Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19–a data-driven retrospective cohort study

Mizani, Mehrdad A. and Dashtban, Muhammad and Pasea, Laura and Lai, Alvina and Thygesen, Johan Hilge, Chris Tomlinson, and Handy, Alex and Mamza, Jil Billy and Morris, Tamsin and Khalid, Sara and Zaccardi, Francesco and Macleod, Mary J. and Torabi, Fatemeh and Canoy, Dexter and Akbari, Ashley and Berry, Colin and Bolton, Thomas and Nolan, John and Khunti, Kamlesh and Denaxas, Spiros and Hemingway, Harry and Sudlow, Cathie and Banerjee, Amitava and Consortium, CVD-COVID-UK

November 2022

Type

Journal article

Publication

Journal of the Royal Society of Medicine

Twitter thread by Prof Ami Banerjee summarising key results

PREPRINT.Our latest research led by @mehrdad_mizani with a big @BHFDataScience @HDR_UK team. Using National Electronic Health Records for Pandemic Preparedness:Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19.https://t.co/lgPaUjMILg (1/2) pic.twitter.com/IcqvcZxd0f
— Prof Amitava Banerjee💙 (@amibanerjee1) March 9, 2022

📺 BHF Data Science Centre seminar by Dr Mehrdad Mizani

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19–a data-driven retrospective cohort study

Chris Tomlinson

MBBS BSc MRes DMCC MRCA
Senior Research Fellow in Health Data Science

Related

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19–a data-driven retrospective cohort study

Chris Tomlinson

MBBS BSc MRes DMCC MRCASenior Research Fellow in Health Data Science

Related

MBBS BSc MRes DMCC MRCA
Senior Research Fellow in Health Data Science