Toward an Information Infrastructure for Global Health Improvement

Abstract

Summary Profound global challenges to individual and population health, alongside the opportunities to benefit from digital technology, have spawned the concept of the Learning Health System. Learning Health Systems (LHSs)--which can function at organizational, network, regional, and national levels of scale--have the capability of continuous data-driven self-study that promotes change and improvement. The LHS concept, which originated in the U.S. in 2007, is rapidly gaining attention around the world. LHSs require, but also transcend, the secondary use of health data. This paper describes the key features of LHSs, argues that effective and sustainable LHSs must be supported by infrastructures that allow them to function with economies of scale and scope, and describes the services that such infrastructures must provide. While it is relatively straightforward to describe LHSs, achieving them at the high level of capability necessary to promote significant health benefits will require advancements in science and engineering, engaging the field of informatics among a wider range of disciplines. It also follows from this vision that LHSs cannot be built from an imposed blueprint; LHSs will more likely evolve from efforts at smaller scales that compose into larger systems.

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

“…These include a requirement to directly connect knowledge to practice within the context of ongoing learning. In LHSs, communities of interest need to continuously learn and then share what they learn easily and widely via existing electronic health records and other health IT systems . In the KGrid approach, KOs play dual roles as archival knowledge resources, for knowledge management, and as service enablers, for knowledge sharing.…”

“…In the KGrid approach, KOs play dual roles as archival knowledge resources, for knowledge management, and as service enablers, for knowledge sharing. By so doing, KOs have the potential to help people meet the knowledge management, archiving, and sharing needs of LHSs …”

“…We postulate that the LHS “learns” through a cyclical process that engages a community in empirical analysis of data relevant to a biomedical problem, which leads to the discovery of new knowledge. The learning cycle is completed by direct application of that knowledge to change practice . Changed practice generates new data, driving the next iteration of the cycle, with improvement occurring via successive iterations.…”

Impact of big data on oral health outcomes

“…The biomedical database buttresses the advances in informative tools such as Al., mobile, social and IoT, and in turn, the application of these tools is driving biomedical data to be positioned at the heart of patient‐centred healthcare services in future. Evolution of the concept “Learning Health System” (LHS)—“a system that can function at organizational, network, regional, and national levels of scale—has the capability of continuous data‐driven self‐study that promotes change and improvement” introduces a complete cyclical process of utilizing and applying health data to generate new knowledge that can be employed to improve the health of individuals and populations (Friedman, Rubin, & Sullivan, ). LHS could provide a cyclical approach to maximize the biomedical big data‐driven future opportunities to improve health care.…”

Ethical, legal, and social implications of learning health systems

“…LHSs represent an innovation in health infrastructure such that learning occurs at multiple levels of scale, ranging from individuals, single practices, and systems to systems of systems spanning organizational and geopolitical boundaries. LHSs are successful when platforms and culture support efficient organization of technology, people, processes, and policy …”