Healthcare Procurement and Firm Innovation

The paper presented in this PRICE seminar explores whether technological learning between hospitals and supplier firms is associated with suppliers’ innovative performance. The empirical Analysis of the authors relies on a dataset combining unprecedented granular data on procurement bids and equipment with patent data measuring suppliers’ innovative performance. They identify the firm’s innovative activity relevant to the bid by using an advanced neural network algorithm for text analysis. This procedure allows them to match in an original way firm’s equipment descriptions with relevant patent documents. The authors then employ a difference-in-differences approach alongside a regression discontinuity design to estimate the causal effect of becoming a supplier on firms’ patents in the relevant IPC classes. Their results show that firms becoming hospital suppliers have a significantly higher propensity to innovate. About the mechanism, they show that supplying AI-powered equipment further boosts the suppliers’ innovative performance. Their results raise important policy implications in terms of the conduct and design of procurement bids in healthcare and in the precision medicine domain.