this under one umbrella of they have a common vision they're trying to achieve.

[00:10:20] So you think of it common vision, common respect for capabilities, common measurement about what we're trying to do. Good communication about progress or making supported by a backbone that really brings this whole session together. That is the section or the approach that you're trying to use within Canada today.

[00:10:39] And quite basically similar principles will need to be implemented in Europe for the European health and space and I must say that when you mentioned that good communication is basically the essence of all this. It made me smile because it's such a it's such an art in a way to actually have good communication

[00:10:58] and what does that even mean. So, for example, when we look at the European health data space and the legislation that came out. There's a lot of discussion around ensuring interoperability, the use of standards but honestly personally I'm still waiting to see which standards will be mandated what are we even talking about.

[00:11:15] In concrete sense. So where do you see that the next step should be in the European health data space. What do you expect to see and where maybe you can start with where most glitches happened or what are the conditions that you're going to see.

[00:11:30] So, where do you see that the next step should be in the European health data space. What do you expect to see and where maybe you can start with where most glitches happened or are happening in Canada with the pan Canadian data strategy.

[00:11:49] Right. That's obviously a very timely question given the current discussions that are going on. My perspective of this is we need to bring forward the public in a very strong way and providers because those are the two groups that are most impacted by the shift towards

[00:12:11] digitalization of health systems and we need to be bringing them into the conversation to make sure that we're designing the system with them, not for them.

[00:12:23] So, where for them is we're going to give you something interesting and then it is neither useful nor usable by individuals and so I think there needs to be more meaningful engagement with the public and with providers about this digitalization journey

[00:12:42] that we're going to take in the next life. And that's one area where I think Canada has been recognized the importance of bringing forward the public voices in the various activities. One of the things that I'm trying to do in my work, both in Canada as well as here is to tap in consistently to the public voice whenever and however I can.

[00:13:03] So, the second area I think is second area that there was the provision that was published a few weeks ago about the European health data space being fundamentally opt out, which is excellent because opt in would be near impossible to effectively

[00:13:22] achieve, especially in a world where the public fundamentally believes that their data should be used in order to improve their own care and the health and well being of their communities, while their data should also be protected. And so understanding that as the

[00:13:40] repeated survey results of public perceptions is really important to actually make that in hence why I really appreciate where it's going with opt out. Having said that there was little asterisk associated with opt out, recognizing that there are scenarios where using data are more important than keeping data wholly and totally protected, such as in the

[00:14:03] cases of pandemics or public health emergencies, such as in the case of trying to address issues of rare diseases. How do we actually foster better cooperation and collaboration across borders while respecting privacy, but also ensuring data are used for effective decision making.

[00:14:21] That was put under a umbrella of public interest in the areas of public interest in the declaration of the HDS a few weeks ago, the details around what those areas of public interest are and how that public interest would actually be administered and communicated.

[00:14:38] I think are one of some of the areas that are going to be most interesting to pay attention to in the coming weeks. The last area, which I will call out being the standards. I think that again, the language I try to use in this space is that we need to ensure that policies are compatible across borders.

[00:15:01] So that way, when you're trying to collaborate between two countries that they can actually collaborate together because their policies are designed to be compatible they do not need to be the same.

[00:15:12] But they need to actually be designed to work together so you can actually do a collaboration between say Germany and France or Latvia and Estonia, or even better Spain and Finland.

[00:15:24] So how do we actually create our policies in a place where there is that level of compatibility of our policies. Then from a state data standards perspective and the semantic and technical standards, how do we ensure that they are common or harmonized wherever they can be.

[00:15:41] I know that there are several joint actions at the European Union Commission that are trying to tackle some of these issues right now. I don't know what the outcome of those discussions are going to be, but do believe that the progress that is being made in Europe is certainly headed in the right direction.

[00:15:58] Having said that, if I can use a cliche, the devil is in the details and trying to get to those details as quickly as we can. I think will be really important to help foster this entire environment.

[00:16:12] What I worry about at large is organizations trying being worried that we need to make things perfect. And so by making it perfect, it takes a lot of time away from actually making it good.

[00:16:29] Because the recognition is that what we have to do here is we need to make good and then make better because that takes a lot less time. And frankly, you get real value and real learnings out of making good and making better.

[00:16:43] Whereas if you make it perfect and you wait to make it perfect, the reality is today's perfect is tomorrow's imperfect because things are going to evolve in terms of technologies.

[00:16:54] And so what we actually have to do is get things going, get things moving, get them good and then make them better. And the other facet I would call out is when making them good, recognizing that it's not perfect, having the very clear control process in place to make sure that things, disastrous consequences are prevented within that thing.

[00:17:17] So make good and protect is probably the best way of actually putting it.

[00:17:22] I think that's a great point because oftentimes when we introduce technologies in healthcare and especially while it's scale implementation such as the national nor portals, they take years to show an impact to be adopted.

[00:17:39] And I love the point that you made around the opt out approach. Generally speaking, we say that history teaches us that we don't learn from history and in healthcare data, we saw that many countries, Australia, Germany started with the opt in model optimistically and it wasn't successful.

[00:18:02] So they had to go to the opt out models to get to scale. But what I would be interested in hearing here from you is when you mentioned that there's this need that's recognized about the work with the community, with the people.

[00:18:19] And I'm wondering what kind of strategies do you see as most successful here, because if we look at the digital health literacy reports by OSED and other researchers.

[00:18:33] It's very clear that for example in Europe around 40% of the population has some challenges with digital health literacy. So to a degree, if I would be the devil's advocate, I would say that the opt out models are playing on the weakness of the population.

[00:18:53] So how would you, how do you see that and how do you see that this could be approached and fears around data sharing and data safety reduced.

[00:19:04] Thank you. They're actually going to pull in a few examples from Canada and some of the stuff that I see happening in Europe today.

[00:19:12] So one thing, I think that there are two separate things that we have to do and engaging with the public meaningfully. One is we do need to increase literacy writ large across across the public.

[00:19:27] And the second thing is we need to be fostering what I'll call patient leaders who can meaningfully engage with policymakers when they're actually at the table designing the future of the health systems and actually having these discussions and debates about where digital health should actually go in

[00:19:44] the next iterations. With that, there are two things that we'll call three things that we'll call out. One is there was a course that Finland put together a few years ago called elements of AI, which was intended as a course like they the headline was to train more data

[00:20:05] for Finland. But practically speaking, what it enabled was people in Finland who took the course and they their aim was to have one percent of the population. Then they were understandable that Matt the world of artificial intelligence for them.

[00:20:20] And so they realized this is not magic. It's just math. And based on that, it lowered the concerns around what is this scary new AI thing that I only see bad things happening in public culture and various movies. It's like, Oh, this is actually really beneficial.

[00:20:38] And so that's what the use case they used within the elements of AI program is actually health related or late breast cancer. And so it enabled people to say, Oh, this isn't actually something I'm that worried about.

[00:20:51] And so I'm trying to tackle one percent of the population. Part of the, the objective of that is if I haven't taken the course, I'm likely to know somebody who has. And so if I'm curious about this, if I have a question about it, then I can have, I can phone a friend, somebody that I trust is

[00:21:07] trust a colleague to actually build a better social fabric around what the acceptability of the use of these new tools and techniques and technologies are. And so I think that is a very, very novel approach that Finland took.

[00:21:20] I will note that elements of AI was then scaled from a European perspective. I think it's available in more than 20 different languages right now. And so it's something that I think is an interesting way.

[00:21:32] But I don't think it's, I think it's a good way to get people deep into understanding what this thing is. I think, however, from the public perspective, or rather from a media perspective, from a communication perspective, we need to make sure that we're meeting people where they are when we communicate with them.

[00:21:50] So we need to make sure that we're not using a lot of jargon when we're actually talking about these new advances. I try to avoid using words like interoperability for frankly a long time when it was talking to public groups, because it just felt like one of those really complicated words that a general person in the public is going to have a problem understanding

[00:22:12] and make a bit more time plan your communications in a way that can actually say, make sure that your messages actually hit home with the public. We would want the public to actually be able to meaningfully engage with the messaging in and of itself.

[00:22:26] If you think of things like the iPhone or Apple, they are used by the vast majority of the public and they don't read the instruction guide of how to use it because it's intuitive how do they use it.

[00:22:38] And so how do we create our communications from a digital health perspective that are actually intuitive for people to actually understand their role in it and understand why it's important to them.

[00:22:49] And I think that's something that we can certainly do. That is the writ large messages around the public. If I can put it this way, that we can better communicate or better train our policymakers, our communicators and our media organizations about how to communicate with the public about this complex topic.

[00:23:08] Having said that, second thing about trying to get to patient leaders. And this is where I'll reference in Canada there was a group called the patient advisors network, which was a network of patients who were sitting on various councils advising

[00:23:25] governments about how to actually do things by creating a network they were able to work together to actually understand what are the types of comments that people have. How do we meaningfully engage in conversations when we're not necessarily understood to be the expert.

[00:23:40] How do we bring our patient expertise to these various tables and that network itself is very well recognized in Canada and actually driven a lot of work in a European context.

[00:23:51] There are many things like there's patient assemblies that have been set up. There's citizen juries that were set up in the UK. I think there are public assemblies that were set up in, remember correctly Denmark and Finland, and ironically the city of Paris.

[00:24:06] So while those aren't necessarily targeted specifically at health. They are a representative body of the public that is brought together to debate important topics that are meaningful use for the public at large, and those groups are brought

[00:24:24] consciously to be representative of the public. There's a day that is spent getting that group up to speed about what the policy issues in terms of the backgrounds are, and then they have a day of deliberation about these are the main challenges we have had to address these areas.

[00:24:40] If I reference back to Canada there was a specific event that was done in a deliberative consultation with the public around what their health data uses were. And in the discussion they brought forward 93 statements, and they asked the public group to say what do you agree with on these statements.

[00:25:00] And at the end of it, they group could only have 100% agreement on three of them.

[00:25:06] And while the group itself is doing the facilitated was disappointed I was delighted because there were three and three that were important one. I expect my data to be used to benefit my care.

[00:25:18] I expect my data to be used to benefit the cell health and safety of my community. I expect my data to be used by academic researchers to improve understanding of disease and illness.

[00:25:30] So those are the three defaults 100% of the public group that was consulted agreed on that.

[00:25:36] Based on that could actually start to define the policy structures that we actually have to enable the use cases that we want in order to improve the health of individuals, the safety of communities and our understanding of disease.

[00:25:49] And especially in areas like prevention.

[00:25:53] And I think the key thing here is that oftentimes even patients that are for example, for example included in clinical trials don't get any feedback information about what happened with their data if they participated in some sort of a research.

[00:26:10] So that's what I see in the patient community that's often mentioned. I want to make sure that my data is used to help others, but I also wanted to know what happened with that and that's the thing that usually doesn't happen.

[00:26:24] I know that we are short on time so I want to move to the next question which is one of the things that you're working on is the economics of digital health and trying to figure out what's the return on investment with healthcare digitalization.

[00:26:40] It can bring a lot of optimization but it can also bring a lot of new costs related to a new workforce that you need to manage all the, for example, health care IT infrastructure and new knowledge new tools, new hardware, potentially.

[00:26:57] And also if we look at the digital health investments at the moment, they have been falling for the last few years.

[00:27:07] And the rock health report for the first quarter of this year, for example, showed that the quarter, the first quarter of 2024 was the lowest first quarter by sector funding since 2019.

[00:27:23] And that's something that's not exactly a great signal in the digital health space. So how do you see this trend and what are your current findings and thinking around the return on investment on digital health?

[00:27:40] I would say I'm not as concerned by the lowering of investments in digital health if it means that the investments are being made or intended to be made in ways that are more pragmatic.

[00:27:56] Let me go into my perspective on the economics. So a few years ago, the OECD published a paper that demonstrated among other things that for investments in digital health, one could expect a return of three euros for every euro that was invested.

[00:28:15] And obviously that type of one for three investment, obviously you have to try that would be something worthwhile pursuing.

[00:28:23] What we now understand, and I think this is really the poignant thing is how do you actually get to those types of returns? What are the critical success factors for those for those types of returns?

[00:28:36] And the critical success factors from a digital perspective is to enable ourselves to move from a linear model of growth to an exponential model of growth.

[00:28:47] And so if I think of a use case, if somebody builds something or rather put it this way, somebody asks a question and based on the question, now I need to go gather the data to answer that question.

[00:29:01] Can't the question could be what is the prevalence of diabetes in the country? What data do we need to gather? Go gather the data.

[00:29:08] Now that I've got the data, I can now answer the question and I've answered your question. That cost me for that one question, it cost me X.

[00:29:16] Then the second question comes along, and then I work out based on this question, what is the data I require in order to answer that question?

[00:29:23] But now I start to also ask, and what data do I already have that could be used to help answer that question?

[00:29:30] So now I only gather the new data I need for the question, I link it to the data I've already gathered, and then I answer the second question.

[00:29:39] And so I've now spent instead for the first question I spent X to gather the data for the second question I probably am spending less than X, call it half of X.

[00:29:48] And then on the second, third, fourth, fifth, sixth, hundredth and ten thousandth questions that we have eventually get to a point where we can start answering questions for free.

[00:29:58] Because we've actually gathered the data effectively in a way that is usable to answer the myriad questions that we're going to have from our policymakers from the public from our providers.

[00:30:09] But that only happens if we are collecting the data in a way where is usable and droppable, and our policies are compatible to allow for its use.

[00:30:19] Those are the things that in order to achieve the types of returns that we want from a digital health perspective, we need to have the foundations of policies and of data standards that actually drive the ability for the reuse of data in of itself.

[00:30:36] But that is not enough, because we also need to have the governance structures in place that encourage the reuse of the various assets and interoperability structures that we've set up.

[00:30:48] This is where from a funding perspective in the first place, if I'm funding a hospital, I can find a hospital to say build a hospital and be a silo, build all your tools and technologies locally do everything you actually need.

[00:31:02] It's going to be easier for you. You will deliver the hospital faster because you don't have to leverage anybody else. It's going to be faster go for.

[00:31:11] But the problem is, when we fund that type of hospital, we create silos and those silos aren't able to communicate to each other.

[00:31:18] And what we have what we create is because we now have silos, we need now additional funding to connect the silos together.

[00:31:26] So we have an unexpected expense of actually connecting.

[00:31:30] This is where digital health investments have frankly in the past because we did fund hospitals as silos.

[00:31:36] And we did have to do the investments to connect them together. And this is where digital health is frankly not had the economic return that we expected in the first place, because we hadn't set up the foundational infrastructure of policies and interoperability structures that allow for the hospitals to connect.

[00:31:55] This is where I'm hoping from a digital investment perspective that the policymakers and specifically the financial leaders are realizing their role in driving digitalization of health, in that when they're actually approving the various initiatives for new built hospitals for new procurements that they're doing, that they're

[00:32:14] embedding in those procurements. These are the rules. These are the standardized policies and standards and practices you need to have in place in order for your system to be interoperable with everyone else recognizing the value of the network is more important than the value of an individual institution.

[00:32:31] And so from that perspective, that is the path that are the mental model that I'm on as far as the economics of health. Having said that the areas where I'm digging in now from an indicator perspective is I'm looking at what is the readiness of health systems to adopt digitalization.

[00:32:49] There's a their human their financial and technical capacities, as well as their policy structures and standards that they have in place.

[00:32:57] What is the usage of the actually have of digitalization. And I'd like to think of that as the more advanced utilization it's not simply do you have a patient portal. It's more have people actually access their patient portal to use their data on a regular basis.

[00:33:13] And then importantly, the third aspect what is the impact that digitalization is having part of that is going to be in the ability to answer questions when they come up.

[00:33:23] But it's also our people more satisfied with the systems are people fundamentally healthier or their self reported outcomes and their self reported experience better are doctors and providers reporting less burnout because the systems are designed for them with them as opposed to them.

[00:33:42] So how do we actually do that and so those are some of the measures that will have. I think the real magic of digital health will happen when we were able to start shifting ourselves from our sick care system that we have today to a more prevention based system tomorrow, because if we actually are able to automate the

[00:34:02] Automatable if we're able to empower 8 billion people with their health data. If we're able to empower the providers the insights they have they need in order to help drive preventative activities in addition to care activities, then will actually generate a healthier and healthier population adding not just quality of years of quality to life but also years to life

[00:34:26] There's probably a million questions that we could go to from here to data quality data interpretation. And I still want to maybe ask you mentioned several indicators or measures that should be taken or insights that we want to get from the data that we are gathering.

[00:34:50] However, one of the things that we often forget when we talk about these insights is the actual skills workforce and capacity to do this research. So there's this notion that data is gold. And I loved when I spoke to fill up fill our Fernandez hermita from the UAE when she said data is not gold people who know what to do with the data are so I think this is something that we don't really mentioned often enough, because

[00:35:20] yeah, you need analysts, you need good data. And even that is sometimes not enough when data sets are not comparable for example especially when you do the digital transformation and you introduce a completely new digital system.

[00:35:35] Even if you wanted to do a cost benefit analysis or a comparison of impact on care, you can't do that because the data set from when things were done manually is not comparable to the ongoing digital data capture.

[00:35:53] What do you think about that? How can we make progress in this field?

[00:35:57] First of all, we'll reflect I very much enjoyed that quote as well. I'm starting to use it myself because people truly are gold. They are the actions and people who actually make change.

[00:36:07] I actually tend to reject any type of analogies of data toward gold or oil because they're physical goods and data are something that can repeat and actually be spread. Data is much more like electricity as a public good or water as a public good.

[00:36:24] But if I use water as the analogy, we need the technologies is the pipes to carry the water and the taps the analytics to actually get the water out of the systems and of itself.

[00:36:34] So we need to develop those services together across the pipes, the water and the taps to actually achieve the outcomes we want because if you're missing any one of those components, it doesn't work.

[00:36:44] And this is where you need, as you said, the right workforce. One of the things I called out before from a readiness perspective is to assess the human capacities to actually engage in the systems itself.

[00:36:57] When I look at health as a whole, and these are estimates that I saw last year, about 3% of the health workforce is dedicated towards technologies or data analytics.

[00:37:12] When I look at comparable other industries, banking for example, they are closer to 1015%. And I would argue that in health where data is frankly more, there's significantly more data significantly more complex and more value to be had from it.

[00:37:31] The fact that we are one fifth of the size of workforce that is dealing with data as income other industries is a clear opportunity where we should actually putting a spotlight on these are the types of jobs that need to exist in the 21st century.

[00:37:48] This is how we can actually bend the, not just the cost curve but just bend the problems that we have. We know, for example, there is a massive deficit of health workers is projected to be 10 million globally by 2030 of health workers.

[00:38:04] And it is not practical or possible to expect that we're going to close that gap at 10 million employees solely through the acquisition of new doctors and nurses.

[00:38:16] While we will certainly need to increase the size of the frontline professional workforces in and of itself. I fundamentally no believe that we must engage with digital tools and technologies in order to help the workforces themselves.

[00:38:31] There are approximately various studies have shown anywhere between 10 and 30% of activities for many frontline health professionals are administrative, automatable activities.

[00:38:45] And so if we're able to use digital tools and technologies to automate those activities, we can free up a massive number of health workers that can actually help close that gap of our future needed health workers and or help those health workers that exist to actually have better balance in their lives

[00:39:05] and better experience. But in order to do that investment we need the health IT health data professionals to actually do the work of automating those workflows in and of itself. So investing in health and IT and data professionals will actually help close our gap that we have from a frontline perspective.

[00:39:26] One of the things that I came to the conclusion of very early days in my time in Canada was that we are at a point where the value of one new IT employee who can save through their efforts five minutes from a day from every health worker is more valuable than hiring in a new doctor or doctor or nurse.

[00:39:49] Now that's not universally true, but it is certainly true in some circumstances where by investing in digital workforce because they are focused on things like how do we automate how do we improve the lives of our frontline professionals in and of itself, then we can actually help to address it.

[00:40:07] So I think putting more of a light on that is one of the things we need to do. I think we also need to describe what are those roles that need to exist because it's not just programmers. We're long beyond that we needed the data science professionals who needed the data steward professionals, we do need to have data protection

[00:40:25] and we need to have the data engineers as well in order to make sure that things are protected and trusted, but we also need to have the people who are fostering the access to data assets in and of itself.

[00:40:37] I think that's a great idea. And I believe Ireland and Canada has a plan for creation of a data commissioner type of role to act as a as appear to the privacy commissioner so that way we can actually champion both the access to data as well as this protection at the same time, ensuring that we're doing it in a way that is trusted and effective for the public.

[00:41:03] So we're also defining what that future workforce looks like. And with that, starting to really invest in those tools and invest in those not tools invest in those people to actually build the capacities we have and encourage the policy leaders who are hiring those jobs, increasing their awareness of the importance of investments

[00:41:23] health is sadly largely it's much easier to justify hiring new doctors and nurses. That is something that is easy for a policymaker to say look up what we did we increase the health doctors and nurses by 10% is harder to make the story.

[00:41:39] Look, we hired all these back room technology people in order to do this work in order to create capacity for those frontline workers. It's a harder conversation to happen, which ironically enough, it is the conversation that needs to happen.

[00:41:54] So it ties back to how do we communicate that most effectively with the public that these investments are actually necessary to improve the quality of health systems and improve the quality of care for people.

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