Using data to improve public health: COVID-19 secondment
Lead Research Organisation:
University of Liverpool
Department Name: Geography and Planning
Abstract
The COVID-19 pandemic has placed large pressures on the NHS. Initially faced with an uncertain future, the NHS responded through cancelling all non-emergency care to make space to treat patients with COVID-19. While the NHS has demonstrated greater resilience during subsequent waves, there has still been considerable ongoing disruption to the delivery of health care. Cancer screening programmes have been postponed, non-essential surgeries delayed, and GPs have consulted with patients online or via telephones. Some people were discouraged from seeing their GP or visiting a hospital for fear of catching COVID-19 or not wanting to take up resources during a pandemic.
It is plausible that this disruption may have negatively impacted people's health. Where screening was delayed, diseases may have not been diagnosed as early as normal, meaning that when people started treatment they were sicker and treatment was less successful. Delayed care might mean that treatable conditions worsen, impacting people's quality of life. Waiting lists have grown, meaning that people wanting to access new care now face longer waits than before which could have longer-term consequences. While the COVID-19 pandemic has affected everyone, the largest health impacts have been experienced among the most disadvantaged communities and it is likely that the disruption of health care will also have had a greater impact on these communities.
This fellowship will study the impacts of health care disruption in the UK. It will describe the extent of healthcare disruption, identify which parts of the NHS have been affected most, examine who this disruption has affected and how it varies across the UK. We will examine the experiences of those individuals affected by disruption, including whether it has impacted their health, wellbeing and quality of life.
It is plausible that this disruption may have negatively impacted people's health. Where screening was delayed, diseases may have not been diagnosed as early as normal, meaning that when people started treatment they were sicker and treatment was less successful. Delayed care might mean that treatable conditions worsen, impacting people's quality of life. Waiting lists have grown, meaning that people wanting to access new care now face longer waits than before which could have longer-term consequences. While the COVID-19 pandemic has affected everyone, the largest health impacts have been experienced among the most disadvantaged communities and it is likely that the disruption of health care will also have had a greater impact on these communities.
This fellowship will study the impacts of health care disruption in the UK. It will describe the extent of healthcare disruption, identify which parts of the NHS have been affected most, examine who this disruption has affected and how it varies across the UK. We will examine the experiences of those individuals affected by disruption, including whether it has impacted their health, wellbeing and quality of life.
Technical Summary
The COVID-19 pandemic has placed considerable pressures on health systems. During the first COVID-19 wave in the UK, a large amount of NHS activity was postponed to free up capacity to treat patients with COVID-19. Some of this postponed activity was tackled in the summer when cases were lower, but subsequent waves have had similar impacts on healthcare. While there has been greater resilience in the NHS since the first COVID-19 wave, there has still been significant disruption that continues to affect the level of care delivered. It has been estimated that there were 4 million fewer elective treatment pathways in England in 2020 than compared to 2019. Cancer screening programmes, non-essential surgeries and diagnostic procedures were postponed or cancelled. Waiting lists have continued to get longer, resulting in delayed access to care for new treatment pathways.
The impacts of healthcare disruption are unlikely to have been evenly experienced across society. The COVID-19 pandemic has amplified existing social and health inequalities, with groups from low socio-economic status and from marginalised backgrounds disproportionally affected in terms of their health and social outcomes. Early evidence suggests that disruption of elective treatment pathways has been greater in deprived areas. Narrowing health inequalities represents a key government priority, and therefore tackling any inequalities resulting from healthcare disruption will be key to ensure inequalities do not widen as a result of the pandemic.
The fellowship will look to answer the following overarching research question: To what extent did healthcare disruption lead to negative health and wellbeing outcomes, and for whom? To answer this research question, the project will further answer the following ancillary research questions:
1. Who was affected by healthcare disruption during COVID-19 (including during different phases of the pandemic)?
2. Where was healthcare disruption greatest and did this contribute to geographical inequalities in health outcomes?
3. Were people more likely to have a delayed diagnosis of health conditions during COVID-19 (i.e., present at healthcare later than normal), for which conditions, and for whom?
To answer our research questions, we will utilise two main types of data. First, linked longitudinal records will be used to assess the impacts of healthcare disruption. We will use the core UK cohort studies, with their additional COVID-19 waves that ask individuals about their experiences of health care disruption, to examine the impact on individuals. These data have been recently linked to health and care records, allowing analyses to investigate the nature of their disruption and any impacts on health. We will follow established methods deployed by the National Core Studies teams, with individual regression-based models fit on each independent cohort dataset and then a meta-analysis to combine insights collectively.
Second, we will interrogate large administrative records of health care utilisation and mortality outcomes to examine the short- and longer-term population impacts of any disruption on health systems. We will explore general measures that may be influenced by any disruption (e.g., amenable mortality), as well as investigate specific pathways through which disruption may produce negative health outcomes (e.g., cancelled cancer screenings resulting in individuals presenting at later stages of cancers). Analyses will include descriptive statistics, GIS and data visualisation, interrupted time-series and regression-based analyses.
The impacts of healthcare disruption are unlikely to have been evenly experienced across society. The COVID-19 pandemic has amplified existing social and health inequalities, with groups from low socio-economic status and from marginalised backgrounds disproportionally affected in terms of their health and social outcomes. Early evidence suggests that disruption of elective treatment pathways has been greater in deprived areas. Narrowing health inequalities represents a key government priority, and therefore tackling any inequalities resulting from healthcare disruption will be key to ensure inequalities do not widen as a result of the pandemic.
The fellowship will look to answer the following overarching research question: To what extent did healthcare disruption lead to negative health and wellbeing outcomes, and for whom? To answer this research question, the project will further answer the following ancillary research questions:
1. Who was affected by healthcare disruption during COVID-19 (including during different phases of the pandemic)?
2. Where was healthcare disruption greatest and did this contribute to geographical inequalities in health outcomes?
3. Were people more likely to have a delayed diagnosis of health conditions during COVID-19 (i.e., present at healthcare later than normal), for which conditions, and for whom?
To answer our research questions, we will utilise two main types of data. First, linked longitudinal records will be used to assess the impacts of healthcare disruption. We will use the core UK cohort studies, with their additional COVID-19 waves that ask individuals about their experiences of health care disruption, to examine the impact on individuals. These data have been recently linked to health and care records, allowing analyses to investigate the nature of their disruption and any impacts on health. We will follow established methods deployed by the National Core Studies teams, with individual regression-based models fit on each independent cohort dataset and then a meta-analysis to combine insights collectively.
Second, we will interrogate large administrative records of health care utilisation and mortality outcomes to examine the short- and longer-term population impacts of any disruption on health systems. We will explore general measures that may be influenced by any disruption (e.g., amenable mortality), as well as investigate specific pathways through which disruption may produce negative health outcomes (e.g., cancelled cancer screenings resulting in individuals presenting at later stages of cancers). Analyses will include descriptive statistics, GIS and data visualisation, interrupted time-series and regression-based analyses.
People |
ORCID iD |
Mark Green (Principal Investigator / Fellow) |
Publications
Green MA
(2022)
Remote general practitioner consultations during COVID-19.
in The Lancet. Digital health
Green MA
(2023)
Associations between self-reported healthcare disruption due to covid-19 and avoidable hospital admission: evidence from seven linked longitudinal studies for England.
in BMJ (Clinical research ed.)
Description | The research project found the following key findings: - During the COVID-19 pandemic, there were increased use of remote GP consultations. Remote consultations remain high despite society moving 'back to normal'. Remote consultations allowed GPs to see more people than pre-pandemic. Remote consultation patterns were equitable - increases were seen in poorer and richer areas, and there was little patterning by deprivation. - Trends in hospitalisations for reasons that could have been prevented (as a proxy for experiences of healthcare disruption) have varied considerably throughout the COVID-19 pandemic. There were decreased hospitalisations for avoidable reasons during national lockdowns. While there were recovery of these trends outside of lockdowns, they did not reach the same levels observed pre-pandemic. Social inequalities (e.g., by deprivation, ethnicity and geography) narrowed during the pandemic, although geographical inequalities widened from 2022 onwards. - People who experienced disrupted access to healthcare during the pandemic were more likely to have been hospitalised for a preventable or avoidable condition. Disrupted access to procedures (e.g. surgery, treatment) had the largest effect, and disrupted access to appointments (e.g., GPs) also were important. |
Exploitation Route | The results demonstrate the need to focus on dealing with the backlog of admissions caused by disrupted access to healthcare during the pandemic. Tackling increased needs for healthcare, through building capacity and increasing service provision, will help. Remote consultations for GPs are popular and should feature as part of a GPs offer to help see more people (as well as allowing face-to-face visits). |
Sectors | Digital/Communication/Information Technologies (including Software) Healthcare Government Democracy and Justice |
Description | Invited presentation at Royal Geographical Society Annual Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited presentation to session about social inequalities in COVID-19 outcomes. Presented preliminary findings about fellowship project. Gained helpful feedback and established new networks. |
Year(s) Of Engagement Activity | 2022 |