S2-Episode 10: Health equity: Using data to make a positive difference for communities

Dec 20 2022

Health influences happiness and overall well-being, but not everyone has fair access to resources that support good health. Health disparities persist, influenced by sociodemographic factors such as age, education, gender, income, and race. What can be done to address health inequity without sacrificing personal privacy? In this episode, Commissioner Kosseim speaks with Dr. Kwame McKenzie, CEO of the Wellesley Institute, about how anonymized data can be used to advance equity in health care and health outcomes.

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Patricia Kosseim:

Hello, I’m Patricia Kosseim, Ontario’s Information and Privacy Commissioner. And you’re listening to Info Matters, a podcast about people, privacy, and access to information. We dive into conversations with people from all walks of life and hear real stories about the access and privacy issues that matter most to them.

Hello listeners. Welcome to another episode of Info Matters. Thanks for tuning in. The writer and philosopher Voltaire once said, “There can be no happiness without good health.” There’s no doubt that health has a major influence on both our happiness and our overall wellbeing. Taking care of body and mind is essential, and everybody should have a fair shake at being as healthy as they can be. Unfortunately, this isn’t always the case. Health disparities persist in neighborhoods across Ontario, resulting in negative health outcomes for individuals and entire communities. Health disparities may be due to various factors including inadequate access to healthcare, employment status, differences in household income, education, age, gender, and race.

What can be done to address these inequities without sacrificing personal privacy? How can we ensure individuals, no matter who they are, where they live, or how much money they make, have a fair and just opportunity to reach their fullest health potential and enjoy quality of life? In this episode, we’ll explore some of the ways data is being used to address inequities in healthcare and health outcomes. My guest is Dr. Kwame McKenzie, CEO of the Wellesley Institute, an organization working to advance urban health in the greater Toronto area through applied research and effective policy solutions. Dr. McKenzie is also a professor in the Department of Psychiatry at the University of Toronto and Director of Health Equity at the Center for Addiction and Mental Health. Dr. McKenzie, welcome to the show. Thank you so much for taking time out of your busy schedule to join us today.

Dr. Kwame McKenzie:

Thank you for having me, and I’m looking forward to the conversation today.

PK:

So can you tell us a little bit more about yourself and your work? How did you come from running a clinic as a practicing psychiatrist to leading a policy think tank working to advance health equity?

KM:

It’s an interesting journey that I have been able to have. And like everybody who goes into medicine, you want to help people and you want to make people better, and I chose to do that through mental health and through psychiatry. And after you’ve been practicing psychiatry for a while, the first thing that comes to you is you think, “Actually, it would be better to have better treatments,” and so you often get into research. And so I went from clinical work to research. And then after a while, you start thinking, “Well, what does research tell us about what we need to really,” as you said from Voltaire, “for health and happiness, what can you do to prevent people getting ill, and what can you do to help people who have been treated actually fully recover?” And that’s when you get into thinking about the social factors that cause disease and the social factors that help recovery.

And so I started then getting into research on what they call the social determinants of health to try to see if I could actually increase the number of people who get better once they’ve been treated and decrease the number of people who were saying, “Well, thanks very much. I was depressed. I was anxious. The treatment seemed to work. The cognitive behavioral therapy seemed to work, but actually I couldn’t pay my bills, and the stress of not being able to pay my bills meant that it may be that everything you’ve done is effective, but now I’m depressed again or now I’m anxious again.” And it’s that revolving door that I thought, “Well, we must be able to do something about.” And then the question is, how do you apply that research? How do you actually get anybody to listen to it, and how do you make change?

If I really want to do the best for my patients, I need to try and increase the knowledge we have from the research to see if it’s possible to get that knowledge to actually make social change, and so that’s how I ended up in a policy think tank. And of course, looking back now, it all seems very clear and sequential, but it’s not quite how it all happened. It was much more haphazard and chaotic, but it does all fill together in a narrative as you’re looking back and you’re making sense of your life.

PK:

Well, interesting and fulfilling careers rarely are sequential, so that certainly is a fascinating journey. In your practice as a clinical psychiatrist, you certainly dealt with a lot of highly sensitive mental health information. Do you think it’s fair to say that mental health information is more sensitive than other types of personal health information?

KM:

I think it’s reasonable to say that, yes, we collect a lot more sensitive information than other people because we’ll collect information about some symptoms that people have and some symptoms that people find distressing or embarrassing, like hearing voices or other things like that. So we collect that information, but we also collect and ask people information about their childhood. We ask them about their relationship with their siblings and their parents and their partner. We ask them about any substances they’re using. We ask them about how they view the world and some of their inner most thoughts that they only share with very close friends. And we need all of that information to be able to really understand the person, make the right diagnosis, and be able to help them in the right way and try and understand things that might get in the way of recovery. So it’s not just the normal symptom information that you often find in medicine, there’s a lot of very personal information that people will only tell very trusted individuals that we need in order to make sure that we are doing the right thing.

PK:

So over the course of your practice over the many years, would you say there’s still a stigma attached to mental health issues today?

KM:

I think I’ve seen the stigma change. So I have seen some decreasing stigma in some places around anxiety and depression, but I’ve seen increasing stigma about people with psychosis such as schizophrenia. I think there’s a lot of stigma around substance use, but I think it’s very different in different places. And so there are parts of the population and parts in certain occupations where there’s less stigma than others, so I think it’s very variable. I think it’s nice to believe that stigma has been decreasing because people seem to be more open to talking about their mental health problems, which is good, but I don’t think it’s true for all, and I don’t think it’s true for all mental health diagnoses. And in fact, there is evidence from various studies in the UK, the US and some in Canada which have shown just that, that the de-stigmatization has been mainly for anxiety, depression, and trauma, but that there’s actually been an increased stigmatization for people with diagnoses such as schizophrenia.

PK:

How important would you say are privacy and confidentiality for maintaining trust in the doctor/patient relationship and achieving better health outcomes overall?

KM:

For mental health, you only make the right diagnosis and a good diagnosis if you have taken a good history. There aren’t a huge amount of tests. There are not clear physical tests for mental health problems. Mental health problems are diagnosed mainly on the history, which is the information we get from our patients and their family and friends. That’s where most of the information comes. And if the information isn’t good, you make a poorer diagnosis. You’re less accurate in your diagnoses. And people have to trust you to give you that information, and people will only trust you with that sort of sensitive information if they believe it is private, if they believe that it is a conversation that is really between their doctor or their therapist, their psychologist, or their social worker. They’ll only tell you these things if they don’t think this information is going anywhere else and if the information is going to be used to their benefit.

And privacy’s really important. People are really worried that the information will be seen by others, and that undermines them giving you all the information. And when you think about it, it’s difficulty enough, you’re speaking with somebody who you’ve developed a relationship with, and you’re thinking about something or you’re doing something you’re a bit embarrassed about. People believe they should be tough. They shouldn’t cry. They should be able to suck it up. They shouldn’t get anxious. That’s what they’re told. And so people are embarrassed, and they think it’s a form of weakness. Some people do. So you muster up all the courage to be able to have a conversation, and then you have to muster up the courage to tell them your inner most thoughts. And all of that is difficult. And think about how much more difficult it is if you then worry that that is going to be shared in some way with people who you don’t know. So’s really important that people believe that their information is confidential, and that they can trust that we are going to look after it properly.

PK:

So while you say that personal health information must be protected for the practitioner’s eyes only, so to speak, there are broader benefits to making it available for other purposes, like improving patient care, research and public health, subject to appropriate conditions of course. Can you elaborate on some of those broader uses of mental health information and how important they are for the health system as a whole?

KM:

It is clear that people need to be able to trust that their information is private. And I think that the systems we generally have in place are really good at that, but I think that people also believe that if in a safe way their information can be used to improve mental health services, health services, improve the treatment of others, I think most people are happy if they can in such a simple way improve the health service and improve our resource allocation, other things like that. And I think anonymized information that is used at the level where nobody’s going to be able to work out that it is a particular individual is really important and is vital for the health service. There’s actually no place in the world and no industry that isn’t using data at the moment to work out whether what they’re doing actually is working as well as it could.

Who is it working for, who is it not working for? Who’s coming through the door, who’s not coming through the door? All of those sorts of things you need data for. And one of the things for a learning health system is that every time something happens, every time somebody comes in with a problem, that problem gets treated, you get to see the outcomes, and you get to work out how you can improve. That’s what a learning health system is. And so I think that it’s not just a nice to, it’s a vital part of health these days is that we use the information we have to improve the outcomes to make sure that we’re reaching the right people and to also identify if things are going wrong. Because if we don’t have the data and if we don’t actually check what we’re doing, if we have a system that inadvertently produces bad outcomes for some people, we wouldn’t know.

And so I think data’s vital for improving care. Data’s vital for working out where our resources should go. Data’s vital for alerting us as to when things are going well and alerting us to when things aren’t going so well. It’s interesting to me that a whole bunch of people got pretty addicted to health service data in 2020 and 2021 when every day we were seeing whether cases were going up and down, how well the pandemic was being controlled, whether we should change what we’re doing. People got used to seeing the different rates of illness and the data that was coming from it. People got really excited when they started seeing the percentage of people who were getting vaccinated and therefore how safe things were becoming. And they could really judge whether the sacrifices that they were having to bear were making a difference.

And the same data has been able to show us that our pandemic response was actually really good in some ways compared to other countries, and was also able to show us where the lockdowns worked, where the masking worked, and we got used to that. But of course, every bit of data that we’re using is somebody’s data anonymized. Nobody knows who it is, but that’s somebody’s data that we’ve put together so that we know what’s going on and so that we can pivot our response accordingly.

PK:

I was certainly one of those people addicted to data, watching that curve every night hoping it would come down and vaccinations would go up, so I can understand exactly what you mean. And speaking of the COVID-19 pandemic, it’s a good segue to another question. I’d like to ask you about how the pandemic related data showed us in some ways how the health system was working and succeeding, but it also highlighted significant inequities in health. And you were of course outspoken about the need to collect race-based data to better understand how communities were being differentially impacted by the virus. In fact, you led a study on that very question and published some important findings. Can you tell listeners about your study and what you found?

KM:

Okay. So if we went back to March 2020, a couple of months after the first case of COVID had been in Canada, there were reports that started coming out in the UK and the US that some racialized populations, and particularly black populations, were at high risk of COVID, two to three times the risk of white populations. And so some people in the black community were saying, “Is this happening in Canada?” And at that time, we couldn’t tell you whether the black population were at more risk or less risk than anybody else. And so a community group formed called the Black Health Equity Working Group and said, “Well, I think we really need to collect these data. If anything like what is happening in the States and in the UK is happening here, then we need to think about what we can do to decrease COVID based inequities.”

And so that group said, “Well, let’s start off by analyzing the data we have.” And just in Toronto, if you looked at the different areas once you analyze that data, it showed that in some parts of Toronto, the rates of COVID were nine times higher than in other parts of Toronto, nine times higher in some areas than others, but what we didn’t know was who in those areas was at highest risk. If you know who in the area is at risk, you can make a response which is really targeted at a particular high-risk group, and that’s the most efficient way of doing things. So we started pushing and pushing hard and trying to get public health units and government to start collecting sociodemographic data and race-based data when people were diagnosed with COVID. And we were quite successful. This coalition of people included academics, community organizers, clinicians, people who ran CHCs, just all sorts of people.

Anybody could join, and this was a sort of community-based initiative. And we convinced some public health units to start collecting data. And then by June 2020, the government of Ontario had decided it was going to ask for these data be to be collected, which was a first for the government and was a really foresighted position of government at the time. And when the data came in, especially say for instance at the Toronto level, it was actually very, very worrying. So some populations, like the Latino populations had rates of COVID which were 11 times higher than the white population. The black population had rates of COVID which were nine times higher than the white population. So the question is, what do you do about it? And the government did some interesting things. So the provincial government decided to set up something called the High Priorities Community Strategy to try and work out how they can improve the rates of COVID in areas with high rates.

And places like the city of Toronto said, “Hey, let’s sit down with particular groups that are at high risk and ask them what we can do to decrease the risk.” And when they did that, when they sat down, say for instance with the black population, the black population talked about, “Hey, can we have pop-up testing and mobile testing? Is there any way we can have places that we can isolate if need be that are free because we’re overcrowded. We can’t isolate? Are there ways of decreasing the crowding on buses because we’re essential workers going to work, and we’re on these buses. These buses are crowded and people are getting COVID.” And they came up with a number of very straightforward solutions that they wanted, plus help with childcare, plus eviction protection. All of these things put together ended up being the Toronto strategy. And once the Toronto strategy was put in place for, say for instance, a black population, the rates of COVID between July, August, and December 2020 came down from nine times the white population to just two times the white population. This huge impact.

That impact was really because we had the data, the data were analyzed, and the data were used to try and produce change, but that use of data, the collection and use of data, that saved lives. And so we did collect the data. We did produce a paper. We sent it to one of the highest medical journal groups, the Lancet Groups. And it got peer reviewed, and it got published in their eClinical Medicine series. And so it’s a peer reviewed piece of work demonstrating that if you collect these data and use them, and if you work with community, you can make huge changes to the outcomes even in a pandemic. So really, really great and exciting work that was spurred by the pandemic, but, yeah, it’s extraordinary what we can do when we’re not flying blind.

PK:

Amazing. What a powerful story of how data can have such concrete results to benefit communities. Under Ontario’s Anti-Racism Act, race-based data is being collected in the justice, education, and child welfare sectors to address racial inequities and root out systemic bias in the system. But currently, health information custodians such as hospitals or other healthcare providers are not covered under the act. Do you think this is a major gap?

KM:

I think that there is evidence across the world and evidence at municipal levels and provincial levels that having these data can make a difference. If these data are not available, the problems are invisible, and it’s very difficult to get people interested in dealing with hypothetical invisible problems. So the data’s there to understand and identify the problem, but the data’s also there to monitor your response. And so it is very, very surprising that health didn’t get included in the first place. I don’t know that it needs an act for health to do what in many places is considered good clinical practice and good public health practice. It is interesting that the public health guidelines, which are published by the province, recommend that sociodemographic data is collected and used to ensure that we have an equitable system. And I don’t think there’s anywhere else, any other high income country where there is so little sociodemographic data available than here.

We are always really happy to look south of the border and say, “We have a better system than they have,” but when people do assessments of what’s good about their system and what’s good about our system, we lose marks on our equity data surprisingly compared to the states. They’ve got much, much, much more data than us. They’re much clearer about who is and isn’t getting care. Now, they don’t always do something about it, but they at least are much clearer about it.

PK:

So speaking of equity of care, you’re a member of the Black Health Equity Working Group that’s developed a governance framework for health data collected from black communities in Ontario. And this working group that you’re a member of has developed the EGAP framework, which stands for engagement, governance, access, and protection. Can you give us some background on the principles of the EGAP framework, how it was developed, and how is it being used on the ground In Ontario?

KM:

When we are looking at any population, whether it’s a black population or any racialized group, or actually any group in society, is it’s not like everybody’s the same. It’s not a homogenous whole. And so when you talk to some racialized groups, and let’s talk about the black groups, there are people who will say, “We need data to be able to see whether we’re getting fair access to care, whether equity is happening, and where equity isn’t happening.” There are other people who say, “The history of people collecting data on our population is it’s been used against us, has been used to stigmatize us one way or the other. I’m not sure I want to give my data,” so there is a big risk in people not trusting data collection and trusting data collection is really important for getting good data. And one of the ways people trust in data collection is by having clear understanding of what the data’s for and some power over what the data is used for.

And so when we were talking to people and saying, “We’re going to collect sociodemographic data during the pandemic,” some people were saying, “Well, we’ll give you our data as long as we’re really clear that it’s being properly looked after. And what we mean by properly looked after is we want a bit of control over these data,” and that’s where this idea of the EGAP came from. It said, “Well, if you’re going to collect data on a group and that group may be sensitive about the data you are collecting, let’s start off by engaging. Engage with the group and make sure that people understand what you’re doing, understand why you’re doing it, and start having a conversation, a trust building conversation with groups.” So that’s the first bit. Engage with people. Have a conversation about data. Second, work with community to set up community governance, and community governance can be really helpful.

Sort of what data is being collected, why it’s being collected, how is it going to be used, and making sure that the community have a say, so that’s the second bit of EGAP. This idea of governance and thinking through in a balanced way how data keepers and community can work together to be happy that things are being done properly. But then communities were also saying, “Well, these data are collected, but we never have access to it. We can’t use it for our own community benefit.” And so one of the things that we were talking about in EGAP was saying, “Well, what does access look like? What does access to anonymized data look like? How would community be able to use data for community good?” And then the last thing was, what protections should be in place to make sure that a community are protected from the negative use of data? So the reason we say that is because communities say, “Well, everybody thinks about privacy to an individual level, but people never think of privacy at a community level.”

And there may be things that, say for instance, a health service needs to know about, but are these things that the health service need to publish data? And publishing data and publishing results can cause harm, and so what protection should be in place to make sure that the use of anonymized data sets do not harm communities? And so that’s where it came from, the engagement, governance, access, and protections. But the important thing about the EGAP isn’t that it’s a prescriptive way of governing data, it is a set of principles that help data stewards start thinking about how they include community in thinking about these issues of sensitive data at a community level. And I know that some CHCs, which are community health centers, some Ontario health teams, and some of the bigger hospital groups who are collecting sociodemographic data as part of their electronic medical record are now saying, “We need to have these conversations, and we need to start thinking about using EGAP principles to ensure that we’re doing things right, but also to ensure that that transparency around these data increase the trust that people have in us as data stewards.”

PK:

While on that very optimistic note, I’d like to thank you once again, Dr. McKenzie, for joining us on the show today. We’ve covered a lot of ground here, and you’ve certainly opened my eyes to some of the complex and evolving factors that contribute to health inequities. It’s clear there’s so much work to be done, as you said, and data is a powerful tool to help reduce inequities and improve health outcomes for vulnerable populations. For listeners who want to learn more about the work my office is doing to support the use of personal health information in privacy respectful ways, you can visit our website at ipc.on.ca. You can also call or email our office anytime for assistance and general information about access and privacy under Ontario’s laws. Once again, thank you everyone for listening. And until next time.

I’m Patricia Kosseim, Ontario’s Information and Privacy Commissioner, and this has been Info Matters. If you enjoyed the podcast, leave us a rating or review. If there’s an access or privacy topic you’d like us to explore on a future episode, we’d love to hear from you. Send us a tweet @IPCInfoPrivacy or email us at podcast@ipc.on.ca. Thanks for listening, and please join us again for more conversations about people, privacy, and access to information. If it matters to you, it matters to me.

Dr. Kwame McKenzie is CEO of the Wellesley Institute, a professor in the Department of Psychiatry at the University of Toronto, and Director of Health Equity at the Centre for Addiction and Mental Health (CAMH).

  • A professional journey combining psychiatry and leading a policy think tank [2:20]
  • Mental health information, more sensitive that other kinds of personal health information? [5:08]
  • The stigma around mental health issues and how it has evolved [6:53]
  • Confidentiality, trust as key elements to achieving better health outcomes [8:33]
  • Broader benefits to the health system through the use of health data [11:56]
  • Using data to address COVID-19 fueled health inequities in Toronto
    communities [16:50]
  • Ontario’s Anti-Racism Act and health data [19:06]
  • Principles of the Engagement, Governance, Access, and Protection (EGAP) framework [25:49]

Resources:

 

Info Matters is a podcast about people, privacy, and access to information hosted by Patricia Kosseim, Information and Privacy Commissioner of Ontario. We dive into conversations with people from all walks of life and hear stories about the access and privacy issues that matter most to them.

If you enjoyed the podcast, leave us a rating or a review.

Have an access to information or privacy topic you want to learn more about? Interested in being a guest on the show? Send us a tweet @IPCinfoprivacy or email us at podcast@ipc.on.ca.

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