Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement.
BMJ Open Qual
; 9(4)2020 11.
Article
in English
| MEDLINE | ID: covidwho-926426
ABSTRACT
BACKGROUND:
The COVID-19 pandemic represents an unprecedented challenge to healthcare systems and nations across the world. Particularly challenging are the lack of agreed-upon management guidelines and variations in practice. Our hospital is a large, secondary-care government hospital in Kuwait, which has increased its capacity by approximately 28% to manage the care of patients with COVID-19. The surge in capacity has necessitated the redeployment of staff who are not well-trained to manage such conditions. There was a great need to develop a tool to help redeployed staff in decision-making for patients with COVID-19, a tool which could also be used for training.METHODS:
Based on the best available clinical knowledge and best practices, an eight member multidisciplinary group of clinical and quality experts undertook the development of a clinical algorithm-based toolkit to guide training and practice for the management of patients with COVID-19. The team followed Horabin and Lewis' seven-step approach in developing the algorithms and a five-step method in writing them. Moreover, we applied Rosenfeld et al's five points to each algorithm.RESULTS:
A set of seven clinical algorithms and one illustrative layout diagram were developed. The algorithms were augmented with documentation forms, data-collection online forms and spreadsheets and an indicators' reference sheet to guide implementation and performance measurement. The final version underwent several revisions and amendments prior to approval.CONCLUSIONS:
A large volume of published literature on the topic of COVID-19 pandemic was translated into a user-friendly, algorithm-based toolkit for the management of patients with COVID-19. This toolkit can be used for training and decision-making to improve the quality of care provided to patients with COVID-19.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Algorithms
/
Coronavirus Infections
/
Delivery of Health Care
/
Health Plan Implementation
Type of study:
Observational study
/
Prognostic study
Limits:
Female
/
Humans
/
Male
Country/Region as subject:
Asia
Language:
English
Year:
2020
Document Type:
Article
Affiliation country:
Bmjoq-2020-001130
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