COVID-19 and the generation of novel scientific knowledge: Research questions and study designs

Using Systems Thinking and Complexity Theory to understand and improve Emergency Medicine: Lessons from COVID-19 in a safety net health system

RATIONALE

COVID-19 has fundamentally changed the practice of Emergency Medicine (EM). Care delivery on the front lines has historically depended upon ostensibly reliable input-output models for staffing, supplies, policies, and therapies. Challenged by the complexity of healthcare during the pandemic, the fallibility of these reductionist models was quickly revealed. Providers and systems quickly had to reconceptualize their dependence on the wider, complex system in which healthcare operates and find adaptive solutions to rapid changes.

AIMS/METHOD

This papers seeks to review and describe how Systems Thinking and Complexity Theory (ST/CT)-concepts, principles, and tools that can be used to understand and impact our constantly evolving health system-can be applied to better understand and enact change in complex settings such as during COVID-19. Some of these ST/CT are described through the real world example of the Alameda Health System Vaccine Taskforce.

RESULTS

ST/CT concepts such as Unintended Consequences, Interrelationships, Emergent Behavior, Feedback Loops, and Path Dependence can help EM providers and planners understand the context in which their system operates. Key principles such as Collaboration, Iterative Learning, and Transformational Leadership can help these actors respond to current and future challenges. The integration of these concepts and principles into the Learning Health System offers a model for tying these key concepts and principles together into an adaptive, cross-sectoral organizational approach.

CONCLUSION

By integrating ST/CT into the practice of EM, we can not only improve our ability to care for patients but also our capacity to understand and strengthen our wider systems of care.

A rapid review of community engagement and informed consent processes for adaptive platform trials and alternative design trials for public health emergencies

Background : Public Health Emergencies (PHE) demand expeditious research responses to evaluate new or repurposed therapies and prevention strategies. Alternative Design Trials (ADTs) and Adaptive Platform Trials (APTs) have enabled efficient large-scale testing of biomedical interventions during recent PHEs. Design features of these trials may have implications for engagement and/or informed consent processes. We aimed to rapidly review evidence on engagement and informed consent for ADTs and APTs during PHE to consider what (if any) recommendations can inform practice. Method : In 2022, we searched 8 prominent databases for relevant peer reviewed publications and guidelines for ADTs/APTs in PHE contexts. Articles were selected based on pre-identified inclusion and exclusion criteria. We reviewed protocols and informed consent documents for a sample of large platform trials and consulted with key informants from ADTs/APT trial teams. Data were extracted and summarised using narrative synthesis. Results : Of the 49 articles included, 10 were guidance documents, 14 discussed engagement, 10 discussed informed consent, and 15 discussed both. Included articles addressed ADTs delivered during the West African Ebola epidemic and APTs delivered during COVID-19. PHE clinical research guidance documents highlight the value of ADTs/APTs and the importance of community engagement, but do not provide practice-specific guidance for engagement or informed consent. Engagement and consent practice for ADTs conducted during the West African Ebola epidemic have been well-documented. For COVID-19, engagement and consent practice was described for APTs primarily delivered in high income countries with well-developed health service structures. A key consideration is strong communication of the complexity of trial design in clear, accessible ways. Conclusion: We highlight key considerations for best practice in community engagement and informed consent relevant to ADTs and APTs for PHEs which may helpfully be included in future guidance. Protocol: The review protocol is published online at Prospero on 15/06/2022: registration number CRD42022334170.