The Knowledge Object Reference Ontology (KORO): A formalism to support management and sharing of computable biomedical knowledge for learning health systems

Abstract

Introduction Health systems are challenged by care underutilization, overutilization, disparities, and related harms. One problem is a multiyear latency between discovery of new best practice knowledge and its widespread adoption. Decreasing this latency requires new capabilities to better manage and more rapidly share biomedical knowledge in computable forms. Knowledge objects package machine‐executable knowledge resources in a way that easily enables knowledge as a service. To help improve knowledge management and accelerate knowledge sharing, the Knowledge Object Reference Ontology (KORO) defines what knowledge objects are in a formal way. Methods Development of KORO began with identification of terms for classes of entities and for properties. Next, we established a taxonomical hierarchy of classes for knowledge objects and their parts. Development continued by relating these parts via formally defined properties. We evaluated the logical consistency of KORO and used it to answer several competency questions about parthood. We also applied it to guide knowledge object implementation. Results As a realist ontology, KORO defines what knowledge objects are and provides details about the parts they have and the roles they play. KORO provides sufficient logic to answer several basic but important questions about knowledge objects competently. KORO directly supports creators of knowledge objects by providing a formal model for these objects. Conclusion KORO provides a formal, logically consistent ontology about knowledge objects and their parts. It exists to help make computable biomedical knowledge findable, accessible, interoperable, and reusable. KORO is currently being used to further develop and improve computable knowledge infrastructure for learning health systems.

A framework for value-creating learning health systems

“…Consistent with the work of Friedman [10, 85], we see the execution and routinisation of learning cycles as the fundamental processes of LHSs. Learning cycles have three phases – P2D, D2K and K2P [85].…”

“…Consistent with the work of Friedman [10, 85], we see the execution and routinisation of learning cycles as the fundamental processes of LHSs. Learning cycles have three phases – P2D, D2K and K2P [85]. The execution of these phases is driven by ‘communities of interest’, which comprise the core group of actors motivated to tackle a collective problem and align LHS pillars to achieve their goals.…”

An overview of healthcare improvement: unpacking the complexity for clinicians and managers in a learning health system

“…Guidance on selection of appropriate model to inform improvement activities, that is, planning or conducting improvement. Table 4 Key lessons about implementation frameworks, theories and models 11,13,39,43 • Findings reveal a lack of predictive and prescriptive frameworks, with more emphasis on descriptive and explanatory. Frameworks were highly variable and setting-centric, where disciplines and clinical context or end user determined focus.…”

“…The learning health system (LHS) [10][11][12] provides a framework for positioning implementation science (IS) and HCI, and demonstrates how they can integrate. The LHS involves processes that generate and apply the best available evidence and use data to support collaborative healthcare decision-making with patients and clinicians; it drives the natural integration of discovery research into high-quality patient care and practice and engineers or promotes innovation, quality, safety and value in healthcare.…”

Mind the Gap: Putting Evidence into Practice in the Era of Learning Health Systems

“…These DKOs can be curated and managed in digital libraries and, through mechanisms completely analogous to the traditional function of libraries, made available to a range of users. Taking inspiration from pioneering work in enterprise knowledge management originally performed within Partners Healthcare, 9 several software products (for example, apervita.com and semedy.com) and standards 10 that support creation of DKOs and their management in digital libraries already exist. These resources, which will continue to mature, combine to make this vision an achievable reality.…”