Too often, protocols are written for a version of patients and clinics that doesn’t exist—one with unlimited flexibility, perfect adherence, and no competing life demands. When design ignores reality, it quietly limits access, reduces diversity, and creates operational barriers that sites must absorb, even though smarter, more flexible design can protect scientific rigor while expanding who can truly participate.
When protocols assume perfection, enrollment drops, deviations rise, and patient diversity declines.
Not because sites lack skill — but because the design doesn’t reflect how people actually live.
If we want more inclusive, accessible research, we need protocols that protect scientific rigor without ignoring human reality.
Rigid Visit Windows and Their Impact on Inclusivity
Many protocols continue to rely on narrow visit windows, weekday-only scheduling, fixed early-morning fasting laboratories, and tightly sequenced procedures that exceed what many patients can reasonably tolerate. These requirements fail to account for work schedules, school obligations, caregiving responsibilities, and transportation limitations. As a result, participation becomes feasible only for a narrow subset of patients whose lives align with highly structured clinical expectations.
A more inclusive approach applies risk-based flexibility without compromising scientific validity. Visit windows can be expanded from ±1 day to ±3–5 days when endpoints are not time-sensitive. Weekend or early evening appointments can accommodate working adults. Six-hour fasting periods may be acceptable when metabolic markers are unaffected. Telemedicine visits can replace in-person assessments when physical examination is not required, and remote completion of patient-reported outcomes (PROs) can replace clinic-based diary reviews. These adaptations do not weaken data integrity; they expand access while preserving rigor.
Exclusion Criteria and the Unintended Reduction of Diversity
Exclusion criteria are often written to minimize variability rather than to address genuine safety concerns. Common examples include excluding patients with any history of mild or resolved chronic illness, those with well-controlled hypertension or diabetes, individuals taking stable medications with no relevant interactions, and older adults based on arbitrary age cutoffs. Such criteria disproportionately eliminate patients who reflect real-world populations.
More inclusive protocols rely on clinically meaningful exclusions rather than blanket prohibitions. Patients with stable comorbidities can be safely included, medication washouts should be required only when scientifically necessary, and investigators should be empowered to apply clinical judgment in borderline cases rather than defaulting to automatic exclusion. Regulators increasingly support science-based inclusivity; excessive conservatism often originates in protocol authorship rather than regulatory expectation.
Operational Design and Its Effect on Site Equity
Protocols sometimes require multiple time-sensitive procedures across different rooms, mandate principal investigator-only assessments during peak clinic hours, enforce rigid sequencing that conflicts with real-world workflow, or require in-person assessments that could safely be conducted remotely. These designs favor large academic centers with extensive infrastructure and inadvertently disadvantage community sites that often serve more diverse patient populations.
Operational equity improves when qualified sub-investigators are permitted to conduct stable assessments, when procedure order can be adjusted without affecting endpoint integrity, when visits can be combined when medically appropriate, and when laboratories may be drawn at accredited local facilities if assay variability is acceptable. These changes preserve scientific standards while broadening site participation.
PRO and Diary Burden as a Barrier to Adherence
Protocols frequently require daily diary entries at fixed times, lengthy questionnaires, device synchronization dependent on stable Wi-Fi, and the use of multiple applications for different trial components. These expectations disproportionately burden caregivers, shift workers, patients with limited digital literacy, and individuals in underserved communities.
A more sustainable approach favors brief, validated instruments over multi-page questionnaires, allows windows for diary completion, enables text-message reminders, and provides devices with data plans when technology access is a barrier. Improved adherence follows when systems reflect how patients actually live, and better adherence produces better data.
Maintaining Safety Without Increasing Patient Burden
Safety oversight remains essential, but many protocols require in-person evaluations or repetitive laboratory testing when remote review or consolidated visits are equally effective. Telehealth visits for adverse event assessments, consolidation of blood draws when biomarkers are stable, acceptance of recent clinically obtained laboratory results, and elimination of redundant safety procedures can all maintain patient safety while reducing unnecessary burden.
Regulatory agencies support efficiency when safety is preserved. Thoughtful simplification strengthens compliance rather than undermining it.
The Path Forward: Real-Life Protocols for Real-Life People
Protocols can be both scientifically rigorous and human-centered. Achieving this balance requires designing visit windows around real patient behavior, broadening eligibility to reflect real-world populations, permitting flexible sequencing of procedures when scientifically justified, incorporating telehealth where appropriate, reducing PRO and diary burden, applying risk-based monitoring to identify truly critical tasks, and involving sites early in protocol development to identify operational barriers.
Rigid design often stems from fear of variability. Yet human variability is intrinsic to clinical research. When protocols are designed for the world as it is rather than as it is imagined, enrollment improves, diversity increases, deviations decline, and data quality strengthens. Scientific integrity is not weakened by flexibility; it is reinforced because studies become executable as designed rather than idealized in theory.