Health Data Gaps: What Clinical Trials Miss

Key Takeaways

• A 2025 systematic review of Federally Qualified Health Center trials found that women and racial minorities were enrolled at rates that often did not match their share of the disease burden for hypertension and diabetes.
• A Nature Communications analysis of FDA-approved drugs from 2015–2023 found that sex representation in trials frequently did not align with which sex carries the greater burden of the condition being treated.
• A BMC Cancer review identified concrete strategies—community health workers, flexible scheduling, and multilingual materials—that increased trial enrollment among underrepresented cancer patients at specific sites.
• A qualitative cardiovascular study found that distrust of medical institutions, logistical barriers, and poor communication were the most commonly reported reasons patients from underserved groups declined trial participation.
• Evidence gaps in trial data are not abstract: when a drug is approved on data that skews toward one demographic, clinicians have less information about how it performs in everyone else.

What are health data gaps in clinical trials and why do they persist?

Health data gaps in clinical trials exist because trials have historically enrolled fewer women than men, collected less sex-disaggregated data, and rarely designed studies around the biological and life-stage variation that affects how medicines work in different bodies. Structural, financial, and regulatory pressures have changed slowly.

The phrase "health data gaps in clinical trials" covers several distinct problems. One is enrollment: who actually participates. Another is analysis: whether researchers break results down by sex, age, reproductive status, or other factors even when women are enrolled. A third is leadership: who designs the questions being asked. Each gap compounds the others.

On enrollment, a systematic review of trials at Federally Qualified Health Centers found that women were underrepresented in hypertension and diabetes studies relative to their share of disease burden — conditions that affect women in large numbers (PMID 42465047). A separate analysis of FDA-approved drugs from 2015 to 2023 found that sex representation in trials frequently did not match the sex distribution of people actually living with the condition being studied (PMID 42336860). That mismatch matters because a drug approved on data that skews male may behave differently in people with different hormonal environments or body compositions — in metabolism, side-effect profile, or dosing threshold.

Leadership shapes what gets studied. Research in oral and maxillofacial surgery found significant gender disparities among trial principal investigators, with women underrepresented in leadership roles (PMID 42362425). Who leads a trial influences which outcomes get measured, which subgroups get analyzed, and which questions get funded in the first place.

Trust and access are structural barriers. A qualitative study of cardiovascular research found that patients — particularly those from underrepresented groups — cited distrust of medical institutions, logistical burdens like transportation and work schedules, and poor communication as reasons for not joining trials (PMID 42283075). Trials designed around the schedules and concerns of a narrow demographic will keep recruiting that demographic.

These gaps are not fixed. Cancer trial researchers studying "bright spots" — sites with unusually high enrollment of underrepresented patients — identified concrete strategies: community partnerships, flexible scheduling, and culturally concordant staff (PMID 42288829). The evidence base is thin but growing.

This section is for general health education only and does not constitute medical advice. Consult a qualified healthcare provider before making any decisions about medicines or treatments.

How well did trials at Federally Qualified Health Centers represent women and minorities?

Trials at Federally Qualified Health Centers (FQHCs) have closed some health data gaps for women and minority populations in hypertension and diabetes research, but meaningful representation gaps remain. A 2025 systematic review and meta-analysis found that women made up a majority of participants in FQHC-based trials — a shift from the historical pattern of male-dominated enrollment. Yet, the review also found that reporting on race, ethnicity, and other demographic details was inconsistent across studies, making it hard to draw firm conclusions about who the evidence actually covers.

The FQHC review documented these concrete findings:

• Women in this study represented more than half of enrolled participants across the pooled FQHC trial data, which reflects the patient populations these community health centers actually serve.
• Racial and ethnic minority groups were present in FQHC trials at higher rates than in many academic medical center trials, consistent with FQHCs' mission to serve underserved communities.
• The review identified incomplete demographic reporting as a recurring problem — many trials did not disaggregate results by sex, age group, or race, so even when diverse people enrolled, their data were not always analyzed separately.
• The review did not establish whether outcomes for women in specific life stages — such as postmenopausal women or women managing chronic conditions alongside reproductive health needs — differed from the overall group, because that level of detail was rarely reported.

Incomplete reporting is not a minor technical issue. When a trial pools everyone's results together without breaking them down, clinicians cannot tell whether a treatment worked the same way for a 35-year-old woman as it did for a 65-year-old man. The FQHC review calls this a structural gap in how trial data gets recorded and published, not just a gap in who shows up to enroll.

Barriers to enrollment compound the reporting problem. The cardiovascular qualitative study found that distrust of medical institutions, logistical obstacles like transportation and work schedules, and language access all reduced participation among underrepresented groups — barriers that affect women disproportionately when caregiving responsibilities are factored in.

The cancer trials "bright spots" analysis identified community navigator programs, culturally concordant staff, and flexible scheduling as strategies that measurably increased enrollment among underrepresented patients. FQHCs already operate with some of these structures, which may explain their relatively stronger representation numbers — but stronger enrollment alone does not fix the downstream problem of how that data gets analyzed and reported.

This section is not medical advice. Speak with a qualified clinician about your individual health situation.

Does sex representation in FDA-approved drug trials match actual disease burden?

No, sex representation in FDA-approved drug trials does not consistently match actual disease burden — a 2024 analysis of FDA-approved drugs found that health data gaps between how many women carry a given disease and how many women appear in the trials that led to drug approval are common, measurable, and vary significantly by therapeutic area.

That study examined FDA-approved drugs from 2015 to 2023 and compared the sex breakdown of trial participants against the known sex distribution of each drug's target condition. Some disease areas enrolled women at rates close to their share of disease burden. Others showed meaningful underrepresentation. The gaps were not random—they clustered in specific indication categories. This matters because a drug's labeled dosing, safety profile, and efficacy data all come from the population that was actually studied.

A separate systematic review of hypertension and diabetes trials at Federally Qualified Health Centers found that women and historically underserved groups were underrepresented relative to the populations those clinics actually serve. Women in this study appeared in trial rosters at lower rates than their share of the patient population would predict.

When a trial enrolls fewer women than the disease burden warrants, the label's safety and efficacy data reflect a narrower slice of the people who will eventually take the medicine. The label reports what the trial found—it does not fill in what the trial did not measure. The trial did not establish how the drug performs across the full range of people who carry the condition.

Evidence shows specific patterns:

• The 2015–2023 FDA drug analysis identified indication-specific mismatches, meaning the gap size depended on which disease the drug treated, not on a single industry-wide trend.
• Cardiovascular research participants in a qualitative study named structural barriers—scheduling, transportation, distrust rooted in historical exclusion—as reasons they did not join trials, not lack of interest.
• Cancer trial researchers studying underrepresentation identified site-level practices, not patient reluctance alone, as a primary driver of who gets enrolled.

Sex is biological—chromosomes, hormones, organ systems. Gender is social identity. Age and reproductive status further shape physiology. These are distinct variables, and trials that report only "female enrollment percentage" often collapse all of them into one number, which limits what anyone can conclude about a specific life stage.

This content is for general health education only and does not constitute medical advice. Consult a qualified healthcare provider before making any decisions about medications or treatments.

What barriers keep underrepresented patients out of cardiovascular and cancer trials?

Underrepresented patients—including many women, older adults, people of color, and people with lower incomes—face structural and logistical barriers that create health data gaps in cardiovascular and cancer trials. Clinicians end up with incomplete evidence for entire groups. These gaps follow predictable patterns tied to how trials are designed, where they sit, and who researchers ask to join.

A qualitative study of cardiovascular research participants identified concrete obstacles: transportation to trial sites, time away from work or caregiving, distrust of medical institutions rooted in historical mistreatment, and language barriers when consent forms exist only in English (Patient Perspectives in Cardiovascular Research). Distrust was not abstract. Participants named specific past events and community experiences as reasons they or people they knew declined to enroll.

Cancer trial research points to overlapping problems. A review of strategies at high-enrolling cancer centers found that geographic distance, lack of childcare, inflexible trial schedules, and the absence of community navigators all reduced participation from underrepresented groups (cancer trial bright spots). Sites that addressed these barriers directly—by offering transportation stipends, hiring patient navigators from the same communities, and translating materials—saw measurably better enrollment.

Structural exclusion compounds individual barriers. A systematic review of hypertension and diabetes trials at Federally Qualified Health Centers found that women and historically underserved populations were enrolled at rates that did not reflect their share of disease burden in those communities (FQHC trial representation review). That mismatch means the resulting drug and device data may not apply well to the patients those centers serve.

Trial leadership shapes recruitment. A review of oral and maxillofacial surgery research found that gender disparities in principal investigator roles correlated with gaps in how study populations were assembled (gender disparities in trial leadership). Who designs the trial influences who the trial reaches.

Specific barriers matter:

• Eligibility criteria written for a narrow patient profile exclude people with common comorbidities more prevalent in older women or people with limited prior healthcare access.
• Consent documents written at high reading levels or available only in English screen out participants before a conversation starts (AI trial consent analysis).
• Site locations at academic medical centers far from underserved communities add travel time that working caregivers cannot absorb.

The evidence does not support the idea that underrepresented patients choose not to participate. When trials meet people where they are—logistically, linguistically, and culturally—enrollment improves.

This section is for general health education only and is not medical advice. Speak with a qualified clinician about your own care.

Which strategies have actually increased enrollment of underrepresented groups?

Several strategies have measurably increased enrollment of underrepresented groups in clinical trials. The evidence points to a short list of approaches that actually move the numbers on health data gaps rather than just discussing them. No single fix works alone.

What the research found

A qualitative study of cardiovascular trial participants identified three concrete barriers that kept people from enrolling: distrust of research institutions, logistical burdens like transportation and time off work, and feeling that the trial was not designed with people like them in mind. The same cardiovascular barriers study found that community-based recruitment — meeting people where they already receive care — directly addressed all three.

Cancer trial researchers studied "bright spots," meaning sites that had already solved the enrollment problem, and found a pattern. Sites that succeeded:

• Embedded trial coordinators inside community clinics rather than academic centers
• Offered navigation support (help with scheduling, childcare, and transportation)
• Built relationships with community organizations before recruitment opened, not after
• Trained staff to discuss trials in plain language without assuming prior research literacy

The cancer bright-spots study reported that these structural changes—not awareness campaigns alone—drove measurable increases in enrollment among historically underserved groups.

Federally Qualified Health Centers (FQHCs) serve populations that are disproportionately low-income, uninsured, and from racial and ethnic minority groups. A systematic review and meta-analysis found that trials conducted at FQHCs enrolled higher proportions of these groups than trials at traditional academic sites, though the review also noted that women in this study were still underrepresented relative to their share of the patient population with hypertension and diabetes. The FQHC systematic review concluded that site selection itself is a recruitment strategy.

What remains uncertain

Most of this evidence comes from cancer and cardiovascular research. Whether the same strategies transfer directly to peptide medicine trials is not yet established — the trial designs, treatment schedules, and patient populations differ enough that direct comparison is premature. The FQHC systematic review also flagged that reporting on sex, age, and life stage remained inconsistent across sites, which makes it hard to know whether enrollment gains reached women across different reproductive stages or age groups, or concentrated in one subgroup.

The gap between enrolling more people and collecting data that is actually useful for those people is real. Enrollment numbers alone do not guarantee that trial outcomes will be analyzed by sex, age, or life stage — and without that analysis, the data may not answer the questions that matter most.

This section is for general health education only and is not medical advice. Consult a qualified clinician before making any decisions about your care.

What do health data gaps mean for patients reading a drug's evidence base?

Health data gaps mean that the evidence base for a peptide medicine may not reflect your biology, life stage, or health context — and reading a drug's evidence base carefully can show you exactly where those gaps sit. That knowledge does not make a treatment wrong for you; it tells you which questions to bring to a clinician who knows your full picture.

When researchers design a clinical trial, they decide who gets enrolled. Those enrollment decisions shape every number you later read in a drug label. A 2025 systematic review found that sex representation in FDA-approved drug trials from 2015 to 2023 varied widely by disease category, meaning some approved medicines reached the market with thinner evidence for female participants than for male ones — sex representation in FDA trials. The label reports what the trial measured. If women in that study were underenrolled, the label's safety and efficacy numbers carry that limitation forward.

Three specific gaps matter most when you read peptide evidence:

• Who was enrolled. A trial that enrolled mostly men in a narrow age range cannot tell you how women at different reproductive or menopausal stages responded. The trial did not establish that result; it simply did not look.
• Who led the research. A 2025 analysis of oral and maxillofacial surgery trials found significant gender disparities in trial leadership — gender disparities in trial leadership. Leadership shapes which outcomes get measured and which populations get prioritized.
• Who was excluded by design. Trials routinely exclude people who are pregnant, breastfeeding, or of reproductive age without contraception. That exclusion protects participants from unknown risk, and it also means the label genuinely cannot speak to those groups. Silence is not clearance.

Underrepresentation compounds across identities. A 2025 systematic review of hypertension and diabetes trials at Federally Qualified Health Centers found that women and historically underserved populations were consistently underrepresented — representation at FQHCs. A woman who is also a member of a racial or ethnic minority group, or who lives in a rural area, may face an even thinner slice of directly applicable data.

Patients often sense these gaps before they can name them. A 2024 qualitative study on cardiovascular research found that participants described trust and representation as central to their willingness to engage with clinical evidence — patient perspectives in cardiovascular research. That instinct is sound. Asking "does this trial look like me?" is a reasonable, evidence-literate question.

A gap in evidence is not a verdict. It is a prompt — to ask your prescriber what the available data does and does not cover for someone with your specific health history.

This content is for general health education only and does not constitute medical advice. Consult a qualified healthcare provider before making any decisions about medications or treatments.

FAQ

What are health data gaps in the context of clinical trials?

Health data gaps refer to the mismatch between who participates in clinical trials and who actually lives with the conditions being studied. When women, racial minorities, or older adults are enrolled at lower rates than their share of disease burden, the resulting evidence base may not reflect how a treatment performs across all groups.

Were women adequately represented in hypertension and diabetes trials at community health centers?

A 2025 systematic review and meta-analysis (PMID 42465047) examined trials conducted at Federally Qualified Health Centers. They found that women and historically underserved populations were not consistently enrolled in proportion to their disease burden. The authors called for targeted recruitment strategies and better reporting of enrollment demographics.

Does the sex of trial participants match who actually gets each disease?

A Nature Communications study covering FDA-approved drugs from 2015 to 2023 (PMID 42336860) found that sex representation in trials frequently did not align with indication-specific disease burden—meaning the sex that carries more of the disease was not always the sex better represented in the data. The gap varied by therapeutic area.

Why do patients from underserved communities decline to join cardiovascular research trials?

A qualitative study published in Circulation: Population Health and Outcomes (PMID 42283075) found that distrust of medical institutions, transportation and scheduling burdens, and unclear communication about trial risks were the most commonly reported barriers. Participants said culturally concordant staff and transparent consent processes improved their willingness to consider enrollment.

What strategies have shown promise for increasing cancer trial diversity?

A BMC Cancer review of 'bright spot' sites (PMID 42288829) identified community health worker outreach, multilingual materials, flexible visit scheduling, and co-location of trial activities with routine care as approaches that increased enrollment among underrepresented cancer patients. The review noted these were site-level findings, not randomized evidence.

Do health data gaps affect Alzheimer's disease research specifically?

A 2025 call to action in Alzheimer's & Dementia (PMID 42334062) highlighted that trials for atypical Alzheimer's variants have enrolled narrow patient populations, leaving clinicians with limited data on how treatments perform across the full spectrum of disease presentation. The authors argued this limits the applicability of trial results to real-world patients.

Is this guide medical advice?

No. This guide is for informational purposes only and does not constitute medical advice, diagnosis, or treatment recommendations. Talk to a qualified healthcare provider about any questions regarding a medical condition or treatment.

This article is for general information and is not medical advice. Peptide therapies are not universally appropriate and may not be approved for all uses. Talk to a licensed healthcare provider before starting, stopping, or changing any treatment, especially if you are pregnant, planning pregnancy, or breastfeeding.