Abstract

Zwarenstein (2015) proposes a novel approach to healthcare innovation that parallels biological evolution, based on stimulation and reward of multiple small competing innovation projects conducted in the field by decentralized teams. Projects would be designed with explicit outcome targets and results would be widely disseminated and publicly available. More successful projects would be grown and spread. Critical to the model is accepting and reporting failure as well as success, for the benefit of future project design.

Examining biological evolution for lessons for healthcare delivery innovation illuminates the need for diversity among healthcare systems to achieve optimum application of best practice interventions across jurisdictions with differing population, provider and facility characteristics. However, careful coordination will be needed to achieve the balance between diversity and harmony across jurisdictions necessary for effective governance and interaction. There are important methodological issues to be addressed to reduce the uncertainty inherent in comparisons of results among discrete innovation projects, especially when observed improvements over the baseline are modest. As well as evolutionary improvement in healthcare outcomes, the model should progressively increase decentralized capacity and expertise in innovation processes.