Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement
| Autor: | Hossam Elamir, Mohammad Galal, Mohammed Shamsah, Lamiaa Ali, Shams Abdelraheem, Huda Alfoudri, Ibtissam Abdo, Ahmed Salem |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Male
Decision support system Quality management decision support Computer science Leadership and Management Quality Improvement Report Best practice media_common.quotation_subject Pneumonia Viral 030204 cardiovascular system & hematology clinical quality improvement 03 medical and health sciences Betacoronavirus 0302 clinical medicine Documentation Multidisciplinary approach Humans Performance measurement Quality (business) 030212 general & internal medicine Pandemics media_common Government lcsh:R5-920 SARS-CoV-2 Health Policy Public Health Environmental and Occupational Health Health Plan Implementation COVID-19 performance measures critical care Kuwait Female lcsh:Medicine (General) Coronavirus Infections Algorithm clinical practice guidelines Delivery of Health Care Algorithms |
| Zdroj: | BMJ Open Quality BMJ Open Quality, Vol 9, Iss 4 (2020) |
| ISSN: | 2399-6641 |
| Popis: | BackgroundThe 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.MethodsBased 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.ResultsA 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.ConclusionsA 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. |
| Databáze: | OpenAIRE |
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