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Most patients will never read the fine print at the end of a research article and will not see who wrote the grants, which company supplied the drug, or which committee approved the protocol, yet these quiet details shape who is invited into research, whose data are collected, and which bodies are considered too complicated or too risky to include. The result is an invisible economy in which funding streams, ethical guidelines, and institutional habits determine what knowledge medicine produces. Women’s health sits at the center of this problem, since questions about who funds research and how conflicts of interest are managed intersect directly with decisions about who is permitted to participate in clinical trials, especially people who can become pregnant, who are pregnant, or who are lactating. Together, these forces dictate not only what gets discovered, but also who is ultimately able to benefit from those discoveries.


The Money Behind the Medicine

Research depends on grants, infrastructure, and institutional support, and as Mandal and colleagues explain, funding can come from internal sources or from outside organizations such as governments, corporations, and nongovernmental groups, a mix that is never ethically neutral [1]. When sponsors have commercial interests in the outcome, pressure to produce favorable findings can shape which questions are asked and how results are presented, and hidden relationships or incomplete conflict-of-interest disclosure can weaken trust in scientific work. Mandal et al. argue for transparency and oversight rather than rejection of industry involvement, insisting that institutions and researchers manage funds responsibly and disclose how sponsorship may shape a study [1]. For women’s health, these concerns are especially important because funders who view pregnancy, lactation, or hormonal conditions as legally risky or scientifically inconvenient may avoid trials that include these groups, which limits the evidence base needed to care for patients whose physiology has long been understudied.


From Exclusion to Conditional Inclusion

Women, particularly those who were pregnant or could become pregnant, were historically excluded from research. ACOG traces this pattern to harms such as the thalidomide tragedy, after which regulators barred people of childbearing potential from many trials in an attempt to protect future children [2]. This approach meant that drugs were tested almost entirely in nonpregnant bodies and then prescribed during pregnancy with little direct evidence to support their safety.


ACOG’s 2024 Committee Statement reframes this exclusion as an ethical failure rather than a safeguard. It argues that people who can become pregnant, who are pregnant, who are lactating, or who identify as women should be presumed eligible for research and that their inclusion is a matter of justice [2]. When these groups are left out, the benefits of research are distributed unfairly and the risks shift to patients who must make decisions without reliable data. Exclusion does not remove risk but instead relocates it, since clinicians still have to prescribe medications during pregnancy and often must rely on estimation rather than evidence.


Autonomy and the Conditions Placed on Participation

Ethics committees and funding bodies often impose conditions such as mandatory contraception or extra consent requirements, and ACOG argues that when these rules apply only to people who can become pregnant, they are paternalistic and discriminatory because they imply that one group’s autonomy is less trustworthy than others [2]. This creates a distribution problem as well as a procedural one. When restrictive criteria determine which studies receive funding, pregnant and lactating people are often excluded from participation, which means the evidence base skews toward nonpregnant bodies and later shapes clinical guidelines and insurance coverage.


Mandal et al. point out that funding structures influence how research questions are framed, while ACOG shows how ethical rules around inclusion and consent can either reinforce or challenge those pressures [1, 2]. Together they reveal a cycle in which funding influences protocol design, protocol design determines who can participate, and participation patterns shape which bodies medicine understands and knows how to treat.


Reimagining an Ethical Research Economy for Women’s Health

When pregnant or lactating people are systematically excluded from research, clinicians frequently must improvise when treating asthma, depression, autoimmune disease, or pregnancy-specific complications. This improvisation can lead to extra visits, off-label prescribing, and higher costs. The financial burden that patients experience often reflects earlier decisions made by grant reviewers and ethics committees.


A more ethical research landscape would place justice, transparency, and respect for participants at the center of funding decisions. Mandal et al. remind us that every source of support requires clear oversight and honest disclosure [1], while ACOG shows that people who can become pregnant should be actively included in studies rather than sidelined [2]. The hidden economy of medicine is ultimately about whose experiences shape scientific knowledge and whose needs are left unsupported. If research is to serve all patients, the choices made long before a study begins must reflect that responsibility.


Designed by: Julia Williams


References:

[1] Mandal, J., Parija, M., & Parija, S. C. (2012). Ethics of funding of research. Tropical parasitology, 2(2), 89–90. https://doi.org/10.4103/2229-5070.105172


[2] American College of Obstetricians and Gynecologists. Ethical considerations for increasing inclusivity in research participants. Committee Statement No. 9. Obstetrics & Gynecology. 2024;143:e155–63.

 
 
 
  • Pranav Kannan
  • Nov 17
  • 3 min read
ree

When a new surgical device in the OR gets FDA approved, it sounds like the end of the medtech

innovation journey. In reality, it’s only the point where the science part ends and the money part begins.

To actually appear in patient care and on a hospital bill, the device must pass through multiple quality

control gates.


Stage 1: The FDA gate

The FDA’s job is to determine whether a device is safe and effective for sale [1,2,3]. Most devices reach the market through three pathways. A 510(k) submission shows that the device is equivalent to an existing device in the market [1]. A De Novo is used for novel low- to moderate-risk devices that don't have a predecessor, so it employs a risk-based review [2]. Finally, Premarket approval (PMA) is reserved for high-risk medical devices and requires the most extensive research to be approved [3].


These are not just labels; they also correspond to product development costs. An economic analysis found that bringing a device to market through the 510(k) pathway costs approximately $31 million on average, while a high-risk PMA costs around $94 million [4,5]. Most of the spending is tied directly to FDA related testing stages, such as bench, human factors, and clinical studies. Early phases can be supported by grants through the National Institutes of Health (NIH); however, later stages are usually financed by investors who expect to recover their costs once medical devices are used in procedures [6].


Stage 2: The payer gate

FDA approval alone doesn’t guarantee that anyone will pay for the device. US reimbursement is vital to the medical device market and comprises three key facets: coverage, coding, and payment [7,8].

  • Coverage: Inquires whether Medicare/Medicaid or private insurers will cover the device or procedure, and if this product is medically necessary. [7,8,16]

  • Coding: asks whether the device and procedure used can be recorded on a claim form using systems such as Current Procedural Terminology (CPT) codes for services and HCPCS codes for devices and supplies.[7-10]

  • Payment: determines how much money flows when specific codes are used [7,8,16]


If any one of these pieces is missing from device proposals, the device can be clinically excellent and FDA cleared, but it will rarely be used, and hospitals cannot cover their costs.


A recent example of this process is the application of AI/ML methods in medicine. The FDA now lists

hundreds of AL/ML devices authorized for marketing; however, adoption in everyday practice is uneven,

and numerous policy discussions highlight limited reimbursement as a significant barrier to use [11-16].


Grants and investors fund the evidence needed for an FDA review, after which the FDA decides which

devices can be approved for the market. Finally, CMS (Medicare/Medicaid) and private insurers

determine which devices can be realistically used in hospitals. In the end, what reaches the OR isn’t just

what works in the lab, but what survives this financial and regulatory marathon from grant to bill.


Designed by: Julia Williams


References:

[1] U.S. Food and Drug Administration. (n.d.). Premarket Notification (510(k)). https://www.fda.gov/medical-devices/premarket-submissions-selecting-and-preparing-correct-sub

mission/premarket-notification-510k


[2] U.S. Food and Drug Administration. (n.d.). De Novo Classification Request. https://www.fda.gov/medical-devices/premarket-submissions/de-novo-classification-request


[3] National Institutes of Health (NIH), SEED. (n.d.). FDA Authorization for High-Risk or Novel Devices. https://seed.nih.gov


[4] StarFish Medical. (n.d.). How Much Does It Cost to Develop a Medical Device? https://starfishmedical.com


[5] Focused Ultrasound Foundation. (n.d.). Why It Takes So Long to Develop a Medical Technology –Part 14. https://www.fusfoundation.org


[6] National Institutes of Health (NIH), SEED. (n.d.). Small Business Program Basics: Understanding SBIR and STTR. https://seed.nih.gov


[7] National Institutes of Health (NIH), SEED. (n.d.). Reimbursement Knowledge Guide for Medical Devices. https://seed.nih.gov


[8] Centers for Medicare & Medicaid Services. (n.d.). CMS Guide for Medical Technology Companies and Other Interested Parties. https://www.cms.gov


[9] American Medical Association. (n.d.). CPT® Overview and Code Approval. https://www.ama-assn.org


[10] Centers for Medicare & Medicaid Services. (n.d.). Healthcare Common Procedure Coding System (HCPCS). https://www.cms.gov


[11] U.S. Food and Drug Administration. (n.d.). Artificial Intelligence/Machine Learning (AI/ML)-Enabled Medical Devices. https://www.fda.gov


[12] Joshi, G., et al. (2024). FDA-approved artificial intelligence and machine-learning-enabled medical devices: An updated landscape. Electronics, 13(4), 498. https://doi.org/10.3390/electronics13040498


[13] Muralidharan, V., et al. (2024). A scoping review of reporting gaps in FDA-approved AI devices. PubMed Central (PMC). https://www.ncbi.nlm.nih.gov/pmc


[14] Wu, K., et al. (2024). Characterizing the clinical adoption of medical AI devices using real-world Medicare claims. NEJM AI. https://ai.nejm.org


[15] Adler-Milstein, J., et al. (2024). Meeting the moment: Addressing barriers and facilitating clinical adoption of artificial intelligence in medical diagnosis. National Academy of Medicine. https://nam.edu


[16] Medicare Payment Advisory Commission. (2024). Paying for software technologies in Medicare: Report to the Congress. https://www.medpac.gov


 
 
 
  • Neil Nimmagadda
  • Nov 17
  • 2 min read

ree

The first thing that often comes to mind for most when considering medical research is the exciting new frontier of discovery. Billion-dollar investments and cutting-edge projects that advance understanding of medical systems usually make headlines. However, recent events have resulted in a significant shift as hospitals and academic medical centers across the country are announcing layoffs and hiring freezes. This wave may be attributed to cuts to federal research grants and reimbursements. 


For instance, the Vanderbilt University Medical Center (VUMC) has announced 650 layoffs as part of an overall effort to reduce operational costs by more than $300 million. VUMC has cited “budgetary actions in Washington, D.C. related to government-sponsored research and patient care” as driving these decisions [2]. This cost-cutting response is evident across the board. According to the Association of American Medical Colleges (AAMC), 1,183 grants to U.S. medical schools and hospitals have been terminated, resulting in an approximate $2 billion cut in funding, which may slow the pace of patient-focused innovation and intervention [3]. 


It is often unclear to the public how much research funding influences hospital operations. Grant funding doesn’t just buy laboratory equipment; it also helps sustain the expansive infrastructure that supports academic medicine, including laboratory technicians, clinical trial operations, and shared data systems for patient health information. The importance of federal funding for patient care cannot be overstated. In response to funding cuts, hospital associations, such as the Washington State Hospital Association, have spoken out about how “reduced federal grant support could affect access to maternal care, opioid addiction prevention, rural staff training, and other hospital services,” thereby significantly affecting equitable access to care [1]. 


Thus, for patients, there are direct, cascading effects that may increase their financial burden. Fewer staff result in longer waits, reduced preventive outreach, and slower clinical progress. These effects accumulate over time, especially at academic hospitals that heavily rely on federal funding and reimbursement. 

The current funding cuts have revealed the subtle truth that research dollars not only fund scientific discovery but also support stability for patient populations. Every funding decision has a resounding impact on who gets care and at what cost. As policymakers, institutions, and even voters navigate this shifting landscape, it is important to recognize the ripple effects that reach far beyond laboratory settings to the hospital setting. Sustained investment ensures that medical care and progress remain accessible to all.


Reviewed by: Ayan Jung

Designed by: Nicholas Wang


References:

[1] How NIH funding cuts Will Impact Hospitals and universities. Advisory Board. (2025, February 12). https://www.advisory.com/daily-briefing/2025/02/12/nih-cuts 


[2] Muoio, D. (2025, June 23). Vanderbilt University Medical Center announces 650 layoffs, $300m-plus budget cut. Fierce Healthcare. https://www.fiercehealthcare.com/providers/vanderbilt-university-medical-center-announces-650 -layoffs-300m-budget-cut 


[3] The impact of federal actions on academic medicine and the U.S. Health Care System. AAMC. (2025, June 11). https://www.aamc.org/about-us/aamc-leads/impact-federal-actions-academic-medicine-and-us-health-care-system

 
 
 

DMEJ

   Duke Medical Ethics Journal   

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