Prediction of hospital bed capacity during the COVID- 19 pandemic.
BMC Health Serv Res
; 21(1): 468, 2021 May 18.
Article
in English
| MEDLINE | ID: covidwho-1234558
ABSTRACT
BACKGROUND:
Prediction of the necessary capacity of beds by ward type (e.g. ICU) is essential for planning purposes during epidemics, such as the COVID- 19 pandemic. The COVID- 19 taskforce within the Ghent University hospital made use of ten-day forecasts on the required number of beds for COVID- 19 patients across different wards.METHODS:
The planning tool combined a Poisson model for the number of newly admitted patients on each day with a multistate model for the transitions of admitted patients to the different wards, discharge or death. These models were used to simulate the required capacity of beds by ward type over the next 10 days, along with worst-case and best-case bounds.RESULTS:
Overall, the models resulted in good predictions of the required number of beds across different hospital wards. Short-term predictions were especially accurate as these are less sensitive to sudden changes in number of beds on a given ward (e.g. due to referrals). Code snippets and details on the set-up are provided to guide the reader to apply the planning tool on one's own hospital data.CONCLUSIONS:
We were able to achieve a fast setup of a planning tool useful within the COVID- 19 pandemic, with a fair prediction on the needed capacity by ward type. This methodology can also be applied for other epidemics.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pandemics
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
BMC Health Serv Res
Journal subject:
Health Services Research
Year:
2021
Document Type:
Article
Affiliation country:
S12913-021-06492-3
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