Critical Illness Outside the Intensive Care Unit: Research Challenges in Emergency and Prehospital Settings

Patients with acute critical illness comprise a population of highly vulnerable patients at high risk of death. The best available treatments have a high rate of failure, and often, there is a paucity of high-level evidence to support many of our diagnostic and therapeutic approaches. Research in acute critical illness is challenging due to the clinical urgency and the lack of capacity of patients to provide informed consent. Even obtaining consent from a surrogate decision-maker may introduce risk of harm from delays to treatment and may be inappropriate and impractical. The traditional model for clinical research has evolved from settings where there is not time urgency or distress, and informed consent from the participant or a surrogate decision-maker can occur. This is unsuited to emergency and critical care investigation. International ethical guidelines for research involving humans define circumstances where research may occur without prospective informed consent, and these have been adopted in many countries. There is, however, substantial variability in the legal and regulatory frameworks that govern research participation. This can be an impediment to undertaking the necessary research to resolve important questions of effectiveness and safety of treatments and paradoxically exposes patients to risk of harm from exposure to unwarranted practice variation and unproven treatments. There is a need to develop a harmonized, internationally recognized regulatory approach to research involving incapacitated critically ill patients, which reflects the ethical framework set out in the Declaration of Helsinki. While, historically, the traditional model of individual patient randomization into a highly regulated clinical trial addressing a single question, the emergence of pragmatic approaches utilizing clinician enrollment and routinely collected data and outcomes, and alternative study designs such as cluster-randomization and Bayesian analyses randomization provide a robust and efficient way of resolving important treatment dilemmas in routine care.