Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement

A forecasting tool for a hospital to plan inbound transfers of COVID-19 patients from other regions

BACKGROUND

In April 2021, the province of Ontario, Canada, was at the peak of its third wave of the COVID-19 pandemic. Intensive Care Unit (ICU) capacity in the Toronto metropolitan area was insufficient to handle local COVID patients. As a result, some patients from the Toronto metropolitan area were transferred to other regions.

METHODS

A spreadsheet-based Monte Carlo simulation tool was built to help a large tertiary hospital plan and make informed decisions about the number of transfer patients it could accept from other hospitals. The model was implemented in Microsoft Excel to enable it to be widely distributed and easily used. The model estimates the probability that each ward will be overcapacity and percentiles of utilization daily for a one-week planning horizon.

RESULTS

The model was used from May 2021 to February 2022 to support decisions about the ability to accept transfers from other hospitals. The model was also used to ensure adequate inpatient bed capacity and human resources in response to various COVID-related scenarios, such as changes in hospital admission rates, managing the impact of intra-hospital outbreaks and balancing the COVID response with planned hospital activity.

CONCLUSIONS

Coordination between hospitals was necessary due to the high stress on the health care system. A simple planning tool can help to understand the impact of patient transfers on capacity utilization and improve the confidence of hospital leaders when making transfer decisions. The model was also helpful in investigating other operational scenarios and may be helpful when preparing for future outbreaks or public health emergencies.

Resource utilization and preparedness within the COVID-19 pandemic in Tunisian medical intensive care units: A nationwide retrospective multicentre observational study

BACKGROUND

The worldwide SARS-CoV-2 pandemic represents the most recent global healthcare crisis. While all healthcare systems suffered facing the immense burden of critically-ill COVID-19 patients, the levels of preparedness and adaptability differed highly between countries.

AIM

to describe resource mobilization throughout the COVID-19 waves in Tunisian University Medical Intensive Care Units (MICUs) and to identify discrepancies in preparedness between the provided and required resource.

METHODS

This is a longitudinal retrospective multicentre observational study conducted between March 2020 and May 2022 analyzing data from eight University MICUs. Data were collected at baseline and at each bed expansion period in relation to the nation's four COVID-19 waves. Data collected included epidemiological, organizational and management trends and outcomes of COVID-19 and non-COVID-19 admissions.

RESULTS

MICU-beds increased from 66 to a maximum of 117 beds. This was possible thanks to equipping pre-existing non-functional MICU beds (n = 20) and creating surge ICU-beds in medical wards (n = 24). MICU nurses increased from 53 to 200 of which 99 non-ICU nurses, by deployment from other departments and temporary recruitment. The nurse-to-MICU-bed ratio increased from 1:1 to around 1·8:1. Only 55% of beds were single rooms, 80% were equipped with ICU ventilators. These MICUs managed to admit a total of 3368 critically-ill patients (15% of hospital admissions). 33·2% of COVID-19-related intra-hospital deaths occurred within the MICUs.

CONCLUSION

Despite a substantial increase in resource mobilization during the COVID-19 pandemic, the current study identified significant persisting discrepancies between supplied and required resource, at least partially explaining the poor overall prognosis of critically-ill COVID-19 patients.

Health innovations in response to the COVID-19 pandemic: perspectives from the Eastern Mediterranean Region

BACKGROUND

This paper aims to document the numerous health innovations developed in response to the COVID-19 crisis in the Eastern Mediterranean Region (EMR) using a scoping review approach.

METHODS

A literature search was conducted using PubMed, the Eastern Mediterranean Health Journal, the Index Medicus for EMR to identify peer-reviewed articles between December 2019 and November 2020 and WHO and ministries of health websites for grey literature. Following an initial review, full-text screening identified studies reporting on health innovations in response to the COVID-19 pandemic in the region.

RESULTS

This review describes 82 health innovations reported from 20 countries across the region: 80% (n = 66) were digital and technology-based products and services including health care delivery (n = 25), public health informatics (n = 24) and prevention (n = 17); 20% (n = 16) were innovative processes including health care delivery (n = 8), educational programmes (n = 6) and community engagement (n = 2).

CONCLUSION

The speed with which these technologies were deployed in different contexts demonstrates their ease of adoption and manageability and thus can be considered as the most scalable. Strengthened frameworks to protect users' privacy, documentation and evaluation of impact of innovations, and training of health care professionals are fundamental for promoting health innovations in the EMR.

Rationalising requests for preoperative sleep studies and postoperative HDU beds: a quality improvement project in paediatric ENT patients undergoing elective surgery

Background

Sleep disordered breathing represents a spectrum of upper airway obstruction including snoring, increased respiratory effort and obstructive sleep apnoea. An increasing demand for paediatric preoperative sleep studies and postoperative high dependency unit (HDU) beds was having a significant impact on service delivery at this ear, nose and throat (ENT) unit.

Methods

Retrospective and prospective review of all paediatric sleep study requests over a 30-month period in a single tertiary ENT department. Data were collected on indication for and result of sleep study, patient outcome, operative details and HDU bed occupancy. During the study period, a ‘Sleep Study’ proforma was introduced which incorporated the ‘I’m Sleepy Score’ (ISS) and ENT-UK national guidelines.

Results

Retrospective review included 198 sleep studies, of which 62% (n=118) showed no evidence of obstructive sleep apnoea (OSA). There was little consistency in patients’ sleep study results and need for monitoring on HDU following adenotonsillectomy. Prospective review following intervention included 60 patients, of which 62% (n=37) showed evidence of OSA. The mean ISS in this cohort was 4.7. Only those with moderate-to-severe OSA or with relevant risk factors underwent overnight HDU observation. The number of sleep study requests fell by >50%; from 11 per month to 5 per month. The total HDU bed occupancy was reduced by 50% following intervention (from n=18 to n=9).

Conclusion

The use of the ISS and incorporation of ENTUK’s recommendations has reduced the number of negative sleep studies being requested and has rationalised the number of paediatric HDU bed requests being made. This has helped provide a prudent elective paediatric ENT service in this unit with corresponding cost benefits.

Dynamic Plus-Delta: an agile debriefing approach centred around variable participant, faculty and contextual factors

The current coronavirus pandemic has necessitated rapid intensive care infrastructure expansion with corresponding demand for training healthcare staff. At the NHS Nightingale Hospital, London, the staff underwent a training programme prior to entering the clinical environment with simulation being a core component. This paper describes the rationale for choosing an initial debriefing model which evolved overtime to consider multiple contextual factors: demands of the clinical environment, the diverse participants and their learning needs, the variable experience of faculty, and the dynamic nature of available debriefing time. The new approach, termed here as the Dynamic Plus-Delta model, blends the traditional Plus-Delta approach with specific dynamic elements which considers the unique demands of rapidly training large number of staff. We outline the core features of this model and detail specific considerations around psychological safety. This debriefing approach can be used in similar simulation intervention settings where rapid training of participants is required with multiple and varying contextual factors.