Patient-level Analysis: Identifying risk factors and supporting capacity planning for COVID-19
Dr Foster has been approached to analyse patterns in patent-level data to understand, for example, why more people have died at one hospital even though the cases are lower. The exploratory data analysis includes identifying the most important risk factors for:
- admission with COVID-19
- treatment in critical care due to COVID-19
- mortality after testing positive for COVID-19
At a trust and site level and compared to a peer group average (based on available data)
What risk factors can we analyse?
A detailed exploratory data analysis can identify potential risk factors leading to a hospital admission due to COVID-19 and the subsequent risk of having to be treated in critical care or risk of mortality.
Cases can be broken down by a number of factors.
Trusts can be compared to a peer group to provide further insights into the most prevalent patient characteristics and conditions of patients admitted with COVID-19.
The analysis can also be compared to Dr Foster’s vulnerability maps in the progression dashboard: https://drfoster.com/2020/04/06/uk-covid-19-progression-dashboard/
The analyses proposed above can be delivered as a Tableau dashboard available to be read using Tableau Reader or as a static report. The data accompanying Tableau can also be provided separately as an Excel or csv file as required.