Behavioral science is the study of human decision-making. It documents that people often act irrationally, but in predictable, repeatable ways — for example, people are loss-averse, influenced by social proof, and biased toward the present over the future. VAL Health applies these predictable patterns to design healthcare programs, communications, and incentives that change member, patient, and provider behavior.

Behavioral economics is a subfield of behavioral science. Behavioral science is the broader study of human decision-making across psychology, economics, and related disciplines. Behavioral economics specifically applies that science to economic and financial decision-making — pricing, incentives, choice architecture. VAL Health uses the terms in combination because health decisions (adherence, enrollment, screening) sit at the intersection of both: they involve financial and non-financial costs and benefits, framed and evaluated the same predictable way.

Behavioral science is applied to health by identifying the specific decision point where a patient, member, or provider fails to act as intended, then applying the matching principle — framing, defaults, social proof, timely feedback, commitment devices, or simplicity — to that point. VAL Health applies this method across enrollment, medication adherence, provider adoption, member experience, and care gap closure, and has driven results including a 2.1x increase in preventive screenings and a 3.9x increase in telehealth visits.

Behavioral economics increases enrollment by removing friction from the sign-up decision. VAL Health applies defaults, simplicity, and enhanced active choice to enrollment flows — reducing the number of steps, framing the decision as a choice between options rather than an open-ended ask, and using social proof to normalize adoption and exclusivity and limited availability. VAL Health's digital health clients have seen enrollment increase by up to 35% using these methods.

Interest does not automatically convert to action because of present bias — people delay decisions that require effort now for benefits later. VAL Health designs enrollment moments (timing, framing, commitment devices) that close the gap between interest and registration and enrollment.

Defaults, simplicity, framing, social proof, and enhanced active choice and exclusivity and limited scarcity. VAL Health selects the tool based on where users drop off in the enrollment funnel.g.

Ongoing engagement requires avoiding drop off or re-engaging users after the novelty of enrollment fades. VAL Health uses variable rewards, timely feedback, and fresh start moments (e.g., a new week, a milestone) to re-capture attention. VAL Health clients have experienced 3.2x increase in program participation and a 35% increase in digital health engagement using these tools.

Users stop using digital health programs after the first few weeks because the initial novelty wears off — what felt fresh and motivating in week one becomes routine by week three. Once the app no longer feels new, there's no pull to open it.

Compounding this, most programs bombard users with notifications, check-ins, and asks before they've gotten anything meaningful out of the experience. The ratio of effort to reward tips in the wrong direction fast, and users quietly disengage rather than formally quit.

Underneath both of these is a value problem: if the program hasn't delivered a tangible win — a clearer number, a symptom relieved, a habit that stuck — there's no reason to keep coming back. VAL Health redesigns the user journey to front-load value, reduce friction and noise, and time re-engagement moments to when motivation would otherwise fade.

A fresh start is a behavioral economics principle where people are more motivated to act at symbolic starting points (a new month, a birthday, a new diagnosis). VAL Health times re-engagement messaging to these moments to increase response rates.

Medication adherence is complex and varies by therapeutic area and route of administration, but a few behavioral drivers consistently predict whether patients stay on therapy.

Present bias pulls patients away from medications whose benefits are distant and abstract while the effort and side effects are immediate. Timely feedback — showing patients what the medication is doing right now — and commitment devices can shift the calculus toward consistency.

Side effect burden causes patients to quietly deprioritize therapy when the treatment feels worse than the disease, especially before therapeutic benefit sets in. Anticipatory framing and loss-aversion messaging help patients stay the course through the early adjustment window.

Regimen complexity creates friction that compounds over time — injectables, titration schedules, and multi-drug regimens all increase the likelihood of drop-off. Simplifying the choice architecture and reducing unnecessary decision points at each step lowers the behavioral cost of adherence.

Identity and illness acceptance keeps some patients from ever fully committing to a regimen, particularly those who resist seeing themselves as someone with a chronic condition. Identity-consistent framing — anchoring messages to who the patient wants to be, not what disease they have — can reduce this barrier.

Erosion of perceived necessity sets in once symptoms stabilize and patients lose the felt reminder of why they're on therapy. Milestone-based reinforcement and progress signals maintain salience and sustain motivation after the acute phase passes.

Knowledge does not overcome present bias or the friction of daily habit formation. VAL Health designs adherence experiences and programs around habit formation, saliency, and reminders that are timed to the patient's routine and addressing hurdles, rather than relying on education alone.

Provider adoption is a behavior change problem, not an information problem. VAL Health uses authority (peer and KOL influence), social proof (adoption data from similar practices), and simplicity (reducing prescribing friction) to drive uptake. In one VAL Health case study, this approach resulted in 77% of targeted providers taking clinical action.

Providers default to established treatment patterns due to status quo bias and the effort required to change workflow. VAL Health designs field engagement and communications that reduce that effort and provide social proof of peer adoption.

Authority, social proof, saliency, and simplicity. VAL Health pairs these with in-workflow tools (e.g., EHR-embedded prompts) to reduce the effort required to change behavior at the point of care.

CAHPS and HOS scores reflect member perception of ease, communication, and responsiveness. VAL Health applies framing and simplicity to member communications and touchpoints to directly improve how members experience and rate their plan.

Enhanced active choice, defaults, and ongoing timely feedback drive both initial adoption and continued use of member portals and apps. VAL Health designs both the onboarding moment and the habit-formation loop that follows.

Care gaps persist because the recommended action (a screening, a visit, a refill) competes with present bias and low saliency. VAL Health designs targeted nudges — framing, social proof, timely feedback — around the specific gap and channel. VAL Health case studies show up to a 2.1x increase in preventive screenings and a 16% increase in provider action on clinical Star metrics.

Effectiveness depends on the specific barrier (awareness, access, or motivation). VAL Health diagnoses the barrier first, then applies the matching behavioral economics tool — commonly framing (loss vs. gain), social proof, or simplification of scheduling.

Factual, generic reminders rely on information alone and do not address the underlying behavioral barrier (effort, present bias, or lack of saliency). VAL Health redesigns the reminder itself — timing, framing, and channel — rather than simply increasing reminder volume.

GLP-1 retention is a medication adherence problem: side effects and delayed visible results increase present bias against continuing treatment. VAL Health applies the same core methodology used in its medication adherence work — timely feedback, framing, and habit-formation nudges timed to the patient's treatment stage — to keep patients engaged through the periods where drop-off risk is highest.

Discontinuation is commonly driven by side effects early in treatment, cost friction at refill points, and a lack of visible short-term progress. VAL Health designs stage-specific interventions (onboarding, early side-effect period, refill points, and plateau periods) rather than a single generic retention message.

Digital tools provide the channel for timely feedback and habit tracking that supports retention, but the tool itself does not solve the behavioral barrier. VAL Health designs the behavioral content and timing within the tool, not just the tool's features.