The Decision-Making Blind Spot for Healthcare Leaders

by Who Decides, What Matters | Series Topic 1 | Jul 10, 2026

Key Insights

Many health system strategic initiatives underperform because they rely on historical data to predict future stakeholder behavior.
Traditional analytics explain what happened but cannot reliably forecast how physicians, patients, employers, or payers will respond to new market conditions.
In many specialty service lines, referring physicians—not patients—remain the primary drivers of where care is delivered, making referral behavior a critical strategic variable.
Behavioral decision intelligence has proven to enable organizations to test strategic assumptions before investing capital, reducing uncertainty and improving investment decisions.

Every year, U.S. health systems invest billions of dollars in strategic initiatives—from expanding service lines and ambulatory networks to launching digital care models and redesigning pricing strategies. These investments are typically supported by extensive planning, including claims analyses, market share reports, surveys, interviews, and focus groups.

Yet many strategic growth initiatives still fail to deliver their expected results (70%, according to McKinsey & Company). Referral leakage continues, out-of-network migration persists, and newly built capacity often falls short of projected demand. The problem is not simply execution. More often than not, organizations make forward-looking decisions using backward-looking data.

The Healthcare Decision Blind Spot

Traditional healthcare analytics are designed to explain yesterday's market—not predict tomorrow's. Claims data, utilization reports, and retrospective dashboards provide valuable operational insight, but they cannot reliably forecast how physicians, patients, employers, or payers will behave when presented with new choices, incentives, or competitive alternatives.

Likewise, conventional market research frequently measures what stakeholders say they might do rather than what they will choose when faced with real tradeoffs. As a result, healthcare leaders often allocate capital based on assumptions that have never been behaviorally tested using applied behavioral economics.

Referral Reality: The 80% Gatekeeper

One of the most common blind spots involves specialty care growth.

Many organizations focus expansion strategies on attracting patients through branding, digital engagement, and improvements in consumer experience. While these investments matter, behavioral decision modeling consistently demonstrates that, for many high-value specialty services, referring physicians control about 80% of referral volume, depending on the specialty and complexity of care.

When referral behavior is not incorporated into strategic planning, organizations risk investing heavily in patient acquisition while overlooking the behavioral factors that influence referral decisions. This is not simply a marketing challenge—it is a decision-making challenge.

Predicting Markets That Don't Yet Exist

Historical data cannot predict stakeholder behavior under conditions that have never existed, including:

New service line launches
Alternative care delivery models
Competitive market entrants
Changes in referral pathways
Pricing or site-of-care redesigns
New scheduling or access strategies

These decisions require understanding how stakeholders will respond—not simply how they responded in the past.

Replacing Assumptions with Behavioral Decision Intelligence

While uncertainty cannot be eliminated, it can be significantly reduced. By experimentally modeling real-world stakeholder behavior before implementation, healthcare organizations can:

Test strategic assumptions before investing capital.
Predict adoption and referral behavior.
Identify hidden sources of market friction.
Optimize service-line and operational design.
Improve capital allocation and investment returns.
Reduce the risk of costly strategic missteps.

Behavioral decision intelligence replaces assumptions with evidence. The result is greater confidence in strategic planning, improved capital allocation, and a reduced risk of costly investment mistakes. In future installments of the “Who Decides. What Matters.” series, we'll demonstrate how these behavioral models are developed, why they consistently predict real-world market behavior, and the results healthcare organizations have achieved by using them to guide high-stakes strategic and operational decisions.

Before launching your next strategic initiative, don't ask only, "What does the historical data tell us?"

Ask instead:

“Have we tested the behaviors that will determine whether this investment succeeds?”

What Matters to Physicians When Capital Investment Depends on Future Physician Supply

In the recent Newsworthy article, "What Matters to Expectant Mothers: Turning Behavioral Evidence into Market Growth.", we presented findings that answer the question of what matters to consumers. Specifically, the article examined how expectant mothers choose where to deliver. The next question was whether the organization could recruit additional obstetricians to support the projected incremental volume.

The proposed center would combine the expertise of a world-class obstetrics service with full-spectrum pediatric subspecialty care. However, projected demand alone was insufficient to justify a major capital investment. Leadership needed evidence that they could attract enough obstetricians to support the business case—either through employment or voluntary alignment.

Rather than relying on historical recruitment patterns or stated intentions, which proved inadequate for predicting obstetricians’ interest in the new business model, MII designed two behavioral experiments to identify the drivers of obstetricians' decisions. The two physician segments we tested were: (1) physicians employed by the center and (2) physicians who had privileges at the center (and were aligned)

Forty-two obstetricians participated in the employment contract acceptance experiment, and 48 in the voluntary alignment agreement experiment. Twelve features were tested, with ten in the employment model and seven in the alignment model.

The results identified specific priority drivers for each physician segment/group

From What Matters to What Changes Behavior

The behavioral research went beyond identifying what physicians said they valued. It quantified how changes to the proposed offers could affect the likelihood of acceptance. Among the scenario simulations tested, the following illustrative results are presented for the employment contract and the voluntary alignment scenarios.

These findings gave leadership what historical data could not: a way to assess how specific investment and contract decisions might influence behavior before committing capital.

Connecting Demand, Physician Supply and Capital

The truly powerful insights are derived from integrating the two physician experiments with the earlier consumer research (What Matters to Expectant Mothers).

While the expectant-mother’s study identified what matters to families when choosing where to deliver and quantified the potential for incremental deliveries, the obstetrician's study identified what matters to physicians when deciding whether to work with or align with the organization and quantified how changes to the employment and alignment agreements could affect participation. Thus, both sides of the supply and demand economic/business equation were considered.

This changed the nature of the Board's decision. The proposed center was no longer supported solely by historical utilization, financial projections, or assumptions about physician participation. Leadership had behavioral evidence showing what mattered to the people who would determine whether the center could succeed—and how changes to the proposition could influence their decisions.

Learning extends beyond this center: when a major healthcare investment depends on changing future behavior, historical data can describe the past—but behavioral evidence can help leadership test the future before investing capital.

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Mi4Sight® is Market Innovations, Inc.’s behavioral economics modeling solution. Built on more than 20 years of experience and 135 healthcare studies, it helps leaders test innovative hypotheses, quantify likely behavior, and evaluate investments before committing capital.

To learn more, visit Mi4sight | Market Innovations Inc.