Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting
Introduction Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disa...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2023-05-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/13/5/e067786.full |
| _version_ | 1797823454502715392 |
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| author | Kamlesh Khunti Vahe Nafilyan Azhar Farooqi Richard Morriss Natalie Armstrong Ash Routen Adam Gordon Neil Bannister Laura Gray Seth Thomas Perrine Machuel Josephine Foubert Helen Colvin |
| author_facet | Kamlesh Khunti Vahe Nafilyan Azhar Farooqi Richard Morriss Natalie Armstrong Ash Routen Adam Gordon Neil Bannister Laura Gray Seth Thomas Perrine Machuel Josephine Foubert Helen Colvin |
| author_sort | Kamlesh Khunti |
| collection | DOAJ |
| description | Introduction Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020–March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures.Methods and analysis This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011–2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic.Ethics and dissemination This study has approval from the National Statistician’s Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website. |
| first_indexed | 2024-03-13T10:23:14Z |
| format | Article |
| id | doaj.art-def905c34f484ae49b6f2fa9d675e78f |
| institution | Directory Open Access Journal |
| issn | 2044-6055 |
| language | English |
| last_indexed | 2024-03-13T10:23:14Z |
| publishDate | 2023-05-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj.art-def905c34f484ae49b6f2fa9d675e78f2023-05-20T00:30:07ZengBMJ Publishing GroupBMJ Open2044-60552023-05-0113510.1136/bmjopen-2022-067786Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data settingKamlesh Khunti0Vahe Nafilyan1Azhar Farooqi2Richard Morriss3Natalie Armstrong4Ash Routen5Adam Gordon6Neil Bannister7Laura Gray8Seth Thomas9Perrine Machuel10Josephine Foubert11Helen Colvin12Diabetes Research Centre, University of Leicester, Leicester, UK1 Health Analysis Division, Office for National Statistics, Newport, UKsenior clinical research fellowFaculty of Medicine and Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UKDepartment of Health Sciences, University of Leicester, Leicester, UKNIHR Applied Research Collaboration-East Midlands (ARC-EM), Leicester, UKUnit of Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Derby Medical School, Royal Derby Hospital, Derby, UKHealth Analysis, Office for National Statistics, Newport, UKWestat Inc, Rockville, Maryland, USAOffice for National Statistics, Newport, UKOffice for National Statistics, Newport, UKOffice for National Statistics, Newport, UKOffice for National Statistics, Newport, UKIntroduction Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020–March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures.Methods and analysis This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011–2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic.Ethics and dissemination This study has approval from the National Statistician’s Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website.https://bmjopen.bmj.com/content/13/5/e067786.full |
| spellingShingle | Kamlesh Khunti Vahe Nafilyan Azhar Farooqi Richard Morriss Natalie Armstrong Ash Routen Adam Gordon Neil Bannister Laura Gray Seth Thomas Perrine Machuel Josephine Foubert Helen Colvin Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting BMJ Open |
| title | Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting |
| title_full | Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting |
| title_fullStr | Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting |
| title_full_unstemmed | Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting |
| title_short | Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting |
| title_sort | study protocol for the use of time series forecasting and risk analyses to investigate the effect of the covid 19 pandemic on hospital admissions associated with new onset disability and frailty in a national linked electronic health data setting |
| url | https://bmjopen.bmj.com/content/13/5/e067786.full |
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