Date: August 25, 2022
Rachel Breslau (RB): How did you get involved in health economics and outcomes research?
NO: I didn't go to school saying, I'm going to be a health economist. I went to MIT for undergrad and studied math and then went to grad school at Columbia University for operations research. Operations research originated with manufacturing processes. It's using math to figure out the most efficient way to do something—for example, how to set up the queues in a shop to optimize how long people wait. A lot of operations research is applied in airlines scheduling, manufacturing and logistics, and supply chain management. Before I went into that program, I did an internship at Daimler Chrysler, which is a car manufacturing company. I was using math to figure out what features to put in cars by looking at what people want in a car and how much they'll pay for it. The department at Colombia was pretty theoretical and I wanted to do something more hands on and practical. After the grad program, I came back to Boston and, in a roundabout way, I ended up connecting with Peter Neumann. We talked about the kind of decision modeling that's done in the healthcare setting and it seemed much more interesting than other applications that I had tried before. I went to work with Peter on the Cost-Effectiveness Analysis (CEA) Registry and conduct research. After that, I worked on health economic issues at a medical device manufacturer and then at a consulting company. Eventually, I got tired of consulting because you don't have the ability to get really in depth. Consulting moves fast. People want quick answers to something and then you move on to the next project. I went back to work with Peter- he was here at CEVR at that point. When I decided that I wanted more independence with my research, I started the PhD program in Clinical and Translational Science at Tufts.
RB: What are you working on right now?
NO: I work on a project looking at outcomes of people with Alzheimer’s disease by racial and ethnic group. It’s important for me to keep in mind my identity as a White researcher when doing this work. We've made a good start with our research, but more work needs to be done to understand the actions that can be taken to mitigate the differences that we're finding. And we're certainly finding differences, which represent some real inequity and under service for certain racial and ethnic groups. I hope that we can get deeper into this work, build new collaborations, and go beyond just publishing studies. What I find motivating is the idea that our research can lead to some kind of improvement in practice and to people actually getting better access to services.
I’m also involved in a partnership with an analytics group within the Tufts Medicine health system. I’m excited to contribute my research expertise to help answer questions and improve care delivery for patients, and I really like working with people from different roles and backgrounds – doctors and clinicians, administrators, analysts.
One of my other projects looks at uncertainty in health technology assessments (HTAs). We're examining whether one HTA body does a good job representing uncertainty in its cost-effectiveness estimates. We’re also exploring the agreement between experts’ judgement on uncertainty assumptions and what kind of judgments on uncertainty affect cost-effectiveness estimates and to what extent. We've been working on case studies with external experts to elicit their judgments on uncertainty. We're doing five case studies. We've completed one and we're in progress on the rest. So at this point I don't really know what our findings will be—I’m excited to see.
Finally, I’m looking at how personal characteristics that can be predicted—like how effective a treatment might be for an individual—can inform cost-effectiveness analysis (CEA). CEAs have typically been conducted at the population level. And within the population, especially for some conditions, there's a lot of heterogeneity. For example, the risk of a disease might be very different for different people. And it might be different in a way that we can predict based on a person's characteristics. We can use a model to input a person's characteristics and get certain information that can be used for CEA. There's a lot of work being done on using prediction models to inform doctor and patient decision making about a course of treatment. It's tricky with the way the US healthcare system works but I think it can be informative and useful to make these more personalized economic estimates.
RB: What advice do you have for those who are new to health economics and outcomes research?
NO: I would suggest you explore because this is a big field with many different ways of looking at things. I've had experiences in different settings and the work I’ve done and the kinds of research questions I’ve answered have been very different. I think it's really good to talk to people with different backgrounds to get a broader perspective on the field. And I would also suggest building a strong understanding of how the healthcare system works in your country of interest, because that healthcare system affects basically everything that happens.
RB: Do you have a memory from your time at CEVR that stands out to you?
NO: The holiday parties at Peter’s house. One year we did a Boston Harbor cruise. Just hanging out with all the CEVRs.
RB: Where did you grow up?
NO: I grew up in Russia. When I was 14, my parents and I moved to the United States and we lived in Richmond, Virginia. After that I went off to college in the northeast and pretty much stayed there.
RB: What do you do when you're not doing research?
NO: I have a lot of interests and not enough time to do them. First of all, I own a house and I have two kids. So that's another full time job. I love gardening. And I love to sing. I've been doing choral singing since high school. I've also been learning the piano. I enjoy being outdoors, going on hikes or going swimming or biking. I like to play tabletop games with friends. I also enjoy crocheting or doing other crafts.