Computers, confounding, clusters, consent, cost, COVID and consultation: how the Health and Disability Code impedes the learning health system.

The Health and Disability Code precludes any research involving a competent patient without the informed consent of the participant. A learning health system requires rigorous evaluation of both new and established clinical practice, including low-risk components of usual care pathways. When comparing two accepted practices, the only way to control for unknown confounders is by randomisation. In some limited circumstances, particularly when comparing groups or clusters of patients, this comparison can only practicably be undertaken without consent. The current Code impedes a learning health system and is detrimental to the health of New Zealanders. It urgently needs updating.

Learning to Regulate Learning Healthcare Systems.

It is commonplace to observe that science often outstrips the ability of society to monitor, supervise and regulate it. A recent challenge in this regard concerns Learning Healthcare Systems, an initiative to collect data and test hypotheses across clinical settings, and therefore to a larger degree than before. Some argue that the line between research and clinical practice is becoming blurred, and that existing regulation seems to obstruct low risk research. They propose the creation of a new ethical framework for Learning Healthcare Systems, to speed up research. This paper opposes that view, and argues that Learning Healthcare Systems do not blur or remove the line between research and practice, and will not result in a single set of regulations for all kinds of biomedical research. The authors suggest that a large proportion of Learning Healthcare System activities resemble public health surveillance to a significant extent. Therefore, they propose that these activities should be organized in accordance with the same ethical principles as public health surveillance, specifically that Learning Healthcare Systems should rest on the principles of comprehensiveness, transparency, and public accountability.

Data Rich, Information Poor: Can We Use Electronic Health Records to Create a Learning Healthcare System for Pharmaceuticals?

Judicious use of real-world data (RWD) is expected to make all steps in the development and use of pharmaceuticals more effective and efficient, including research and development, regulatory decision making, health technology assessment, pricing, and reimbursement decisions and treatment. A "learning healthcare system" based on electronic health records and other routinely collected data will be required to harness the full potential of RWD to complement evidence based on randomized controlled trials. We describe and illustrate with examples the growing demand for a learning healthcare system; we contrast the exigencies of an efficient pharmaceutical ecosystem in the future with current deficiencies highlighted in recently published Organisation for Economic Co-operation and Development (OECD) reports; and we reflect on the steps necessary to enable the transition from healthcare data to actionable information. A coordinated effort from all stakeholders and international cooperation will be required to increase the speed of implementation of the learning healthcare system, to everybody's benefit.