Who Is Next: Patient Prioritization Under Emergency Department Blocking

In “Who Is Next: Patient Prioritization Under Emergency Department Blocking,” Li, Sun, and Hong study how physicians and nurses choose the next patient for treatment in hospital emergency departments (EDs). Using data from a tertiary hospital in Alberta, Canada, they conduct an empirical investigation and find that both clinical factors and resource constraints are considered in patient-prioritization decisions. In particular, discharged patients are prioritized when ED beds are increasingly occupied by boarding patients so as to avoid further blocking the ED. A stylized model is developed to explain the rationale behind the prioritization behavior. Using a simulation study, they show such behavior can improve ED operations by reducing the average patient waiting time and length of stay without adding extra capacity, which results in significant cost savings for hospitals.

Bioethical Concerns During the COVID-19 Pandemic: What Did Healthcare Ethics Committees and Institutions State in Spain?

Objectives: Each new wave of the COVID-19 pandemic invites the possible obligation to prioritize individuals' access to vital resources, and thereby leads to unresolved and important bioethical concerns. Governments have to make decisions to protect access to the health system with equity. The prioritization criteria during a pandemic are both a clinical and legal-administrative decision with ethical repercussion. We aim to analyse the prioritization protocols used in Spain during the pandemic which, in many cases, have not been updated.Method: We carried out a narrative review of 27 protocols of prioritization proposed by healthcare ethics committees, scientific societies and institutions in Spain for this study. The review evaluated shared aspects and unique differences and proffered a bioethical reflection.Results: The research questions explored patient prioritization, the criteria applied and the relative weight assigned to each criterion. There was a need to use several indicators, being morbidity and mortality scales the most commonly used, followed by facets pertaining to disease severity and functional status. Although age was initially considered in some protocols, it cannot be the sole criterion used when assigning care resources.Conclusions: In COVID-19 pandemic there is a need for a unified set of criteria that guarantees equity and transparency in decision-making processes. Establishing treatment indications is not the aim of such criteria, but instead prioritizing access to care resources. In protocols of prioritization, the principle of efficiency must vary according to the principle of equity and the criteria used to guarantee such equity.

Mitigating selection bias in organ allocation models

Background The lung allocation system in the U.S. prioritizes lung transplant candidates based on estimated pre- and post-transplant survival via the Lung Allocation Scores (LAS). However, these models do not account for selection bias, which results from individuals being removed from the waitlist due to receipt of transplant, as well as transplanted individuals necessarily having survived long enough to receive a transplant. Such selection biases lead to inaccurate predictions. Methods We used a weighted estimation strategy to account for selection bias in the pre- and post-transplant models used to calculate the LAS. We then created a modified LAS using these weights, and compared its performance to that of the existing LAS via time-dependent receiver operating characteristic (ROC) curves, calibration curves, and Bland-Altman plots. Results The modified LAS exhibited better discrimination and calibration than the existing LAS, and led to changes in patient prioritization. Conclusions Our approach to addressing selection bias is intuitive and can be applied to any organ allocation system that prioritizes patients based on estimated pre- and post-transplant survival. This work is especially relevant to current efforts to ensure more equitable distribution of organs.

COVID-19 Mass Vaccination Resource Calculator

Background Despite the recent emergency use authorization of two vaccines for the prevention of the 2019 novel coronavirus (COVID-19) disease, vaccination rates are lower than expected. Vaccination efforts may be hampered by supply, delivery, storage, patient prioritization, administration infrastructure or logistics problems. To address the last issue, our institution is sharing publically a calculator to optimize the management of staffing and facility resources in an outpatient mass vaccination effort. Objective By sharing our calculator locally and through this paper, we aim to help health organizations administering vaccines optimize resource allocation while maximizing efficiency. Methods Our calculator determines the maximum number of vaccinations that can be administered per hour, the number of check-in staff (clerks) needed, the number of vaccination staff (nurses) needed, and the required room capacity needed for the vaccination and the mandatory 15-minute observation period after inoculation. Results We provide a functional version of the calculator, allowing users to replicate the calculation for their own vaccine events. Conclusion An efficient and organized vaccination program is critical to halting the spread of COVID-19. By sharing this calculator, it is our hope that other organizations may use it to facilitate rapid and efficient vaccination.

Implementation of Stereotactic Ablative Radiotherapy for the Treatment of Oligometastatic Cancer in Canada

The aim of this Environmental Scan is to identify and describe the use of stereotactic ablative radiotherapy in Canada, the systems in place to manage the treatment of patients with oligometastatic cancer, and the barriers and facilitators to the implementation of this treatment. The findings are based on a literature review, 22 survey responses from stakeholders, and email- and video call-based follow-up consultations with select stakeholders. Ten Canadian jurisdictions were represented by the survey respondents, who were primarily radiation oncologists. Stereotactic ablative radiotherapy for the treatment of oligometastatic cancer is currently being accessed in all Canadian provinces as a standard treatment option. Centres are primarily treating oligometastases in the lungs, bones (non-spine), lymph nodes, spine, and liver. Some cancer care centres have the capacity for stereotactic ablative radiotherapy to treat localized primary tumours but do not treat oligometastatic sites. There is a variation in patient selection criteria and treatment guidelines across Canadian jurisdictions, with most facilities following institutional guidance for the processes required for patient prioritization and treatment. There is a lack of standardized consensus guidelines with common criteria. Reported facilitators for the implementation of stereotactic ablative radiotherapy for the treatment of oligometastatic cancer include access to dedicated equipment and teams. Reported barriers to its implementation include the lack of standardized patient selection and treatment guidelines, and constraints in equipment and staff resources (including time).

Semantic Representation of Patient Triage Data Collected in Emergency Departments

Emergency Department (ED) overcrowding is a major issue for the efficient management of patients. To this end, triage algorithms have been developed to support the task of patient prioritization. In this paper an ontology was designed to represent the knowledge about patient triage procedure in EDs.

Population-level management of Type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health

Objective: To develop and scale algorithm-enabled patient prioritization to improve population-level management of type 1 diabetes (T1D) in a pediatric clinic with fixed resources, using telemedicine and remote monitoring of patients via continuous glucose monitor (CGM) data review. Research Design and Methods: We adapted consensus glucose targets for T1D patients using CGM to identify interpretable clinical criteria to prioritize patients for weekly provider review. The criteria were constructed to manage the number of patients reviewed weekly and identify patients who most needed provider contact. We developed an interactive dashboard to display CGM data relevant for the patients prioritized for review. Results: The introduction of the new criteria and interactive dashboard was associated with a 60% reduction in the mean time spent by diabetes team members who remotely and asynchronously reviewed patient data and contacted patients, from 3.2 +/- 0.20 to 1.3 +/- 0.24 minutes per patient per week. Given fixed resources for review, this corresponded to an estimated 147% increase in weekly clinic capacity. Patients who qualified for and received remote review (n=58) have associated 8.8 percentage points (pp) (95% CI = 0.6-16.9pp) greater time-in-range (70-180 mg/dL) glucoses compared to 25 control patients who did not qualify at twelve months after T1D onset. Conclusions: An algorithm-enabled prioritization of T1D patients with CGM for asynchronous remote review reduced provider time spent per patient and was associated with improved time-in-range.