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?”

Getting to Yes: How Behavioral Decision Intelligence Helped Secure Board Approval for a Women & Infants Tower

Key Insights

After two decades of stalled advocacy, behavioral decision intelligence helped healthcare executives transform a high-risk capital proposal into an evidence-based Board decision.

  • Leadership replaced assumptions based on historical inference with evidence of future market behavior, advancing the proposal to secure approval
  • Historical utilization data showed past choices but provided no clear indication of whether families would switch hospitals - and locations - for a new care model.
  • The key question: would expectant mothers bypass an established suburban leader in favor of a new urban Women & Infants Tower?
  • A discrete choice experiment quantified likely switching behavior and the factors most likely to influence delivery decisions.
  • Predictive simulations estimated incremental deliveries, market-share gains, and financial performance across scenarios.

For more than two decades, a leading pediatric academic medical center’s Chief Medical Officer advocated for a Women & Infants Tower that would integrate labor and delivery with neonatal intensive care, pediatric subspecialists, maternal-fetal medicine, and enhanced patient amenities. The proposal repeatedly stalled because the Board required credible evidence that the tower would generate enough incremental deliveries to justify the hundreds of millions of dollars in construction costs.

Success hinged on whether expectant mothers would bypass the region’s established suburban labor and delivery leader in favor of an unbuilt urban facility. Historical utilization data reflected past choices, not future switching behavior in a market with no comparable facility.

The obstacle was not the vision but uncertainty.

Modeling a Market Before It Exists

MII designed a discrete choice experiment to simulate how families choose where to give birth. Women of childbearing age evaluated realistic delivery options that varied by affiliation, out-of-pocket costs, NICU capabilities, patient safety, room guarantee, family sleeping options, convenience, and patient satisfaction. Their choices indicated whether the proposed tower offered sufficient value to overcome the incumbent’s advantage.

These choices provided new data for decision-making. By simulating future scenarios, leadership could now estimate market share, incremental deliveries, and volume shifts across competing hospitals.

Replacing Assumptions with Decision-Ready Evidence

The simulations provided leaders with market scenarios for comparing against the project’s financial requirements. They also identified the factors most likely to motivate families to switch hospitals, helping executives assess the conditions needed for success. Behavioral decision intelligence turned a twenty-year discussion into a Board-level investment decision grounded in evidence.

The Strategic Value of Knowing What Matters Before Building

Major capital investments often stall when leaders cannot estimate demand in markets that do not yet exist. Behavioral decision intelligence shows where patients are likely to choose tomorrow—and what will influence those choices. For healthcare executives, that can turn a speculative capital debate into a disciplined investment decision.

In the next article in the series, Who Decides. What Matters, we will share what mattered to expectant mothers in Getting to Yes.

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.