From Threatening Chaos to Temporary Order through a Complex Process of Adaptation: A Grounded Theory Study of the Escalation of Intensive Care during the COVID-19 Pandemic

To ensure high-quality care, operationalize resilience and fill the knowledge gap regarding how to improve the prerequisites for resilient performance, it is necessary to understand how adaptive capacity unfolds in practice. The main aim of this research was to explain the escalation process of intensive care during the first wave of the pandemic from a microlevel perspective, including expressions of resilient performance, intervening conditions at the micro-meso-macrolevels and short- and long-term consequences. A secondary aim was to provide recommendations regarding how to optimize the prerequisites for resilient performance in intensive care. A grounded theory methodology was used. First-person stories from different healthcare professionals (n70) in two Swedish regions were analyzed using the constant comparative method. This resulted in a novel conceptual model (including 6 main categories and 24 subcategories), and 41 recommendations. The conclusion of these findings is that the escalation of intensive care can be conceptualized as a transition from threatening chaos to temporary order through a complex process of adaptation. To prepare for the future, the components of space, stuff, staff, system and science, with associated continuity plans, must be implemented, anchored and communicated to actors at all levels of the system.

Drive-Through Medicine: A Novel Health Care Delivery Mechanism for the COVID-19 Pandemic

BACKGROUND

Coronavirus disease 2019 (COVID-19) placed additional strain on an already struggling health care system. In response, novel solutions such as telehealth have been explored, however, there is significant room for innovation in health care delivery.

OBJECTIVES

The aim of our study was to evaluate the effectiveness of a drive-through medical treatment system for evaluating patients with COVID-like symptoms.

METHODS

We designed a prototype drive-through medical treatment facility (DMF) to triage large volumes of patients quickly and efficiently, while fully evaluating, treating, and discharging low-risk patients. A retrospective chart review was performed to extract clinical and logistical metrics.

RESULTS

A total of 2164 patients were evaluated between May 1 and July 1, 2020. Overall accuracy for patient classification was 92.4% (95% confidence interval [CI] 91.2-93.5%). Screening criteria resulted in a return with need for workup or admission rate of 0.25%, yielding a sensitivity of 83.3% (95% CI 65.3-94.4%). Of those presenting to the DMF, 179 patients (8.3%) were diverted to the main emergency department (ED) for further evaluation, of which 14% received diagnostic workups and 5% subsequent admission to an inpatient service, yielding a specificity of 92.8% (95% CI 91.7- 93.9%). Length of stays for those seen in the DMF vs. the main ED (M = 38 min vs 149 min) yielded a mean difference of 111 min per encounter and a total time savings of 3762 h.

CONCLUSION

Drive-through medical systems can accurately triage patients presenting with potential COVID-19 and effectively treat lower-risk patients, thereby reducing ED utilization.

Increased fracture incidence in snow and ice conditions; a model for escalation

Several studies have shown that the incidence of fractures during periods of snow and ice increases significantly and continues to persist despite preventative measures. The studies discussed in this article suggest that these predominantly consist of "walking wounded" with significant increase in demands in specific services such as the emergency department and the trauma and orthopaedic department. Traditionally, the only formal mechanism in place for most hospitals to react to extreme events is to declare a major incident. This is a binary, all or nothing response, and it is questionable whether an increase of snow and ice-related fractures would be justified in triggering such an extreme response. On the other end is the "do nothing" approach, which relies heavily on the professionalism, adaptability, and resilience of the staff to deal with the additional demand. The authors present a graded surge plan model for escalation in key resources, such as staff, space, and supplies in order to achieve the most efficient response ensuring good clinical outcome for patients.