mortality among care home residents in england during the first and second waves of CORD-Papers-2022-06-02 (Version 1)

Title: Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an observational study of 4.3 million adults over the age of 65
Abstract: BACKGROUND: Residents in care homes have been severely impacted by COVID-19. We describe trends in the mortality risk among residents of care homes compared to private homes. METHODS: On behalf of NHS England we used OpenSAFELY-TPP to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to Care and Quality Commission data. FINDINGS: We included 4340648 people aged 65 years or older on the 1st of February 2019 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to those in private housing in February 2019: comparative mortality figure (CMF) = 10.59 (95%CI = 9.51 11.81) among women and 10.87 (9.93 11.90) among men. By April 2020 these relative differences had increased to more than 17 times with CMFs of 17.57 (16.43 18.79) among women and 18.17 (17.22 19.17) among men. CMFs did not increase during the second wave despite a rise in the absolute age-standardised COVID-19 mortality risks. INTERPRETATION: COVID-19 has had a disproportionate impact on the mortality of care home residents in England compared to older residents of private homes but only in the first wave. This may be explained by a degree of acquired immunity improved protective measures or changes in the underlying frailty of the populations. The care home population should be prioritised for measures aimed at controlling COVID-19. FUNDING: Medical Research Council MR/V015737/1
Published: 2022-01-10
Journal: Lancet Reg Health Eur
DOI: 10.1016/j.lanepe.2021.100295
DOI_URL: http://doi.org/10.1016/j.lanepe.2021.100295
Author Name: Schultze Anna
Author link: https://covid19-data.nist.gov/pid/rest/local/author/schultze_anna
Author Name: Nightingale Emily
Author link: https://covid19-data.nist.gov/pid/rest/local/author/nightingale_emily
Author Name: Evans David
Author link: https://covid19-data.nist.gov/pid/rest/local/author/evans_david
Author Name: Hulme William
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hulme_william
Author Name: Rosello Alicia
Author link: https://covid19-data.nist.gov/pid/rest/local/author/rosello_alicia
Author Name: Bates Chris
Author link: https://covid19-data.nist.gov/pid/rest/local/author/bates_chris
Author Name: Cockburn Jonathan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/cockburn_jonathan
Author Name: MacKenna Brian
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mackenna_brian
Author Name: Curtis Helen J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/curtis_helen_j
Author Name: Morton Caroline E
Author link: https://covid19-data.nist.gov/pid/rest/local/author/morton_caroline_e
Author Name: Croker Richard
Author link: https://covid19-data.nist.gov/pid/rest/local/author/croker_richard
Author Name: Bacon Seb
Author link: https://covid19-data.nist.gov/pid/rest/local/author/bacon_seb
Author Name: McDonald Helen I
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mcdonald_helen_i
Author Name: Rentsch Christopher T
Author link: https://covid19-data.nist.gov/pid/rest/local/author/rentsch_christopher_t
Author Name: Bhaskaran Krishnan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/bhaskaran_krishnan
Author Name: Mathur Rohini
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mathur_rohini
Author Name: Tomlinson Laurie A
Author link: https://covid19-data.nist.gov/pid/rest/local/author/tomlinson_laurie_a
Author Name: Williamson Elizabeth J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/williamson_elizabeth_j
Author Name: Forbes Harriet
Author link: https://covid19-data.nist.gov/pid/rest/local/author/forbes_harriet
Author Name: Tazare John
Author link: https://covid19-data.nist.gov/pid/rest/local/author/tazare_john
Author Name: Grint Daniel
Author link: https://covid19-data.nist.gov/pid/rest/local/author/grint_daniel
Author Name: Walker Alex J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/walker_alex_j
Author Name: Inglesby Peter
Author link: https://covid19-data.nist.gov/pid/rest/local/author/inglesby_peter
Author Name: DeVito Nicholas J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/devito_nicholas_j
Author Name: Mehrkar Amir
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mehrkar_amir
Author Name: Hickman George
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hickman_george
Author Name: Davy Simon
Author link: https://covid19-data.nist.gov/pid/rest/local/author/davy_simon
Author Name: Ward Tom
Author link: https://covid19-data.nist.gov/pid/rest/local/author/ward_tom
Author Name: Fisher Louis
Author link: https://covid19-data.nist.gov/pid/rest/local/author/fisher_louis
Author Name: Green Amelia CA
Author link: https://covid19-data.nist.gov/pid/rest/local/author/green_amelia_ca
Author Name: Wing Kevin
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wing_kevin
Author Name: Wong Angel YS
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wong_angel_ys
Author Name: McManus Robert
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mcmanus_robert
Author Name: Parry John
Author link: https://covid19-data.nist.gov/pid/rest/local/author/parry_john
Author Name: Hester Frank
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hester_frank
Author Name: Harper Sam
Author link: https://covid19-data.nist.gov/pid/rest/local/author/harper_sam
Author Name: Evans Stephen JW
Author link: https://covid19-data.nist.gov/pid/rest/local/author/evans_stephen_jw
Author Name: Douglas Ian J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/douglas_ian_j
Author Name: Smeeth Liam
Author link: https://covid19-data.nist.gov/pid/rest/local/author/smeeth_liam
Author Name: Eggo Rosalind M
Author link: https://covid19-data.nist.gov/pid/rest/local/author/eggo_rosalind_m
Author Name: Goldacre Ben
Author link: https://covid19-data.nist.gov/pid/rest/local/author/goldacre_ben
Author Name: Leon David A
Author link: https://covid19-data.nist.gov/pid/rest/local/author/leon_david_a
sha: 2bf56026db81cf3dc88d7da4eb5ccfd8caea8cd7
license: cc-by
license_url: https://creativecommons.org/licenses/by/4.0/
source_x: Elsevier; Medline; PMC; WHO
source_x_url: https://www.elsevier.com/https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/https://www.who.int/
pubmed_id: 35036983
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/35036983
pmcid: PMC8743167
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8743167
url: https://api.elsevier.com/content/article/pii/S2666776221002817 https://doi.org/10.1016/j.lanepe.2021.100295 https://www.sciencedirect.com/science/article/pii/S2666776221002817 https://www.ncbi.nlm.nih.gov/pubmed/35036983/
has_full_text: TRUE
Keywords Extracted from Text Content: NHS women CMF men COVID-19 4,340,648 people 1/2/2019 NHS G30 centre 95,215 UK Stockholm, Sweden PIs https://github.com/opensafely/carehome-non carehome-death-research/tree/master/codelists COPI people men CMF F01, F02, F03 COVID-19. IgG antibodies 4a-4c COVID-19 Figure 3a LTC residents liver patient kidney ISO S2a-S2c S1a-c SHA-512 GSK DSR lockdown women Patient ONS patients English residents 425,408 UK Health Service S2a S8a-c non-COVID-19 PPE CMF Office women CMF cardiovascular cell SARS-CoV-2 B.1.1.7 appendix OpenSAFELY NHS IG GlaxoSmithKline ( 4,340,648 Mohn-Westlake London. VPN allcause, Figure 2a À 2c persons cardiac DSRs men cancer NHS lanepe.2021.100295
Extracted Text Content in Record: First 5000 Characters:Background Residents in care homes have been severely impacted by COVID-19. We describe trends in the mortality risk among residents of care homes compared to private homes. Methods On behalf of NHS England we used OpenSAFELY-TPP to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to Care and Quality Commission data. Findings We included 4,340,648 people aged 65 years or older on the 1st of February 2019, 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to those in private housing in February 2019: comparative mortality figure (CMF) = 10.59 (95%CI = 9.51, 11.81) among women, and 10.87 (9.93, 11.90) among men. By April 2020 these relative differences had increased to more than 17 times with CMFs of 17. 57 (16.43, 18.79) among women and 18.17 (17.22, 19.17) among men. CMFs did not increase during the second wave, despite a rise in the absolute age-standardised COVID-19 mortality risks. The COVID-19 pandemic has had a major adverse effect on the residents of care homes in the UK and in many other countries. 1 By the end of the first wave in England and Wales (August 2020) the Office for National Statistics (ONS) estimated that almost a third of all deaths occurring among care home residents in the pandemic had been due to COVID-19. 2 These 19 thousand COVID-19 deaths of care home residents accounted for approximately 40% of all COVID-19 deaths in England and Wales. 3 However, this is likely to be an underestimate given the low levels of testing in care homes at the time. The Health Foundation estimated that there were approximately 10,000 additional so-called "excess" deaths among care home residents in England alone during the first wave. 3 In addition, it has been found that the vast majority of excess care home deaths in England and Scotland occurred in care homes where there had been COVID-19 outbreaks. 4, 5 The impact of the COVID-19 pandemic on the risk of death among care home residents in England has not yet been comprehensively investigated and placed in the context of the mortality of people living in private residences, in part because of the absence of a national registry of care home residents. Working on behalf of NHS England, our aim was to provide the first direct estimates of mortality risks of care home residents compared to that of individuals in private residences across a period starting in February 2019 through waves 1 and 2 ending in March 2021. Adequate quantification of these differences is an essential component of learning the lessons of COVID-19. Our methods were developed to provide monthly updated estimates of the population at risk and deaths for residents in care homes and those in private households across our follow-up period from 1 February 2019 to 31 March 2021 in a large electronic health record database of patients registered with General Practices (GPs) in England. Primary care records managed by the GP software provider TPP were linked to ONS death data through OpenSAFELY, a data analytics platform created by our team on behalf of NHS England to address urgent COVID-19 research questions (https://opensafely.org). OpenSAFELY provides a secure software interface allowing the analysis of pseudonymized primary care patient records from England in near real-time within the TPP Electronic Health Records (EHR) vendor's highly secure data centre, avoiding the need for large volumes of potentially disclosive pseudonymized patient data to be transferred off-site. This together with other technical and organisational controls, minimizes any risk of re-identification. Pseudonymized datasets from other data providers are securely provided to the TPP and linked to the primary care data. The dataset analysed within OpenSAFELY is based on 24 million people currently registered with GP surgeries using TPP SystmOne software. It includes pseudonymized data such as coded diagnoses, medications and physiological parameters. No free text data are included. Further details on our information governance can be found in the appendix, under information governance and ethics. Evidence before this study Residents of care homes in the UK and elsewhere are known to have been severely affected by the COVID-19 pandemic. In the UK this has been clearly demonstrated by very large increases in the number of excess deaths occurring in care homes in first and second waves 2020/21, and by studies in England, Scotland and Wales up to the summer of 2020. However, to date there have not been any large-scale studies of care home mortality in England over the first two pandemic waves that have been based on follow-up of care home residents regardless of whether they died where they lived or in hospital. Much of previously published literature on COVID-
Keywords Extracted from PMC Text: wave.30 Office persons occurred.25 CEM patient SD, TW S2a BMK NHS appendix VPN UKRI men CMF census.19 residents survivors ONS DSRs men lockdown vaccinated.31 liver S1a-c G30 countries.1 NJDV London.20 Figure 2a – 2c SH, SJWE known6 GlaxoSmithKline ( 4a-4c Mohn-Westlake S8a-c FH kidney AG 95,215 cardiovascular LTC residents UK patient consent.39 English residents harvesting'28 CMF ISO COPI 4,340,648 non-COVID-19 patients time-point.12 DSR homes.11 425,408 CB GSK AYSW Sir Henry Wellcome Fellowship funded by the Wellcome Trust (201375/Z/16/Z) women CMF authors27 DG women " RMM IgG antibodies AM limitations.6,17,18 Scotland.4,11 IJD 6.44 – 729.76 cancer BG COVID-19 NIHR, F01, F02, F03 NHS IG Toolkit cardiac EJW SHA-512 KB COVID-19.2 2020.22 approaches.10 PIs centre AJW OpenSAFELY GH BG's grants studies.7 SARS-CoV-2 B.1.1.7 CTR S2a-S2c Figure 3a-3c CB JP JC SH SB DE PI CM RMM Stockholm, Sweden JC, Patient LAT staff-to-bed ratios26 KW, AYSW cell counts.38 people PI UK Health Service wave.24 PPE AR
Extracted PMC Text Content in Record: First 5000 Characters:The COVID-19 pandemic has had a major adverse effect on the residents of care homes in the UK and in many other countries.1 By the end of the first wave in England and Wales (August 2020) the Office for National Statistics (ONS) estimated that almost a third of all deaths occurring among care home residents in the pandemic had been due to COVID-19.2 These 19 thousand COVID-19 deaths of care home residents accounted for approximately 40% of all COVID-19 deaths in England and Wales.3 However, this is likely to be an underestimate given the low levels of testing in care homes at the time. The Health Foundation estimated that there were approximately 10,000 additional so-called "excess" deaths among care home residents in England alone during the first wave.3 In addition, it has been found that the vast majority of excess care home deaths in England and Scotland occurred in care homes where there had been COVID-19 outbreaks.4,5 The impact of the COVID-19 pandemic on the risk of death among care home residents in England has not yet been comprehensively investigated and placed in the context of the mortality of people living in private residences, in part because of the absence of a national registry of care home residents. Working on behalf of NHS England, our aim was to provide the first direct estimates of mortality risks of care home residents compared to that of individuals in private residences across a period starting in February 2019 through waves 1 and 2 ending in March 2021. Adequate quantification of these differences is an essential component of learning the lessons of COVID-19. Primary care records managed by the GP software provider TPP were linked to ONS death data through OpenSAFELY, a data analytics platform created by our team on behalf of NHS England to address urgent COVID-19 research questions (https://opensafely.org). OpenSAFELY provides a secure software interface allowing the analysis of pseudonymized primary care patient records from England in near real-time within the TPP Electronic Health Records (EHR) vendor's highly secure data centre, avoiding the need for large volumes of potentially disclosive pseudonymized patient data to be transferred off-site. This together with other technical and organisational controls, minimizes any risk of re-identification. Pseudonymized datasets from other data providers are securely provided to the TPP and linked to the primary care data. The dataset analysed within OpenSAFELY is based on 24 million people currently registered with GP surgeries using TPP SystmOne software. It includes pseudonymized data such as coded diagnoses, medications and physiological parameters. No free text data are included. Further details on our information governance can be found in the appendix, under information governance and ethics. We extracted 26 monthly cohorts of people aged 65 years or older with a valid address registered with a TPP practice on the 1st of every month from 1st February 2019 until 31st March 2021. Valid address data is missing for a small proportion of individuals aged 65 years or older registered with TPP practices (1.1%). The exposure of interest was residency in a care or nursing home on the 1st of each month. The identification of care homes in OpenSAFELY has been previously described.6 Briefly, the address an individual used to register with their GP was matched to the Care Quality Commission (CQC) registry of public and privately owned old-age care homes. Natural language processing was applied to the addresses to account for spelling inconsistencies, and data cleaning based on the number of residents at a given address was also undertaken. This process allowed us to assign to each individual their expected care home status at any point in time. Individuals who were not classified as being a care home resident were considered to be living in a private household, the latter referred to subsequently as private homes. The outcome of interest was mortality captured by the Office for National Statistics (ONS). COVID-19 deaths were defined as having an underlying or secondary cause of death listed as COVID-19 (ICD-10 codes U07.1 or U07.2). Specific non-COVID-19 underlying causes of death of interest were also described: deaths due to cancer (ICD-10 chapter code C), cardiovascular disease (ICD-10 chapter I), respiratory disease (ICD-10 chapter J) and dementia (ICD-10 codes F00, F01, F02, F03 and G30). Deaths with any of these underlying causes but a secondary cause of death listed as COVID-19 were considered to be due to COVID-19. The demographic and clinical characteristics considered were age, gender, self-reported ethnicity (5 categories), Nomenclature of Territorial Units for Statistics geographical region of the GP practice, quintile of index of multiple deprivation, stroke, dementia, diabetes, chronic kidney disease, cancer, chronic liver disease, chronic cardiac disease and chronic respiratory disease (https://github.com/opensafely/carehome-n
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