'Humbling' Hospital Simulations Inspire Stanford Graduate Students to Solve Problems in Health Care Delivery - Healthcare Training and Education
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‘Humbling’ Hospital Simulations Inspire Stanford Graduate Students to Solve Problems in Health Care Delivery

Stanford

A recent Biodesign Innovation class got off to an unusual start. Instead of asking students to pull out their laptops and listen to a lecture, organizers handed out envelopes assigning students to mysterious roles as a patient, caregiver or observer. Then, the students left grad school behind.

For the next hour, the students immersed themselves in chaotic, sometimes wrenching hospital scenarios that included an emergency room; a quiet patient room where a woman lay dying; and physical therapy consultation with an ornery fall victim. As each simulation played out, the students struggled to obtain appropriate care and make critical medical decisions against a frustrating backdrop of financial limitations, overburdened providers and conflicting family wishes.

The purpose of the unsettling exercise? To give students in this class, which focuses on developing medical devices and other technology-based solutions to problems in health care, a chance to observe problems in health care delivery firsthand. According to the Stanford Byers Center for Biodesign, this is an essential first step for innovators hoping to invent viable technology solutions that fully address an unmet need.

Learning what the needs are

The philosophy of deeply understanding a problem before trying to invent a solution to address it is at the heart of how the Biodesign Center teaches students at all levels. This method, called a needs-driven approach, requires an innovator to delve deeply into a medical need, including understanding what characteristics a solution must have to satisfy the various stakeholders. Then, those criteria guide the development of a solution. This approach avoids the pitfalls of developing a technology that isn’t marketable or won’t be adopted. As an example, if a technology works but would be too expensive, a hospital may not buy it and the technology won’t reach patients.

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