This qualitative study investigates themes in the experiences of triage team members participating in statewide simulations of health care triage under circumstances of scarce resource allocation during the COVID-19 pandemic in Washington State.

Perspectives of Triage Team Members Participating in Statewide Triage Simulations for Scarce Resource Allocation During the COVID-19 Pandemic in Washington State

Inter-hospital patient transfers to hospitals with greater resource availability and expertise may improve clinical outcomes. However, there is little guidance regarding how patient transfer requests should be prioritized when hospital resources become scarce.To understand the experiences of healthcare workers involved in the process of accepting inter-hospital patient transfers during a pandemic surge and determine factors impacting inter-hospital patient transfer decision-making.We conducted a qualitative study consisting of semi-structured interviews between October 2021 and February 2022.Eligible participants were physicians, nurses, and non-clinician administrators involved in the process of accepting inter-hospital patient transfers. Participants were recruited using maximum variation sampling.Semi-structured interviews were conducted with healthcare workers across Michigan.Twenty-one participants from 15 hospitals were interviewed (45.5% of eligible hospitals). About half (52.4%) of participants were physicians, 38.1% were nurses, and 9.5% were non-clinician administrators. Three domains of themes impacting patient transfer decision-making emerged: decision-maker, patient, and environmental factors. Decision-makers described a lack of guidance for transfer decision-making. Patient factors included severity of illness, predicted chance of survival, need for specialized care, and patient preferences for medical care. Decision-making occurred within the context of environmental factors including scarce resources at accepting and requesting hospitals, organizational changes to transfer processes, and alternatives to patient transfer including use of virtual care. Participants described substantial moral distress related to transfer triaging.A lack of guidance in transfer processes may result in considerable variation in the patients who are accepted for inter-hospital transfer and in substantial moral distress among decision-makers involved in the transfer process. Our findings identify potential organizational changes to improve the inter-hospital transfer process and alleviate the moral distress experienced by decision-makers. 

/pdf/inter-hospital-transfer-decision-making-during-the-covid-19-1oq5g25q.pdf

Inter-hospital Transfer Decision-making During the COVID-19 Pandemic: a Qualitative Study

Simulation and evaluation of a prioritization protocol at a German university hospital using a convergent parallel mixed methods design.Prospective single-center cohort study with a quantitative analysis of ICU patients and qualitative content analysis of two focus groups with intensivists.Five ICUs of internal medicine and anesthesiology at a German university hospital.Adult critically ill ICU patients ( n = 53).After training the attending senior ICU physicians ( n = 13) in rationing, an impending ICU congestion was simulated. All ICU patients were rated according to their likelihood to survive their acute illness (good-moderate-unfavorable). From each ICU, the two patients with the most unfavorable prognosis ( n = 10) were evaluated by five prioritization teams for triage.Patients nominated for prioritization visit ( n = 10) had higher Sequential Organ Failure Assessment scores and already a longer stay at the hospital and on the ICU compared with the other patients. The order within this worst prognosis group was not congruent between the five teams. However, an in-hospital mortality of 80% confirmed the reasonable match with the lowest predicted probability of survival. Qualitative data highlighted the tremendous burden of triage and the need for a team-based consensus-oriented decision-making approach to ensure best possible care and to support professionals. Transparent communication within the teams, the hospital, and to the public was seen as essential for prioritization implementation.To mitigate potential bias and to reduce the emotional burden of triage, a consensus-oriented, interdisciplinary, and collaborative approach should be implemented. Prognostic comparative assessment by intensivists is feasible. The combination of long-term ICU stay and consistently high Sequential Organ Failure Assessment scores resulted in a greater risk for triage in patients. It remains challenging to reliably differentiate between patients with very low chances to survive and requires further conceptual and empirical research. 

Preparing for the Worst-Case Scenario in a Pandemic: Intensivists Simulate Prioritization and Triage of Scarce ICU Resources*

COVID-19 pandemic has sent millions of people to hospitals worldwide, exhausting on many occasions the capacity of healthcare systems to provide care patients required to survive. Although several epidemiological research works have contributed a variety of models and approaches to anticipate the pandemic spread, very few have tried to translate the output of these models into hospital service requirements, particularly in terms of bed occupancy, a key question for hospital managers. This paper proposes a tool for predicting the current and future occupancy associated with COVID-19 patients of a hospital to help managers make informed decisions to maximize the availability of hospitalization and intensive care unit (ICU) beds and ensure adequate access to services for confirmed COVID-19 patients. The proposed tool uses a discrete event simulation approach that uses archetypes (i.e., empirical models of trajectories) extracted from empirical analysis of actual patient trajectories. Archetypes can be fitted to trajectories observed in different regions or to the particularities of current and forthcoming variants using a rather small amount of data. Numerical experiments on realistic instances demonstrate the accuracy of the tool's predictions and illustrate how it can support managers in their daily decisions concerning the system's capacity and ensure patients the access the resources they require. 

https://doi.org/10.1016/j.health.2023.100197

A simulation model for predicting hospital occupancy for Covid-19 using archetype analysis

Severe staffing shortages have emerged as a prominent threat to maintaining usual standards of care during the COVID-2019 pandemic. In dire settings of crisis capacity, healthcare systems assume the ethical duty to maximise aggregate population-level benefit of existing resources. To this end, existing plans for rationing mechanical ventilators and intensive care unit beds in crisis capacity focus on selecting individual patients who are most likely to survive and prioritising these patients to receive scarce resources. However, staffing capacity is conceptually different from availability of these types of discrete resources, and the existing strategy of identifying and prioritising patients with the best prognosis cannot be readily adapted to fit this real-world scenario. We propose that two alternative approaches to staffing resource allocation offer a better conceptual fit: (1) prioritise the worst off: restrict access to acute care services and hospital admission for patients at relatively low clinical risk and (2) prioritise staff interventions with high near-term value: universally restrict selected interventions and treatments that require substantial staff time and/or energy but offer minimal near-term patient benefit. These strategies—while potentially resulting in care that deviates from usual standards–support the goal of maximising the aggregate benefit of scarce resources in crisis capacity settings triggered by staffing shortages. This ethical framework offers a foundation to support institutional leaders in developing operationalisable crisis capacity policies that promote fairness and support healthcare workers.

https://jme.bmj.com/content/medethics/early/2022/07/01/jme-2022-108262.full.pdf

Staffing crisis capacity: a different approach to healthcare resource allocation for a different type of scarce resource

Abstract Objective: Plans for allocation of scarce life-sustaining resources during the coronavirus disease 2019 (COVID-19) pandemic often include triage teams, but operational details are lacking, including what patient information is needed to make triage decisions. Methods: A Delphi study among Washington state disaster preparedness experts was performed to develop a list of patient information items needed for triage team decision-making during the COVID-19 pandemic. Experts proposed and rated their agreement with candidate information items during asynchronous Delphi rounds. Consensus was defined as ≥80% agreement. Qualitative analysis was used to describe considerations arising in this deliberation. A timed simulation was performed to evaluate feasibility of data collection from the electronic health record. Results: Over 3 asynchronous Delphi rounds, 50 experts reached consensus on 24 patient information items, including patients’ age, severe or end-stage comorbidities, the reason for and timing of admission, measures of acute respiratory failure, and clinical trajectory. Experts weighed complex considerations around how information items could support effective prognostication, consistency, accuracy, minimizing bias, and operationalizability of the triage process. Data collection took a median of 227 seconds (interquartile range = 205, 298) per patient. Conclusions: Experts achieved consensus on patient information items that were necessary and appropriate for informing triage teams during the COVID-19 pandemic.

/pdf/patient-information-items-needed-to-guide-the-allocation-of-3i74lds7.pdf

Patient Information Items Needed to Guide the Allocation of Scarce Life-Sustaining Resources: A Delphi Study of Multidisciplinary Experts

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Perspectives of Triage Team Members Participating in Statewide Triage Simulations for Scarce Resource Allocation During the COVID-19 Pandemic in Washington State

Staffing crisis capacity: a different approach to healthcare resource allocation for a different type of scarce resource

Patient Information Items Needed to Guide the Allocation of Scarce Life-Sustaining Resources: A Delphi Study of Multidisciplinary Experts