INTRO

PIPER

Hi, this is Piper Hale, and you’re listening to Inform Me, Informatics. For this episode, I’m bringing you part two of my conversation with Vivian Singletary, the director of the Public Health Informatics Institute, and David Addiss, the director of the Focus Area for Compassion and Ethics in Global Health, or FACE. In the last episode, you may remember, we talked about big data and how consumers may opt in to supply their health data to private companies. This time, we’ll be looking at population health and public health practice, and unpacking health data ethics through that lens.

Let’s jump back into the conversation, when I asked Vivian and David how to weigh competing interests when considering the ethics of using specific health data. I provided an example to get the conversation started.

PIPER

So for example, with HIV, we want accurate surveillance in order to inform treatment and prevention services. But we also want to keep people’s HIV status confidential, especially in situations where it might be unsafe for their status to be known in general to their community. So how do you weigh those interests? How do you determine what is ethical based on all these complex factors?

DAVID

That’s the key question. And I think the challenge is in really being aware of the different interests and bringing them into the conversation. So the example that you just described is sort of a classic one, and too often we don’t bring all the voices into the room and ask the question, “What do we as a society think about this? How do we weigh these competing interests?” For the example of vaccination, for example, we require immunization to enter school, but we realize that too strong an insistence on that is going to provoke even a larger backlash than we’re seeing now. And so it’s this tension between really making the norm what is in the public interest, but allowing some safety valves so that the resistance to those norms which benefit all of us doesn’t become as large as it is now and is threatening the public good. So I think part of it is having the conversation and recognizing whose interests are in favor of an intervention, whose interests might be harmed, and really weighing that at a societal level in a way that respects all of the different views. And sometimes that’s challenging, which is why we have groups in opposition to some of the public health measures that we have, like immunization.

VIVIAN

I think the use case that you gave about HIV is very interesting. On the surface, when you think about data collection of HIV status for population purposes and the collection of HIV information for use in treating the individual, all just kind of benign type of things that we do that we need to understand and treat the individual. And also, cure for the broader population and understand how we need to go through and do our interventions to reduce the burden of a particular disease, HIV just being the example here. I think what comes into play when we talk about data ethics here, in our new digital world that we live in, is making sure that we’re doing the right things from the data side, the technical side, that we are protecting people as best as we can. You know, we hear about data breaches every other day. You know, maybe something happened a year ago, and maybe we might hear about it. And so we’re still dealing with a lot of this.

So on the surface, there’s nothing wrong with collecting that data. The ethics comes in how we care for this data, protect it, and make sure in the protection of that data that we’re protecting those individuals and their privacy, to make sure that we’re not impacting them. Because certain diseases or statuses could have certain negative connotations and cultures, and we don’t want individuals to be subject to that. We also have to also be careful in terms of how we are portraying populations. So if you think about Metro Atlanta, for example, and we post a big disease burden map of, let’s say, HIV, and it’s in one particular part of, you know, the Metro Atlanta area, and even though that burden is true there, we from the data perspective have to be careful about that, in terms of how we represent them, because we could end up damaging that area economically. All of the people that live in that area, whether they have that disease or not, can be ostracized.

So even though data sharing is important, we absolutely have to be careful in how we handle that and how open it is, honestly, how open that data is. And think about who needs to see it, who we need to educate, and why they’re seeing it, “Are they part of the intervention here? Or are we just going to, you know, open it up to everybody for them to, you know, really just call a judgment on something?” So those are just examples of being careful, even if something is true.

DAVID

That’s a great point. And I think, in public health, we have to [00:25:30] not only use data, and share it and analyze it, but also interpret it and present it in a way that protects individuals and populations, as you’ve said.

PIPER

That’s a great point. That’s a great point. So to think about how we protect people on a population level, on a personal level, we do have guiding rules in the U.S. in the form of HIPAA and other laws and regulations, but there really isn’t the same level of oversight on population-level deidentified data. So, Vivian, you gave the great example of a Metro Atlanta community that might have a high HIV incidence. You know, we don’t protect the data of communities, for example, in the same way legally. So what are your ethical concerns or recommendations for considering these issues, when it comes to the population level rather than the individual level?

VIVIAN

This is a really complicated one, but I think it goes back to some of the principles that, David, you called out early on about ethics, you know, doing the right thing. So what is the right thing for us to do with this data? What is the purpose of the collection and use of this data? Because we don’t want to cause harm, I mean, so I think that’s another principle that we have to abide by. So being very clear, and then understanding that we don’t want to cause harm. We’re actually trying to do something positive to maybe reverse the trend that we’re seeing. So those are two key guiding principles that we have to use, in terms of thinking about how we go about using that data. We have to be careful about the words that we use in the interpretation of the data as well, that we don’t cause, you know, a new stigma around a particular thing that we’re looking at, whether it’s the disease or it’s something else. We have to be very thoughtful about that.

So I think we have to bring in the cultural perspective, or social-cultural piece of that as well, and think about it almost putting ourselves in the shoes of those populations like, “What if that was me? What if that was my community? What would I want people to say, and how would I want them to represent me?” So coming at it from the perspective of, sometimes not being so analytical from just the hardcore data perspective, but bringing some personal kind of skin in the game. And wanting to be as protective of the people that we are collecting data from and making sure that the data that we’re using is used in a way that brings help, and not more harm.

PIPER

So this is a difficult question. What can public health practitioners do to apply ethics to their own practice, whether that’s questions they can ask themselves or best practices they can follow?

What are some things that our listeners who work in public health can do to ensure they’re adhering to ethical best practices?

DAVID

The first thing would be to think, to imagine, to ask the question, “How might this intervention or the use of these data cause harm?” We don’t often think in those terms because we’re thinking about the benefits. So just stopping, thinking, and asking the question, I think, is the first step. Listening to people who might have a different view, or who might be impacted by the use of the data, would be the second thing that I would encourage all of us to bring into our daily practice.

VIVIAN

Yeah. I like the idea of incorporating a lot of what we discussed already. But if I am a practitioner, really being very clear on, again, the purpose of the data, how we’re going to use it. Thinking about some of the edge cases, even though I may be coming at it from a very positive standpoint, “What are some of the edge cases, in terms of longer-term impact that I may have not thought through?” So really, trying to challenge yourself and think about, “What if? What if this data got into the hands of someone, what does it mean? Will it harm somebody? How will it impact them?” So thinking through some of those things. The other piece that has come to me lately through some just general conversation is also about data retention. So while there is a real purpose and need for certain types of data, how long do we actually need to retain this data so that it doesn’t potentially have some other long-term, lasting effect on somebody or unexpected effect on someone? So maybe we’re collecting, you know, community-level data, or maybe we’re collecting, you know, some specific data on an individual or a population, but we may only need to keep it, you know, for a certain period of time, and then we can let it go.

So maybe, for example, you have a child that was in school, they had a run in with, you know, an officer, a police officer, you know, they had some not necessarily incarceration, but maybe they did something very petty. That information, there’s some type of alert system that may alert the school that the child is having some trouble. Why should the school keep that for 20 years if the child is not there, and it could have some lasting effects, and it’s something that would be expunged from their record at a certain age and no one else need to know about it? That’s just a really, kind of an edge-case example. But these are real examples because as data storage becomes cheaper and cheaper for us, it’s difficult for us to purge. We never wanna get rid of data. It becomes a great resource for future analytics and research papers, and different things. But I think it’s something that we need to think about and continue to challenge ourselves on.

PIPER

So your answers are probably going to be things you’ve touched on already in this conversation for this question. But what issues regarding public health data and ethics keep you up at night?

DAVID

For me, the issues around public health ethics and data that keep me up at night are the unintended consequences, the consequences that we can’t see related to our actions and related to how we use data, and particularly the potential for harm. We have a lot of well-meaning people in public health, some of the best do-gooders, I think, on the planet. And yet, we don’t often see the potential for the unintended consequences of our actions.

Justice Brandeis of the Supreme Court in 1928 said

“The greatest dangers to liberty lurk in insidious encroachment by men of zeal, well-meaning but without understanding.”

VIVIAN

I think the piece that really keeps me up all night is that we haven’t quite figured it all out, that we need some more guidance around it to help all of us, you know, not just public health practitioners, but others that are in the game of Big Data. And maybe we need to come together in some way to put together some frameworks or templates around how we can make sure that we are doing the right thing, that we are doing good, and that we are bringing ethics into everything that we’re doing with this data. We need to make sure that the ethics discussion is at the table. Because it’s good to be well-meaning, but then you can’t take back, you know, the consequence of what happens, you know, maybe not tomorrow but well down the line. So we need to be more future-thinking as we continue to push the boundaries of data analytics, you know, with this whole Big Data movement.

DAVID

I agree. And I think the good news on this or the silver lining is that if we’re aware of unintended consequences, we’re aware that we don’t know, we can come together and find out. And if we’re not overly identified with ourselves as doing good, we can recognize when we’re doing harm and then make adjustments so that we avoid that in the future.

PIPER

That’s great. So just being constantly critical and aware of your own actions and their consequences?

DAVID

That’s right, yeah.

PIPER

That’s great.

DAVID

And maybe it’s having some people around us who help remind us to be critical, or who serve that function of being an irritant or a questioner. Those are not always pleasant people to have in your inner circle, but they serve a very good purpose.

PIPER

Is that advice that you would give to public health practitioners is find an irritant, and place them prominently in your organization?

DAVID

Well, Bill Foege used to say that, “You need naysayers to eliminate a disease. But keep them on as consultants rather than as employees, so you can listen to their advice when you need it, but you don’t have to hear it every day.”

PIPER

That’s good advice.

DAVID

I would say that it would be helpful to bring in the voices of people who are affected by the data. Have some Town Halls to present some of these challenges and get input from people who are living their ordinary lives day to day, and really get the input from them as to their concerns and the cautions that they would have for us.

PIPER

As we closed out the discussion, I asked both David and Vivian the question we ask all our guests—how they define public health informatics. You heard Vivian’s answer on the last episode. Here’s what David had to say.

DAVID

I see two parts of public health informatics. One is, it’s information. It’s not just data, so it carries meaning. And hopefully, that meaning is used to improve health outcomes. So this is information that is infused with the potential for health. But then there is informatics, and that’s the form of the data are automated. And they’re generally rapid, they can be manipulated, they can be sent around the world immediately and repurposed, and that raises the issue of ethics and the need to be vigilant about how the data are used.

PIPER

Thank you again to Vivian Singletary and David Addiss for taking the time to have this conversation with me! I so enjoyed venturing into the thorny and complicated world of health data ethics with both of you, and I hope all of our listeners did too.

This podcast is a project of the Public Health Informatics Institute, which is a program of The Task Force for Global Health. Visit phii.org to learn more about all of our informatics work! You can also find us on Facebook and follow us on Twitter @PHInformatics. The music used in this episode was composed by Kevin MacLeod.

As I mentioned on the last episode, we still want to hear from you on YOUR definition of public health informatics! Leave us your thoughts in a voicemail at our podcast call-in line, 678-974-0344, and we may use your answer on a future episode. That phone number will also be in the episode notes.

I’m Piper Hale, and you’ve been informed.

BUTTON

PIPER

Periodically, while we’re talking, you’ll just hear a burst of applause from the next room. Uh-oh, that’s not going to be easy to cut out of the audio!

VIVIAN

Gold stars!

PIPER

Right! You guys are just so good at talking about data ethics, that people are standing outside the room and applauding.