Experts Discuss How Expanding Traditional Value Frameworks Can Address Inequities in Health Outcomes

Expanding traditional value frameworks to include inequality and factors that contribute to this is the first step to addressing disparities in health outcomes. Utilizing multi-criteria decision analysis and distributional cost effect analysis can assist in deriving data and subsequently acting on these issues, said Jason Shafrin, vice president of Health Economics at PRECISIONheor, and Meena Venkatachalam, senior director of Health Economics at PRECISIONheor.

Transcript

AJMC®: Hello, I'm Matthew Gavidia. Today on the MJH Life Sciences’ Medical World News, The American Journal of Managed Care® is pleased to welcome Meena Venkatachalam, senior director of Health Economics at PRECISIONheor,

and Jason Shafrin, vice president of Health Economics at PRECISIONheor. Can you both just introduce yourselves and tell us a little bit about your work?

Venkatachalam: Hi, this is Meena Venkatachalam, as you mentioned I am the senior director at PRECISIONheor. My background is in health economics, and I'm actually based in our London office. I work a lot on cost development of cost effectiveness models for the purpose of HTA submissions.

Shafrin: Great, I'm Jason Shafrin, and I'm a vice president at PRECISIONheor. My background is also a health economist–I'm also the founder and editor of the health care economist blog.

AJMC®: Amid the pandemic, disproportionate access to care and severe COVID-19 outcomes have been spotlighted in minority communities, especially among Blacks and Hispanics. Can you both speak on some factors that contribute to these disparities?

Venkatachalam: Sure, I think there's obviously a number of factors that are contributing to that, but I think few of the obvious ones that I think people are most aware of is 1, access to health care. Obviously, there's differences in insurance coverage. We pointed that out in our piece. Some statistics show that there's actually about 13 years difference in health insurance coverage between African American population and other minority groups.

So, obviously, when you've got that financial pressure of accessing care, that can lead to differences in outcomes as well; but beyond just the financial pressure and coverage of insurance, I think there's also barriers to access. So, if you think about factors like ease of transportation, childcare, having a job that's flexible enough for you to go see a physician–all of those are also factors that are barriers to access.

I think another factor, which is that even if those 2 weren’t at play and it wasn't about health insurance coverage and it wasn't about access, there's also increased risk of exposure. There are some statistics that show that minority groups are more likely to be in essential working jobs. So, that puts them at a higher risk. Also, culturally, they could be in homes with larger families, communal living, smaller housing, all of that increases your risk of exposure.

So, I think all of these factors at play–it's hard to pinpoint which 1 it is specifically, whether they’re cumulative or additive, but there are a lot of things at play that are specifically affecting the minority population versus other ethnic groups.

Shafrin:I think 1 thing just to add on, certainly just kind of waiting times and access even if you do have insurance–Meena mentioned the social determinants of health, but I think there's been some studies that show that for Medicaid patients the wait times just to get into the doctor's office were 20% longer. So, certainly care access once insurance is important.

AJMC®: How can the current health care system better address health-related issues prominent in minority populations? Especially when it comes to clinical trial participation on novel therapies?

Shafrin: So, I think really for this 1 clinical trial participation is pretty important along 2 dimensions. So, the first is we’re going to be investigating a disease, and you want to make sure that the trial is representative in terms of authentically, racially, culturally, socioeconomic status of that disease. I think that's a bit more straightforward.

The second dimension, though, is you want to ensure that the drugs in the pipeline are representative of the diseases that are affecting the whole population. The FDA actually has an annual snapshot where they compare enrollment in clinical trials in the previous year, against the racial and ethnic composition of the country as a whole, age groups, gender, etc.

So, that's kind of a helpful first step to just kind of keep track of what we're doing, but also it's important to incentivize getting people to develop those treatments and that's where having value assessment frameworks that incorporate inequality into those are important for getting those incentives.

Venkatachalam: Yeah, I think I echo the same comments. I think research and development right now reflects the incentives that are there for the pharmaceutical industry and value frameworks stay quite close. The incentives are smaller to invest in therapeutic areas that impact minorities. So, I think a lot of what we're writing about and talking about now is how to sort of expand that. So, you do incentivize it because I think unless there is that it's hard to get research and development to really match the needs.

AJMC®: Beyond research and development issues, there is a notable gap in traditional value frameworks that would consider a treatment’s impact on improving equity in health outcomes in disadvantaged communities when it comes to incentivizing reimbursement. Can you speak first, Meena, on what an ideal framework would entail and how it can be incorporated into the current US health care delivery system?

Venkatachalam: Yeah, I think our papers are speaking about what the ideal framework would be right now–it's not measured. If you really look at ICER, even beyond the US, it's not really considered at all equity concerns. So, I think the first baby step in this process is actually getting value frameworks that actually consider equity. So, 2 of the approaches that we've mentioned are multicriteria decision analysis and distributional cost effect analysis, which actually formally include impact on equity as a criteria in the model. So, it expands the traditional framework.

So, I think, unless you can measure something, you can't make decisions on it, and right now, we're not measuring it at all. So, I think an ideal framework is at least making that first step to measure this impact and the value of a drug on these issues.

Shafrin: I think really getting at the ideal–Meena mentioned some of the methods with the distributional cost effectiveness and then multicriteria decision analysis (MCDA) and I think some of those kind of ideals are–the distributional cost effectiveness, you kind of have 1 number that can be helpful for people that incorporates inequality. For the MCDA approach, for people who are a bit more active and they want to see–well, I want to prioritize overall health gains or side effects or costs or inequality–you can do that a bit more in an evolved way.

So, I think there's not 1 kind of ideal way to do that, but I think Meena’s right that getting the tools there, and at least starting to incorporate the value of reducing inequality is extremely important.

AJMC®: Jason you can go first here, what further steps are warranted to address inequalities in health outcomes among minority communities?

Shafrin: I think that's a question for a 3-hour long seminar symposium. Certainly a big issue, I think, just really kind of narrowing it down to in terms of new treatment development, really getting the MCDA methods that are really well known in academia and getting those implemented. The reason is not just–I'm a health economist by training, it's not just to do it for technical reasons and because it's fun, but it's really because we want to incentivize life sciences to create treatments that will improve health outcomes for disadvantaged communities.

Really, by doing that, and saying, hey, if you have a treatment that improves health, that's great, but if you have it for disadvantaged communities that are really having poor health outcomes, that's even better–that will really put the right incentives in place and allow people to make explicit trade-offs to incorporate those.

Venkatachalam: I think sometimes what people might see is this is too far of a jump, like this is just an academic piece and it's too far to think about actually applying this in a real world setting; but I don't think this is an uncommon trend. We've been in a situation before where academic groups respond to a gap and a need where we're lacking something. There's methods that are well published, well validated, they're just not being used and I think our kind of piece right now is let's use them more. We don't need to reinvent the wheel, it exists.

It's measuring the impact on equity. So, if we use this and we can get decision makers to be a little bit more accepting of it, and that trend is consistent, that kind of cycle of innovation is pretty common in our type of work.

AJMC®: Lastly, do either of you have any other concluding thoughts?

Shafrin: I think for me, I mean, I think the problem is certainly high, it's multi dimensional, and life sciences, drug development is just 1 piece. Certainly a piece that's near and dear to my heart and the research that I do, but certainly a multi factorial issue that we need a lot of hands on deck to help to improve health outcomes for disadvantaged communities.

Venkatachalam: I think we're somewhat limited in what we can do with heor [health economics and outcomes research]research. We can’t influence investment in certain drugs directly, but I think our research can indirectly kind of nudge in the right direction. So, if we increase incentives to invest in these areas through value frameworks, that's 1 way to nudge and there's multiple ways to nudge. It may not address all of the issues, but it's 1 part of the puzzle that we can help address.

AJMC®: To learn more, visit our website at ajmc.com. I’m Matthew Gavidia, thanks for joining us!