Knowledge infrastructure: a priority to accelerate workflow automation in health care.

Dear Editors, We recognize that inefficient and idiosyncratic workflows in health care contribute to a myriad of obstacles for all healthcare stakeholders, including misuse of resources, provider burnout, and increased burden on patients and their caregivers.1 Therefore, we were pleased to read Zayas-Cabán et al’s2 article, “Priorities to accelerate workflow automation in healthcare.” We applaud them for their work illuminating determinants, priorities, and associated strategies for workflow automation. We augment their findings by proposing a seventh priority to stand alongside their original 6—develop and promote infrastructure to facilitate findability, accessibility, interoperability, and reusability of workflows (Table 1). In our view, the automation of healthcare workflows depends on the deployment of reliable, valid, robust, and proven computable biomedical knowledge (CBK) artifacts. We define CBK artifacts as separately packaged software implementations of evidence-based procedural, logical, mathematical, and statistical algorithms.3 We hold this view at an equal level of importance as the need for high-quality, interoperable data and a deep understanding of workflows, as emphasized by Zayas-Cabán et al. Our perspective is that automation of workflows will depend on formalizing and explicitly representing current and desired (optimal) workflows so that they can be tracked and processed by computers in valuable ways. Moreover, to achieve powerful automation, infrastructure must be developed to coordinate and combine computable workflows or process models with AI models, computable guidelines, and other CBK artifacts.