• Preventive care falls behind because routine care is organized around short visits addressing acute symptoms, leaving limited time and capacity for screenings, counseling, and coordinating specialist follow-up visits. 
• Embedding screening, follow-up, and referral steps into default workflows and offloading administrative tasks means clinicians’ roles remain focused on clinical care rather than administrative tasks.
• When financial and social incentives are aligned with preventive care, and visible commitment devices are used in clinics, preventive visits and follow-up work can be planned more deliberately and sustained over time.

Preventive care includes routine screenings, immunizations, and early interventions that reduce risk across cancer, chronic disease, mental health, substance use, vision, and oral health.² When these services are delivered consistently, they’re generally associated with lower illness and mortality rates. Uptake, though, has not fully kept pace. In the United States, fewer than half of adults aged 65 and older are up to date on core preventive services, and persistent racial and ethnic disparities may be leaving many patients exposed to avoidable risk.³ That gap has not come from uncertainty about the clinical advantages associated with preventive care. It more frequently reflects how preventive services are accessed, scheduled, and carried through in everyday care.

Time is one of the main constraints in primary care. For example, physicians in Ontario work an average of 47.7 hours per week, and roughly 40% of that time is spent on administrative tasks rather than patient care.⁴ Comparable estimates using national Canadian data point to tens of millions of clinical hours being absorbed by paperwork and coordination each year.⁵ Even when guidelines are clear, delivery may exceed capacity. In one modeling study informed by 2020 U.S. Preventive Services Task Force (USPSTF) recommendations, results suggest that family physicians don’t have the time to provide all recommended preventive health care services, which would take more than eight hours per day.⁶ In packed schedules, prevention may be delayed, shortened, or pushed aside as care teams address immediate needs. Extra steps around scheduling, billing, and documentation add strain when schedules are already overflowing. Behavioral science research suggests that uptake improves when defaults favor prevention-based approaches, administrative effort is reduced, and incentives are aligned for patients, clinicians, and the teams around them.

Primary care is widely positioned as the ideal setting for prevention and health promotion, and clinicians generally agree with that role. However, delivery is constrained by persistent operational barriers, including high workload, limited visit time, insufficient referral infrastructure, and restricted access to allied health services.⁷ When preventive care requires multiple steps—screening, counseling, referral, documentation, and follow-up—it becomes dependent on resources many clinics don’t have. Policy endorsement at the system level has not translated into consistent delivery during routine visits.³

The biomedical model also shapes how time is used, and it functions as a mental model rather than a values problem. In many Western systems, routine care has been organized around identifying illness, assigning a diagnosis, intervening, and restoring stability.⁸ A patient schedules an appointment because something feels wrong, and the visit begins from that premise. Risk reduction and long-horizon planning then arrive as additional tasks layered onto an already packed agenda. Clinicians don’t typically enter the room assuming the patient is well and primarily managing long-term risk; they enter expecting a near-term problem to resolve and a chart to close. 

Evidence from implementation research illustrates how tightly prevention is linked to capacity. In Swedish primary health care units where a computer-based lifestyle intervention tool had been operating for two years, use differed sharply based on whether additional resources had been allocated.⁹ Units with added staffing or protected time used the tool as intended and reported satisfaction with preventive care delivery. Where no extra capacity had been provided, preventive activities were consistently deprioritized when acute demands emerged, including immunization campaigns and other time-sensitive tasks. The tool wasn’t rejected; it was deferred. Prevention depended less on clinician motivation and more on whether clinics could absorb it operationally.

Within individual patient visits, time limits become more pronounced. A video-based analysis of primary care encounters found a median visit length of 15.7 minutes covering six topics.¹⁰ The longest topic received about five minutes, while the remaining topics averaged roughly one minute each. That amount of time leaves little room for preventive counseling that typically requires discussion, goal setting, and follow-up planning.

Cognitive Load Theory offers a useful explanation for why preventive care is so often deferred in primary care. Working memory is limited, and in routine clinical practice, task demands frequently exceed that capacity. Clinicians are diagnosing symptoms, prioritizing across comorbidities, communicating risk, documenting decisions, and managing uncertainty simultaneously. Cognitive load is high by design, making complex, multi-step tasks like preventive counseling, behavior change planning, and follow-up coordination harder to deliver within standard visit lengths.

Further, once time and resources are constrained, bounded rationality describes the decision logic that takes over: people choose options that are acceptable, defensible, and feasible rather than optimal across every objective.¹¹ In a compressed visit, the clinician’s goal isn’t long-term health maximization; it is safe, guideline-consistent care delivered within time, scope, and accountability requirements. Treating the acute issue and stabilizing the problem list becomes a rational satisficing strategy, and it’s the strategy clinics can execute reliably.

System-level incentives reinforce this decision logic through present bias and temporal discounting. Preventive care imposes immediate costs on clinicians and clinics because it leads to longer visits, additional documentation, referrals that must be coordinated, and follow-up that may not be reimbursed or tracked. The benefits of prevention, however, accrue later and often occur outside of the clinician’s direct line of sight. Immediate pressures therefore receive disproportionate weight, while delayed benefits are discounted. Over time, this imbalance trains the system to prioritize what can be completed now over what pays off later. 

Time scarcity in primary care can be eased without extending visit length or raising expectations for individual clinicians. The opportunity lies in changing how preventive care enters administrative workflows, including electronic health records, and in redistributing work that’s currently concentrated inside the visit.

Make prevention default by embedding opt-out scheduling and orders into the system

Under time pressure, clinicians gravitate toward actions that are fastest to complete and least disruptive to clinical throughput. The default effect captures this tendency directly: when a preventive action is presented as the standard path, it’s more likely to be executed than when it must be recalled and initiated under load.¹² In practice, this means embedding age- and risk-appropriate preventive screenings, follow-up appointments, or counseling referrals into order sets and scheduling logic using available electronic health data so they surface automatically.¹³ The system prepares the plan, and clinicians quickly approve, defer, or modify it rather than assembling the entire process step by step.

Operationally, this reduces task-switching. Instead of recalling guidelines, navigating menus, placing orders, and coordinating follow-up, clinicians respond to a prepared option. Fewer decisions are required mid-visit, and working memory is conserved. Prevention becomes part of the visit’s baseline flow because it’s already there. 

Evidence supports this design. In a stepped-wedge randomized clinical trial of 7,634 hospitalized patients, embedding a default hepatitis C screening order into admission order sets increased screening and completion compared with interruptive alerts.¹⁴ Alerts had been pulling attention away from primary tasks and increasing switch costs. Defaults lowered cognitive burden, and screening rates rose without increasing visit length or clinician workload.

Outpatient care shows a similar pattern. A 2024 randomized trial of postpartum primary care engagement found that default scheduling paired with tailored messaging increased primary care visit completion by nearly 19 percentage points within four months, from 22% to 40%.¹⁵ Preventive screening rates followed the same direction: blood pressure checks increased by about 15 percentage points, depression screening nearly doubled, and postpartum readmissions declined from 5.8% to 1.7%. Appointments were scheduled automatically or prompted through outbound messages with pre-set options, so clinicians weren’t managing logistics during the visit.

Choice architecture helps explain why this approach scales across settings. By shaping how options appear at the point of decision, systems influence behavior without demanding extra motivation or training. Defaults reduce switch costs, lower cognitive friction, and align preventive care delivery with how clinicians already work under constraint. 

Create time back so increased prevention doesn’t overload clinicians

Defaults alone won’t hold, however, if they add downstream work. If preventive appointments increase while documentation burden and care coordination demands remain unchanged, clinicians could become more saturated rather than less. For prevention to scale without backfiring, time has to be freed in parallel. The behavioral lever here is reducing cognitive and administrative load so scarce minutes can be spent on clinical reasoning and high-value conversations.

Documentation remains one of the largest drains on clinician capacity. In a U.S. national longitudinal cohort study of 18,265 ambulatory physicians, adoption of team-based documentation support was associated with substantial reductions in electronic health record documentation time and after-hours charting.¹⁶ High-intensity adopters reduced documentation time by more than 50 minutes per week and cut after-hours Electronic Health Record (EHR) use by over 20%, while visit volume increased by roughly 6%, rising to nearly 11% after a learning period. 

AI-enabled clinical documentation tools are also beginning to show similar promise, particularly in high-volume settings where documentation consumes a large share of clinician time. In a randomized evaluation spanning roughly 72,000 patient encounters, physicians using commercial AI scribes reduced documentation time by close to 10%, and many reported lower work-related stress as a result.¹⁷ Adoption probably won’t look the same across specialties, but the signal is consistent: administrative work can be offloaded without reducing access, fragmenting visits, or slowing care.

Defaults simplify decisions at the point of care. Administrative offloading creates the capacity to act on those decisions. Together, they reduce task-switching, lower cognitive load, and support the more consistent delivery of preventive care with downstream public health benefits.

Preventive care also often occupies a structurally weak position in health system financing. Although it’s widely endorsed and often cost-effective, it consistently receives a small share of total health expenditure and is among the first areas to be constrained when budgets tighten.¹⁸ That funding reality sends a clear signal about what the system actually expects actors to prioritize.

Looking across Organisation for Economic Co-operation and Development (OECD) countries, prevention spending has remained a modest fraction of overall health expenditure for decades. During the pandemic, that share increased to roughly 6%, then fell back to around 3% by 2023 as fiscal normalization took hold.¹⁸ Primary health care spending, meanwhile, has hovered near 14% of total health expenditure for more than a decade. Despite repeated commitments to population health and upstream care, budget envelopes have continued to favor treatment and acute services. For leaders operating inside those constraints, prevention may be viewed as strategically important, yet it’s often treated as discretionary when trade-offs are made, particularly when short-term fiscal pressures accumulate.

Across health systems, the actors who benefit most from prevention are often not the same actors who pay for or deliver it. System leaders and policymakers may be aiming to improve long-term population health, reduce avoidable hospital use, and control future costs, while clinics and clinicians are responding to near-term financial and operational constraints. Preventive care typically requires upfront investment: staffing, outreach systems, longer encounters, coordination, and follow-up. The returns also often arrive later and elsewhere. Hospital admissions may decline without primary care budgets increasing. Patients avoid morbidity, yet the clinic absorbs the immediate cost. This separation between who does the work and who captures the benefit reflects a classic principal–agent problem, and under these conditions, deprioritizing preventive services becomes a rational response rather than a lack of commitment.

Payment models in many health care systems amplify this logic by tying revenue directly to patient throughput. Under fee-for-service arrangements, which remain common either alone or in blended forms across high-income countries, clinicians and clinics are paid per visit, per encounter, or per unit of care delivered.¹⁹ Productive behavior is therefore defined by moving patients through the schedule efficiently and resolving the presenting complaint within the allotted time. Preventive care often sits awkwardly on top of that structure. Counseling extends visits. Care coordination spills beyond the visit and requires coordination across administrative teams. Behavior-change planning unfolds over weeks or months, and outreach to patients who aren’t already scheduled generates work without guaranteed reimbursement. Faced with that reality, actors don’t abandon prevention in principle, but they tend to prioritize work that fits the visit-based payment logic under which they are paid to operate.

If financial incentives shape how care is delivered, then differences in payment models should show up in measurable patterns of preventive uptake. That’s exactly what empirical evidence suggests. In Ontario, comparisons across physician remuneration models have shown higher preventive cancer screening rates under blended capitation than under blended fee-for-service, for example, with colorectal screening rates roughly 3.0–3.6 percentage points higher by 2022.²⁰ These differences emerged within a universal health system, suggesting that payment design itself may be shaping preventive uptake rather than patient demand or insurance coverage.

Behavioral decision science helps explain why these patterns persist even when prevention is known to be valuable. Present bias leads decision-makers to overweight immediate costs relative to delayed benefits, especially when budgets are annual and performance is assessed in short cycles. Status quo bias further stabilizes the arrangement. Payment structures and budget allocations that have been in place for years feel administratively safe, even if they’re misaligned with stated goals. Changing them introduces uncertainty and transitional costs. Maintaining the existing distribution of spending may feel easier than reallocating toward prevention, particularly when the benefits are diffuse and the costs are immediate and visible.

If clinicians are being reimbursed for the number of patients seen, care tends to be organized around shorter encounters and rapid resolution of acute complaints. When preventive interventions are reimbursed directly, preventive care becomes a priority to plan, staff, and deliver, and one would reasonably expect uptake to increase.

Australia’s 45–49-year-old health check provides a concrete example of how this incentive change plays out in practice. The policy emerged from a broader national push to address chronic disease earlier and more systematically in primary care, articulated through the Council of Australian Governments’ Plan for Better Health for All Australians and the National Chronic Disease Strategy.²¹ To translate those priorities into routine practice, the health check was introduced as a Medicare-rebateable item in November 2006. It paid general practitioners to deliver structured preventive consultations for patients aged 45–49 with at least one chronic disease risk factor, whether lifestyle-related, biomedical, or based on family history. The rebate covered work that’s often difficult to sustain in short visits, including comprehensive history-taking, clinical examination, and investigations, assessment of readiness to change, initiation of referrals or interventions, and tailored advice. Once that work was reimbursed explicitly, clinics could schedule prevention deliberately rather than absorbing it informally. Uptake patterns reflected how incentives interacted with access: patient participation was higher in divisions serving larger proportions of recent migrants from non-English-speaking backgrounds, and general practitioner participation increased with rurality, suggesting predictable reimbursement may have supported preventive delivery where unmet need and access constraints were more pronounced.²²

Financial incentives, though, don’t need to carry the entire burden. Social norms and social comparison theory suggest that professionals often evaluate their behavior relative to peers, especially in settings where standards are complex and time is limited.²³ In health care, where clinicians operate under uncertainty and constant pressure, peer benchmarks can influence behavior even when formal incentives are modest.

Antibiotic stewardship provides a clear example. In a randomized trial published in The BMJ, family physicians received mailed feedback comparing their antibiotic prescribing rates to those of peers, alongside brief guidance.²⁴ Within six months, prescribing fell by roughly 5% relative to controls, with fewer unnecessary prescriptions and shorter treatment courses. No penalties were imposed, and no additional reimbursement was offered. Behavior changed because the intervention recalibrated what typical practice looked like.

Preventive care may show similar sensitivity to peer comparison. In one study, clinicians received monthly emails benchmarking their influenza vaccination completion rates against peers.²⁵ Completion increased from approximately 27.6% under usual care to 34.7% with feedback. The message didn’t instruct or enforce. It made performance visible and comparable, which allowed clinicians to self-correct without external pressure.

Commitment devices operate through a related but distinct mechanism. When individuals make public commitments, they experience pressure to behave consistently with those commitments in order to preserve credibility and professional identity. In health care, where trust and reputation matter, that pressure can be meaningful even in the absence of formal enforcement. This effect has been demonstrated in trials addressing inappropriate antibiotic prescribing. In one study, clinicians displayed signed commitment posters in their examination rooms stating their intention to prescribe responsibly, often alongside their photograph.²⁶ Inappropriate prescribing declined substantially, with difference-in-difference estimates approaching 20 percentage points. The intervention didn’t change incentives or workflows.²⁶ It changed the social context of the decision. Once a promise was visible to patients and colleagues, deviation carried a reputational cost that many clinicians appeared motivated to avoid.

Applied to prevention, these tools could support brief but consistent preventive actions even in short visits. Peer comparison may guide behavior when payment signals are incomplete or slow to change. Commitment devices anchor intentions directly in the clinical environment, making preventive care part of how clinicians present themselves professionally. 

Behavioral interventions can improve preventive care delivery, but whether they do so depends less on intent and more on execution. When workflow realities, incentive design, and professional norms aren’t aligned, tools that look sensible on paper may be sidelined in practice or may instead trigger resistance.

One risk arises with “time back” strategies such as team-based documentation or AI scribes. Although reductions in documentation burden may materialize over time, early phases can feel slower and more frustrating for clinicians. New tools impose learning curves, disrupt established routines, and can temporarily increase cognitive load. If that friction isn’t anticipated, programs may be abandoned before benefits emerge. Adoption’s more likely to occur when implementation is phased, onboarding time is protected, and troubleshooting is built in from the start. Without those guardrails, early dissatisfaction could outweigh downstream gains.

A different tension emerges with pay-for-performance models. Evidence from large schemes suggests incentivized indicators can improve early, then flatten once targets are met, while care outside the incentive frame may drift.²⁷ These risks could be reduced by designing incentives that don’t lock clinicians into a single narrow target. Instead of fixed thresholds that stop paying once a box is checked, programs could rotate which preventive actions are rewarded across periods and include follow-up completion, referral uptake, or continuity indicators in the same bundle.

Peer comparison introduces another layer of complexity. Benchmarking can clarify norms, yet it may demoralize clinicians when it feels punitive, surveillant, or disconnected from leadership support. In one study, social comparison feedback was associated with higher burnout and lower job satisfaction among clinicians who perceived weak organizational backing.²⁸ For peer feedback to be effective, it needs to be framed as support rather than ranking, delivered by trusted leadership, and paired with concrete next steps. 

Preventive care hasn’t been limited by a lack of clinical skill or professional judgment. It’s been shaped by environments where time is scarce, coordination stretches across teams, and incentives often favor work that can be completed and documented within a single encounter. In those conditions, clinicians are making reasonable trade-offs about how to use limited attention and effort. When prevention requires additional coordination, scheduling, or unreimbursed follow-through, uneven delivery becomes a feature of the system rather than a failure of practice.

There’s growing reason to think some of that burden could be eased. Adjustments to workflows, documentation, and incentives may create room for prevention without adding pressure. Defaults can reduce the need to remember or initiate extra steps, documentation support can return time to clinical work, and carefully designed financial or social signals might reinforce preventive actions that already align with professional norms. None of these tools is a complete solution on its own, but together they point toward ways the system could better support the care clinicians are already trying to provide.
At The Decision Lab, we apply behavioral science to health care settings where professionals are operating under real constraints. We work with primary care networks, hospitals, and public health organizations to redesign workflows so evidence-based care holds up in day-to-day operations. If you’re exploring ways to deliver care more effectively while supporting clinician well-being and patient experience, we’d welcome the opportunity to collaborate on solutions that will hold up in real health care settings.

How social norms reduced missed hospital appointments by 31.7%

Globally, around 23% of patients miss scheduled clinical appointments. Missed hospital visits place strain on already limited resources and can lead to poorer health outcomes and higher downstream costs. In this piece, we highlight how leveraging social norms can reduce missed appointments and improve follow-through by shaping expectations around attendance and responsibility.

Health Belief Model

Health behavior goes far beyond simply knowing what’s good for us. The Health Belief Model identifies six key factors that influence whether a person will take action to prevent, screen for, or control illness. With these insights in mind, practitioners can design interventions that address hesitation around attendance and make it easier for patients to book and attend their health care appointments.

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