Diabetes, obesity, heart failure, chronic kidney disease, and atherosclerosis often overlap, creating layered eligibility barriers that complicate patient enrollment in cardiometabolic trials. At the same time, breakthrough therapies such as GLP-1 receptor agonists and evolving standards of care are reshaping who qualifies for participation.
The result is that too many trials recruit slowly, overspend, and fail to reflect the real-world patients most affected by these conditions. For sponsors and contract research organizations, the implications are significant. Recruitment delays drive up development costs, prolong timelines to regulatory approval, and weaken the external validity of trial outcomes.1
This article offers strategies to accelerate recruitment and ensure representative enrollment. The formula is simple: design inclusive protocols, optimize site networks, engage patients through trusted channels, and use data and technology to track performance. First, it is essential to understand the barriers that slow enrollment.
Why Recruitment Stalls in Cardiometabolic Trials
Recruitment challenges in cardiometabolic trials arise from the intersection of biology, demographics, healthcare infrastructure, and market forces. Common obstacles include:
- Multi-morbidity meets narrow criteria. Many patients are excluded by rigid thresholds (HbA1c, BMI, eGFR, blood pressure) or polypharmacy. Reviews in type 2 diabetes show 40–60 percent screen failures, unless criteria are broadened (e.g., wider HbA1c ranges, allowance for co-medications).2
- Under-representation persists. Meta-analyses show participants from racialized groups remain underrepresented (participation-to-prevalence ratio <0.8) in type 2 diabetes and cardiovascular outcome trials, particularly in industry-funded studies.3
- Saturated site networks. In heart failure programs, average enrollment sits at 0.6–0.7 patients per site per month because numerous active sites are competing for the same pool.4
- Market dynamics shrink the pool. In metabolic-associated steatohepatitis and nonalcoholic steatohepatitis (i.e., progressive liver diseases linked with obesity and type 2 diabetes), median enrollment rates dropped 83 percent between 2012–2015 and 2020–2023 as competing studies and new therapies narrowed eligibility.5
- Site operating friction is real. Academic research units face staff shortages, competing clinical duties, and infrastructure bottlenecks, slowing trial activation and patient accrual.6
While these obstacles are complex, sponsors who take a coordinated, multi-strategy approach can accelerate enrollment and improve representativeness.
Four Proven Strategies Shaping Patient Recruitment Success
Cardiometabolic recruitment requires coordinated, multi-lever solutions that align design, operations, patient engagement, and technology.
1. Rethink Study Protocols to Widen the Gate
Recruitment success starts with protocols that anticipate screen failures and adapt to real-world care create the foundation for inclusive trials.
Right-size eligibility.
- Simulate screen failures to assess relaxing eligibility thresholds (blood sugar, kidney function, BMI, background medications).
- Align with FDA guidance on inclusive designs; document protocol justifications.7
Add pragmatic elements.
- Use usual-care comparators, minimize extra visits, and allow remote assessments (blood pressure, weight, patient-reported outcomes).
- Heart-failure method papers show pragmatic designs boost feasibility without sacrificing rigor.3
Leverage community-based models.
- Adapt proven outreach models such as the “barbershop” study, where pharmacist-led hypertension care in barbershops significantly reduced blood pressure among Black men.8
2. Build Site Networks Where Patients Are
Even the best-designed protocol will fail without the right sites. Sponsors must balance academic excellence with community reach and provide the resources sites need to succeed.
Shift sites toward disease prevalence.
- Use claims and electronic health record (EHR) data to identify Federally Qualified Health Centers, safety-net hospitals, and community clinics serving underrepresented patients.9
- Partner with networks like Alliance Clinical Network to reduce startup friction and access diverse, high-performing sites.
Ensure pre-contract readiness.
- Provide EHR computable phenotypes and prescreening lists. The ADAPTABLE trial enrolled 15,000 patients via centralized EHR records and remote outreach, demonstrating scalability.10,11
Resource sites to accelerate timelines.
- Allocate targeted budgets (e.g., fund part-time recruiters or patient navigators) to directly enhance site speed and capacity.
- Establish micro–service level agreements (e.g., <72 hours from referral to first contact; <10 days from consent to first dose) to set expectations and accountability upfront.
3. Put the Patient Journey at the Center
Patients weigh convenience, trust, and burden when deciding whether to join a trial. Simplifying the journey and meeting participants where they are can make the difference between failure and success.
Reduce financial/logistical burden.
- Offer transportation, parking vouchers, childcare stipends, flexible hours, or mobile phlebotomy. AHA statements highlight logistics as key equity barriers.12,13
Use patient-centered communication.
- Provide plain-language, bilingual, culturally competent consent forms. Cardiovascular inclusivity frameworks stress the need for co-designed consent materials.8
Engage trusted local venues.
- Partner with churches, pharmacies, and community centers to reach patients with hypertension and metabolic syndrome. Community health workers and pharmacists can provide education and triage support.7,14
4. Use Data and Technology to Scale
Technology enables centralized screening, real-time monitoring, and digital access that expand reach without sacrificing inclusiveness.
Centralize prescreening.
- Build sponsor-run, IRB-approved hubs that push de-identified prescreen logs to trial sites.
- Use multi-modal outreach (e.g., email, SMS, phone, letters). The ADAPTABLE trial showed remote methods can scale across socioeconomic groups.15,16
Monitor representativeness in real time.
- Set enrollment targets for sex, race/ethnicity, age, and rurality (e.g., 0.8–1.2 participation-to-prevalence ratio). Launch remediation plans if subgroups lag.8
Adopt digital-first with safeguards.
- Offer eConsent, tele-visits, and home vitals for convenience, but provide in-person alternatives to avoid digital-access bias, especially in older or lower-income populations relevant in heart-failure and diabetes patient participants.17
Key Takeaway.
Cardiometabolic trials succeed when sponsors:
- Broaden eligibility
- Balance site networks between academic and community settings
- Simplify patient journeys
- Track inclusivity and performance.
Together, these strategies shift recruitment from a reactive, trial-by-trial struggle to a proactive, scalable model that balances speed with representativeness.
Helping Sponsors & CROs Succeed
Turning strategy into execution requires the right partner. At Alliance Clinical Network, we help sponsors move beyond traditional recruitment tactics and build trials designed for speed, inclusivity, and real-world relevance.
Our approach combines:
- Evidence-based diversity strategies to align enrollment with prevalence across age, sex, race, ethnicity, and geography.
- Optimized site networks that balance high-performing academic centers with strategically placed community sites.
- Patient-first processes that simplify journeys from referral to first dose and reduce trial burden.
- Continuous performance tracking to identify barriers early and keep recruitment and retention on pace.
To learn more about how Alliance Clinical Network can help accelerate your next trial, contact us.
1 Desai, Mira. Recruitment and retention of participants in clinical studies: Critical issues and challenges. Perspectives in Clinical Research 11(2):p 51-53, Apr–Jun 2020.
2 Currie, B.M., Howell, T.A., Matza, L.S. et al. A Review of Interventional Trials in Youth-Onset Type 2 Diabetes: Challenges and Opportunities. Diabetes Ther 12, 2827–2856 (2021).
3 Ahmed, R., de Souza, R. J., Li, V., Banfield, L., & Anand, S. S. (2024). Twenty years of participation of racialised groups in type 2 diabetes randomised clinical trials: A meta-epidemiological review. Diabetologia.
4 Greene, S, Velazquez, E, Anstrom, K. et al. Pragmatic Design of Randomized Clinical Trials for Heart Failure: Rationale and Design of the TRANSFORM-HF Trial. J Am Coll Cardiol HF. 2021 May, 9 (5) 325–335.
5Hardy, T., Delegge, M., Ionescu, G., et al. (2024). Insights into MASH clinical research: Enrollment amid increasing access to GLP-1 agonists (White paper). IQVIA.
6 Knapke JM, Snyder DC, Carter K, et al. Issues for recruitment and retention of clinical research professionals at academic medical centers: Part 1 – collaborative conversations Un-Meeting findings. Journal of Clinical and Translational Science. 2022;6(1):e80.
74 United States Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research. (2020, November). Enhancing the diversity of clinical trial populations: eligibility criteria, enrollment practices, and trial designs [Technical report]. U.S. Department of Health and Human Services.
8 Victor, R. G., Lynch, K., Li, N., et al. (2018). A cluster‑randomized trial of blood‑pressure reduction in Black barbershops. New England Journal of Medicine, 378(14), 1291–1301.
9 Zannad, F., Berwanger, O., Corda, et al. (2024). How to make cardiology clinical trials more inclusive. Nature Medicine.
10 O’Brien EC, Mulder H, Jones WS, et al. Concordance Between Patient-Reported Health Data and Electronic Health Data in the ADAPTABLE Trial. JAMA Cardiol. 2022 Dec 1;7(12):1235-1243.
11 Rymer JA, Mulder H, Wruck LM, et al. Contribution of Clinical Trial Event Data by Data Source: A Prespecified Analysis of the ADAPTABLE Randomized Clinical Trial. JAMA Cardiol. 2024 Sep 1;9(9):852-857.
12 Lopez, K. N., Baker-Smith, C., Flores, G., et al., & on behalf of the American Heart Association Scientific Statement Writing Group. (2022). Addressing social determinants of health and mitigating health disparities across the lifespan in congenital heart disease: A scientific statement from the American Heart Association. Journal of the American Heart Association, 11(8), e025358.
13 King S, Trabanino S, Azizi Z, Rodriguez F. Leveraging Social Determinants of Health to Enhance Recruitment of Underrepresented Populations in Clinical Trials. Methodist Debakey Cardiovasc J. 2024 Nov 5;20(5):81-88.
14 Islam NS, Wyatt LC, Ali SH et al. Integrating Community Health Workers into Community-Based Primary Care Practice Settings to Improve Blood Pressure Control Among South Asian Immigrants in New York City: Results from a Randomized Control Trial. Circ Cardiovasc Qual Outcomes. 2023 Mar;16(3):e009321.
15 Hau C, Efird JT, Leatherman SM, Soloviev OV, et al. A Centralized EHR-Based Model for the Recruitment of Rural and Lower Socioeconomic Participants in Pragmatic Trials: A Secondary Analysis of the Diuretic Comparison Project. JAMA Netw Open. 2023 Sep 5;6(9):e2332049.
16 Marquis-Gravel G, Roe MT, Robertson HR, et al. Rationale and Design of the Aspirin Dosing-A Patient-Centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE) Trial. JAMA Cardiol. 2020 May 1;5(5):598-607.
17 Cunningham, J. W., Abraham, W. T., Bhatt, A. S et al.; Heart Failure Collaboratory. (2024, November 12). Artificial intelligence in cardiovascular clinical trials. Journal of the American College of Cardiology, 84(20), 2051–2062.
Diabetes, obesity, heart failure, chronic kidney disease, and atherosclerosis often overlap, creating layered eligibility barriers that complicate patient enrollment in cardiometabolic trials. At the same time, breakthrough therapies such as GLP-1 receptor agonists and evolving standards of care are reshaping who qualifies for participation.
The result is that too many trials recruit slowly, overspend, and fail to reflect the real-world patients most affected by these conditions. For sponsors and contract research organizations, the implications are significant. Recruitment delays drive up development costs, prolong timelines to regulatory approval, and weaken the external validity of trial outcomes.1
This article offers strategies to accelerate recruitment and ensure representative enrollment. The formula is simple: design inclusive protocols, optimize site networks, engage patients through trusted channels, and use data and technology to track performance. First, it is essential to understand the barriers that slow enrollment.
Why Recruitment Stalls in Cardiometabolic Trials
Recruitment challenges in cardiometabolic trials arise from the intersection of biology, demographics, healthcare infrastructure, and market forces. Common obstacles include:
- Multi-morbidity meets narrow criteria. Many patients are excluded by rigid thresholds (HbA1c, BMI, eGFR, blood pressure) or polypharmacy. Reviews in type 2 diabetes show 40–60 percent screen failures, unless criteria are broadened (e.g., wider HbA1c ranges, allowance for co-medications).2
- Under-representation persists. Meta-analyses show participants from racialized groups remain underrepresented (participation-to-prevalence ratio <0.8) in type 2 diabetes and cardiovascular outcome trials, particularly in industry-funded studies.3
- Saturated site networks. In heart failure programs, average enrollment sits at 0.6–0.7 patients per site per month because numerous active sites are competing for the same pool.4
- Market dynamics shrink the pool. In metabolic-associated steatohepatitis and nonalcoholic steatohepatitis (i.e., progressive liver diseases linked with obesity and type 2 diabetes), median enrollment rates dropped 83 percent between 2012–2015 and 2020–2023 as competing studies and new therapies narrowed eligibility.5
- Site operating friction is real. Academic research units face staff shortages, competing clinical duties, and infrastructure bottlenecks, slowing trial activation and patient accrual.6
While these obstacles are complex, sponsors who take a coordinated, multi-strategy approach can accelerate enrollment and improve representativeness.
Four Proven Strategies Shaping Patient Recruitment Success
Cardiometabolic recruitment requires coordinated, multi-lever solutions that align design, operations, patient engagement, and technology.
1. Rethink Study Protocols to Widen the Gate
Recruitment success starts with protocols that anticipate screen failures and adapt to real-world care to create the foundation for inclusive trials.
Right-size eligibility.
- Simulate screen failures to assess relaxing eligibility thresholds (blood sugar, kidney function, BMI, background medications).
- Align with FDA guidance on inclusive designs; document protocol justifications.7
Add pragmatic elements.
- Use usual-care comparators, minimize extra visits, and allow remote assessments (blood pressure, weight, patient-reported outcomes).
- Heart-failure method papers show pragmatic designs boost feasibility without sacrificing rigor.3
Leverage community-based models.
- Adapt proven outreach models such as the “barbershop” study, where pharmacist-led hypertension care in barbershops significantly reduced blood pressure among Black men.8
2. Build Site Networks Where Patients Are
Even the best-designed protocol will fail without the right sites. Sponsors must balance academic excellence with community reach and provide the resources sites need to succeed.
Shift sites toward disease prevalence.
- Use claims and electronic health record (EHR) data to identify Federally Qualified Health Centers, safety-net hospitals, and community clinics serving underrepresented patients.9
- Partner with networks like Alliance Clinical Network to reduce startup friction and access diverse, high-performing sites.
Ensure pre-contract readiness.
- Provide EHR computable phenotypes and prescreening lists. The ADAPTABLE trial enrolled 15,000 patients via centralized EHR records and remote outreach, demonstrating scalability.10,11
Resource sites to accelerate timelines.
- Allocate targeted budgets (e.g., fund part-time recruiters or patient navigators) to directly enhance site speed and capacity.
- Establish micro–service level agreements (e.g., <72 hours from referral to first contact; <10 days from consent to first dose) to set expectations and accountability upfront.
3. Put the Patient Journey at the Center
Patients weigh convenience, trust, and burden when deciding whether to join a trial. Simplifying the journey and meeting participants where they are can make the difference between failure and success.
Reduce financial/logistical burden.
- Offer transportation, parking vouchers, childcare stipends, flexible hours, or mobile phlebotomy. AHA statements highlight logistics as key equity barriers.12,13
Use patient-centered communication.
- Provide plain-language, bilingual, culturally competent consent forms. Cardiovascular inclusivity frameworks stress the need for co-designed consent materials.8
Engage trusted local venues.
- Partner with churches, pharmacies, and community centers to reach patients with hypertension and metabolic syndrome. Community health workers and pharmacists can provide education and triage support.7,14
4. Use Data and Technology to Scale
Technology enables centralized screening, real-time monitoring, and digital access that expand reach without sacrificing inclusiveness.
Centralize prescreening.
- Build sponsor-run, IRB-approved hubs that push de-identified prescreen logs to trial sites.
- Use multi-modal outreach (e.g., email, SMS, phone, letters). The ADAPTABLE trial showed remote methods can scale across socioeconomic groups.15,16
Monitor representativeness in real time.
- Set enrollment targets for sex, race/ethnicity, age, and rurality (e.g., 0.8–1.2 participation-to-prevalence ratio). Launch remediation plans if subgroups lag.8
Adopt digital-first with safeguards.
- Offer eConsent, tele-visits, and home vitals for convenience, but provide in-person alternatives to avoid digital-access bias, especially in older or lower-income populations relevant in heart-failure and diabetes patient participants.17
Key Takeaway
Cardiometabolic trials succeed when sponsors:
- Broaden eligibility
- Balance site networks between academic and community settings
- Simplify patient journeys
- Track inclusivity and performance
Together, these strategies shift recruitment from a reactive, trial-by-trial struggle to a proactive, scalable model that balances speed with representativeness.
Helping Sponsors & CROs Succeed
Turning strategy into execution requires the right partner. At Alliance Clinical Network, we help sponsors move beyond traditional recruitment tactics and build trials designed for speed, inclusivity, and real-world relevance.
Our approach combines:
- Evidence-based diversity strategies to align enrollment with prevalence across age, sex, race, ethnicity, and geography.
- Optimized site networks that balance high-performing academic centers with strategically placed community sites.
- Patient-first processes that simplify journeys from referral to first dose and reduce trial burden.
- Continuous performance tracking to identify barriers early and keep recruitment and retention on pace.
To learn more about how Alliance Clinical Network can help accelerate your next trial, contact us.
1 Desai, Mira. Recruitment and retention of participants in clinical studies: Critical issues and challenges. Perspectives in Clinical Research 11(2):p 51-53, Apr–Jun 2020.
2 Currie, B.M., Howell, T.A., Matza, L.S. et al. A Review of Interventional Trials in Youth-Onset Type 2 Diabetes: Challenges and Opportunities. Diabetes Ther 12, 2827–2856 (2021).
3 Ahmed, R., de Souza, R. J., Li, V., Banfield, L., & Anand, S. S. (2024). Twenty years of participation of racialised groups in type 2 diabetes randomised clinical trials: A meta-epidemiological review. Diabetologia.
4 Greene, S, Velazquez, E, Anstrom, K. et al. Pragmatic Design of Randomized Clinical Trials for Heart Failure: Rationale and Design of the TRANSFORM-HF Trial. J Am Coll Cardiol HF. 2021 May, 9 (5) 325–335.
5Hardy, T., Delegge, M., Ionescu, G., et al. (2024). Insights into MASH clinical research: Enrollment amid increasing access to GLP-1 agonists (White paper). IQVIA.
6 Knapke JM, Snyder DC, Carter K, et al. Issues for recruitment and retention of clinical research professionals at academic medical centers: Part 1 – collaborative conversations Un-Meeting findings. Journal of Clinical and Translational Science. 2022;6(1):e80.
7 United States Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research. (2020, November). Enhancing the diversity of clinical trial populations: eligibility criteria, enrollment practices, and trial designs [Technical report]. U.S. Department of Health and Human Services.
8 Victor, R. G., Lynch, K., Li, N., et al. (2018). A cluster‑randomized trial of blood‑pressure reduction in Black barbershops. New England Journal of Medicine, 378(14), 1291–1301.
9 Zannad, F., Berwanger, O., Corda, et al. (2024). How to make cardiology clinical trials more inclusive. Nature Medicine.
10 O’Brien EC, Mulder H, Jones WS, et al. Concordance Between Patient-Reported Health Data and Electronic Health Data in the ADAPTABLE Trial. JAMA Cardiol. 2022 Dec 1;7(12):1235-1243.
11 Rymer JA, Mulder H, Wruck LM, et al. Contribution of Clinical Trial Event Data by Data Source: A Prespecified Analysis of the ADAPTABLE Randomized Clinical Trial. JAMA Cardiol. 2024 Sep 1;9(9):852-857.
12 Lopez, K. N., Baker-Smith, C., Flores, G., et al., & on behalf of the American Heart Association Scientific Statement Writing Group. (2022). Addressing social determinants of health and mitigating health disparities across the lifespan in congenital heart disease: A scientific statement from the American Heart Association. Journal of the American Heart Association, 11(8), e025358.
13 King S, Trabanino S, Azizi Z, Rodriguez F. Leveraging Social Determinants of Health to Enhance Recruitment of Underrepresented Populations in Clinical Trials. Methodist Debakey Cardiovasc J. 2024 Nov 5;20(5):81-88.
14 Islam NS, Wyatt LC, Ali SH et al. Integrating Community Health Workers into Community-Based Primary Care Practice Settings to Improve Blood Pressure Control Among South Asian Immigrants in New York City: Results from a Randomized Control Trial. Circ Cardiovasc Qual Outcomes. 2023 Mar;16(3):e009321.
15 Hau C, Efird JT, Leatherman SM, Soloviev OV, et al. A Centralized EHR-Based Model for the Recruitment of Rural and Lower Socioeconomic Participants in Pragmatic Trials: A Secondary Analysis of the Diuretic Comparison Project. JAMA Netw Open. 2023 Sep 5;6(9):e2332049.
16 Marquis-Gravel G, Roe MT, Robertson HR, et al. Rationale and Design of the Aspirin Dosing-A Patient-Centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE) Trial. JAMA Cardiol. 2020 May 1;5(5):598-607.
17 Cunningham, J. W., Abraham, W. T., Bhatt, A. S et al.; Heart Failure Collaboratory. (2024, November 12). Artificial intelligence in cardiovascular clinical trials. Journal of the American College of Cardiology, 84(20), 2051–2062.
