Modern-day health care has remarkable capabilities in producing novel scientific innovations that extend and improve life. However, many of these innovations remain prohibitively expensive even decades later—long after their novelty or patent protections have ended. Thus, while many new innovations continue to get commercialized, too few ever get commoditized. This cost-inflationary cycle of paying premium prices for both new and old innovations is financially unsustainable and has resulted in market failures that are hurting people. What makes health care so different from other industries that have successfully made older innovations dramatically cheaper over time? And more importantly, based on those differences, is there a better way to make older innovations more affordable without harming the industry’s high-performing novel innovation capabilities? Based on intensive primary research into a group of uniquely structured businesses in the United States, called Health Care Utilities (HCUs), this thesis provides new insights into these questions.

HCUs are a new genre of business in which incumbent institutions form self-sustaining, mission-driven corporations to provide essential products and services for customers and society at the lowest sustainable costs. They represent structural transformations in health care that were established through employing a specific mindset and form of collaboration, called disruptive collaboration, which involves multiple organizations working together to collectively disrupt an entire subindustry. In the first part, the thesis develops the underlying structural model of a HCU and presents first empirical results, based on primary data, that demonstrate the promising improvements on generic pharmaceutical access and affordability for a large HCU member health system in the United States. The second part of the thesis draws on management theory to study the potential and limitations of applying the new HCU structure to other areas in healthcare. The thesis develops a practical framework of boundary conditions that can be directly applied by leaders in assessing future model application. The framework is illustrated through multiple use cases.