Affiliations 

  • 1 Anaesthesia and Intensive Care Department, Sabah Al Ahmad Urology Centre, Ministry of Health, Sabah, Kuwait
  • 2 Quality and Accreditation Directorate, Ministry of Health, Safat, Kuwait [email protected]
  • 3 Anaesthesia, Critical Care and Pain Management Department, Adan Hospital, Ministry of Health, Hadiya, Kuwait
  • 4 Critical Care Department, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
  • 5 Quality and Accreditation Directorate, Ministry of Health, Safat, Kuwait
BMJ Open Qual, 2020 Nov;9(4).
PMID: 33199287 DOI: 10.1136/bmjoq-2020-001130

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.