Imagine the situation: a loved one needs an organ transplant, but even with insurance, the costs are overwhelming. Crowdfunding platforms like GoFundMe and Fundly are increasingly used to bridge the gap in these moments of critical need. But does everyone have equal success on these platforms? This new study dives deep into the issue, exploring whether racial disparities affect crowdfunding outcomes and how that impacts patients seeking life-saving transplants.

Crowdfunding as a “Digital Safety Net”

Medical crowdfunding has been called a “digital safety net,” offering hope for individuals grappling with hefty medical bills. For those facing organ transplantation, it becomes more than just a financial lifeline; it’s often the only way to cover necessary expenses outside of insurance coverage, such as travel, accommodation, and caregiver support. But what happens when success on these platforms appears influenced by factors beyond just need?

The Study’s Unique Approach: Crowdfunding, Race, and Health Needs

The researchers of this study analyzed data from nearly 20,000 U.S.-based crowdfunding campaigns dedicated to organ transplants. Using an algorithm to infer race and ethnicity based on names and locations, the team categorized these campaigns to examine differences in success rates among White, Black, and Hispanic campaigners. They also looked at variables like state-level uninsurance rates and transplant waiting list statistics to better understand disparities across racial and ethnic groups.

Key Insights: Patterns, Need, and Campaign Success

The results show some noteworthy patterns:

• Fundraising Gaps by Race: Black and Hispanic campaigners, on average, raised less than their White counterparts and were less likely to meet their fundraising goals.
• Regional Needs: Crowdfunding campaigns in states with high uninsurance rates varied, suggesting that where you live and your access to insurance can impact the success of your campaign.
• Organ-Specific Needs and Waiting Lists: Black campaigners were more likely to be associated with higher rates of organ waitlist additions, hinting at a heightened need for transplants in this group.

Why These Findings Matter

These disparities aren’t simply statistics; they represent real lives affected by gaps in financial support. For policymakers, this data may open discussions about alternative support structures and potential reforms in health coverage that could lessen the need for medical crowdfunding altogether.

Beyond the Data: Questions for Future Exploration

The study leaves us with plenty to think about. For instance, are there ways to make medical crowdfunding more equitable? Could health systems collaborate with crowdfunding platforms to provide a more secure safety net? And, on a broader scale, what does the reliance on crowdfunding say about the gaps in our current health care system?

This study raises critical questions without definitive answers, leaving us to ponder: is medical crowdfunding just a bandage for a much larger issue?

The role of race and ethnicity in health care crowdfunding: an exploratory analysis 

Sara Machado, Beatrice Perez, Irene Papanicolas 

Health Affairs Scholar, Volume 2, Issue 3, March 2024, qxae027, https://doi.org/10.1093/haschl/qxae027

Published: 28 February 2024

Abstract :

Medical crowdfunding is a key source of financing for individuals facing high out-of-pocket costs, including organ-transplant candidates. However, little is known about racial disparities in campaigning activity and outcomes, or how these relate to access to care. In this exploratory, nationwide, cross-sectional study, we examined racial disparities in campaigning activity across states and the association between US campaigners’ race and ethnicity and crowdfunding outcomes using a novel database of organ-transplant–related campaigns, and an algorithm to identify race and ethnicity based on name and geographic location. This analysis suggests that there are racial disparities in individuals’ ability to successfully raise requested funds, with Black and Hispanic campaigners fundraising lower amounts and less likely to achieve their monetary goals. We also found that crowdfunding among White, Black, and Hispanic populations exhibits different patterns of activity at the state level, and in relation to race-specific uninsurance and waitlist additions, highlighting potential differences in fundraising need across the 3 groups. Policy efforts should consider not only how inequalities in fundraising ability for associated costs influence accessibility to care but also how to identify clinical need among minorities.

Fig 1. waiting-list addition

Namsor API was used for crowdfunding campaigner race and ethnicity classification :

We assigned 1 of 4 race/ethnicity categories to the crowdfunding campaign organizer using the NAMSOR classifier: White non-Hispanic, Black non-Hispanic, Hispanic, and Other non-Hispanic. Onomastic classifiers are increasingly used to characterize individuals’ race and ethnicity (and potentially gender) when the information is not directly available from the subject. We use NAMSOR API, a commercially available classifier (https://namsor.app/), as it computes the probability of the 2 most likely race/ethnicity pairs using 3 elements—first name, last name, and zip code—and it has been evaluated as having high accuracy among similar tools. The race/ethnicity categories map onto the classifications provided by the Centers for Disease Control and Prevention (CDC) WONDER database.
The geographical element is important to improve accuracy and harnesses the geographic information in our data. The first and last names of the campaign organizer were collected directly from the campaign data, and the campaign organizer’s self- reported “city, state” was used to assign the relevant zip code(s) information using the US Cities List database. We ran the NAMSOR classifier for all “first name, last name, zip code” sets in the data and recorded the estimated probability for the most likely race/ethnicity for each campaign. We assigned a single race/ethnicity category to each campaign organizer, based on their highest estimated probability. If, based on a set of zip codes, a campaign was assigned more than 1 possible race/ethnicity (n = 1354, 6.9% of the campaigns), we
computed the race/ethnicity score as a weighted average of the estimated race/ethnicity probabilities identified by NAMSOR. For example, consider 1 campaigner who was assigned 10 possible zip codes, 7 of which identifying “White” as the most likely race/ethnicity: their score is the weighted average of 7 “White” estimated probabilities, where the weight is the proportion of “White” outcomes, in this case 7 of 10.
As this could potentially introduce a bias in the classification, we conducted a sensitivity analysis using an alternative classification procedure that simply chooses the race/ethnicity according to the highest estimated probability across all possible zip codes to assess whether alternative procedures led to substantial classification disparities, considering the limitation of dealing with classifiers with less than 100% certainty (see Supplementary Analysis including Supplementary Figure 3-6 and Supplementary Table 9 for the results).

Image credits : DALL-E illustration for the scientific paper titled “The role of race and ethnicity in health care crowdfunding: an exploratory analysis”. Text credits : study was summarized by ChatGPT.

About NamSor

NamSor™ Applied Onomastics is a European vendor of sociolinguistics software (NamSor sorts names). NamSor mission is to help understand international flows of money, ideas and people. We proudly support Gender Gap Grader.