Journal article 402 views
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
Mehrdad A Mizani,
Ashkan Dashtban,
Laura Pasea,
Alvina G Lai,
Johan Thygesen,
Chris Tomlinson 
,
Alex Handy,
Jil B Mamza,
Tamsin Morris,
Sara Khalid,
Francesco Zaccardi,
Mary Joan Macleod,
Fatemeh Torabi,
Dexter Canoy,
Ashley Akbari ,
Colin Berry,
Thomas Bolton,
John Nolan,
Kamlesh Khunti,
Spiros Denaxas,
Harry Hemingway,
Cathie Sudlow,
Amitava Banerjee ,
(on behalf of the CVD-COVID-UK Consortium),
Fatemeh Torabi
,
Alex Handy,
Jil B Mamza,
Tamsin Morris,
Sara Khalid,
Francesco Zaccardi,
Mary Joan Macleod,
Fatemeh Torabi,
Dexter Canoy,
Ashley Akbari ,
Colin Berry,
Thomas Bolton,
John Nolan,
Kamlesh Khunti,
Spiros Denaxas,
Harry Hemingway,
Cathie Sudlow,
Amitava Banerjee ,
(on behalf of the CVD-COVID-UK Consortium),
Fatemeh Torabi
Journal of the Royal Society of Medicine, Volume: 116, Issue: 1, Pages: 10 - 20
Swansea University Authors:
Ashley Akbari , Fatemeh Torabi
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1177/01410768221131897
Abstract
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
| Published in: | Journal of the Royal Society of Medicine |
|---|---|
| ISSN: | 0141-0768 1758-1095 |
| Published: |
SAGE Publications
2023
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa59637 |
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| spelling |
v2 59637 2022-03-16 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 aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false f569591e1bfb0e405b8091f99fec45d3 0000-0002-5853-4625 Fatemeh Torabi Fatemeh Torabi true false 2022-03-16 HDAT Journal Article Journal of the Royal Society of Medicine 116 1 10 20 SAGE Publications 0141-0768 1758-1095 1 1 2023 2023-01-01 10.1177/01410768221131897 http://dx.doi.org/10.1177/01410768221131897 The document attached is the pre-print of this article. Please follow the DOI for the official publication. COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University 2023-06-01T12:35:25.9078051 2022-03-16T11:43:12.0334530 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Mehrdad A Mizani 1 Ashkan Dashtban 2 Laura Pasea 3 Alvina G Lai 4 Johan Thygesen 5 Chris Tomlinson 0000-0002-0903-5395 6 Alex Handy 7 Jil B Mamza 8 Tamsin Morris 9 Sara Khalid 10 Francesco Zaccardi 11 Mary Joan Macleod 12 Fatemeh Torabi 13 Dexter Canoy 14 Ashley Akbari 0000-0003-0814-0801 15 Colin Berry 16 Thomas Bolton 17 John Nolan 18 Kamlesh Khunti 19 Spiros Denaxas 20 Harry Hemingway 21 Cathie Sudlow 22 Amitava Banerjee 0000-0001-8741-3411 23 (on behalf of the CVD-COVID-UK Consortium) 24 Fatemeh Torabi 0000-0002-5853-4625 25 |
| title |
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 |
| spellingShingle |
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 Ashley Akbari Fatemeh Torabi |
| title_short |
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 |
| title_full |
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 |
| title_fullStr |
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 |
| title_full_unstemmed |
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 |
| title_sort |
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 |
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aa1b025ec0243f708bb5eb0a93d6fb52 f569591e1bfb0e405b8091f99fec45d3 |
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aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari f569591e1bfb0e405b8091f99fec45d3_***_Fatemeh Torabi |
| author |
Ashley Akbari Fatemeh Torabi |
| author2 |
Mehrdad A Mizani Ashkan Dashtban Laura Pasea Alvina G Lai Johan Thygesen Chris Tomlinson Alex Handy Jil B Mamza Tamsin Morris Sara Khalid Francesco Zaccardi Mary Joan Macleod Fatemeh Torabi Dexter Canoy Ashley Akbari Colin Berry Thomas Bolton John Nolan Kamlesh Khunti Spiros Denaxas Harry Hemingway Cathie Sudlow Amitava Banerjee (on behalf of the CVD-COVID-UK Consortium) Fatemeh Torabi |
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Journal article |
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Journal of the Royal Society of Medicine |
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116 |
| container_issue |
1 |
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10 |
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2023 |
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Swansea University |
| issn |
0141-0768 1758-1095 |
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10.1177/01410768221131897 |
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SAGE Publications |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine |
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http://dx.doi.org/10.1177/01410768221131897 |
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2023-01-01T12:35:24Z |
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