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# LLC_0009
Understanding the association between self-reported healthcare disruption due to COVID-19 and avoidable hospitalisation
# LLC_0009: Understanding the association between self-reported healthcare disruption due to COVID-19 and avoidable hospitalisation

We will study the impacts of health care disruption (e.g., delays and confusion over service delivery) in the UK. We will examine the experiences of those individuals affected by this disruption, including whether it has affected their health. We will share the findings with policy makers, NHS care managers, and politicians to help inform:
**Team:** Mark A. Green, Martin McKee, Olivia Hamilton, Richard J. Shaw, John Macleod, Andy Boyd, and Srinivasa Vittal Katikireddi.
On behalf of the LH&W NCS Collaborative

Which services to invest in or act on first,
Which types of people need additional help.
Our study will help benefit patients and lessen the effects of the problem.
Preprint: Coming soon

Having access to the linked data is necessary to understand the experiences of patients. We do not know exactly how people used healthcare services during the pandemic in the surveys. While people in the surveys are asked if they experienced some disruption, how this relates to their actual use of healthcare is unclear. The linked data will allow us to examine the types of healthcare people used, their experiences, and any health conditions diagnosed during the pandemic. Only through having access to all of this information can we begin to track how healthcare disruption impacts health. This is not currently possible through other data sources. We are not aware of another study doing this research.
**Lay summary**
We will study the impacts of health care disruption (e.g., delays and confusion over service delivery) in the UK. We will examine the experiences of those individuals affected by this disruption, including whether it has affected their health. We will share the findings with policy makers, NHS care managers, and politicians to help inform which services to invest in or act on first, and which types of people need additional help. Our study will help benefit patients and lessen the effects of the problem. Having access to the linked data is necessary to understand the experiences of patients. We do not know exactly how people used healthcare services during the pandemic in the surveys. While people in the surveys are asked if they experienced some disruption, how this relates to their actual use of healthcare is unclear. The linked data will allow us to examine the types of healthcare people used, their experiences, and any health conditions diagnosed during the pandemic. Only through having access to all of this information can we begin to track how healthcare disruption impacts health. This is not currently possible through other data sources. We are not aware of another study doing this research.

**Scientific Abstract**
**Background:** Health services across the UK struggled to cope during the COVID-19 pandemic. Many treatments were postponed or cancelled, although the impact was mitigated by new models of delivery. While the scale of disruption has been studied, much less is known about if this disruption impacted health outcomes. The aim of our paper is to examine whether there is an association between individuals experiencing disrupted access to healthcare during the pandemic and risk of an avoidable hospitalisation.
**Methods:** We used individual-level data for England from seven longitudinal cohort studies linked to electronic health records from NHS Digital (n = 29 276) within the UK Longitudinal Linkage Collaboration trusted research environment. Avoidable hospitalisations were defined as emergency hospital admissions for ambulatory care sensitive and emergency urgent care sensitive conditions (1st March 2020 to 25th August 2022). Self-reported measures of whether people had experienced disruption during the pandemic to appointments (e.g., visiting their GP or an outpatient department), procedures (e.g., surgery, cancer treatment) or medications were used as our exposures. Logistic regression models examined associations.
**Results:** 35% of people experienced some form of disrupted access to healthcare. Those whose access was disrupted were at increased risk of any (Odds Ratio (OR) = 1.80, 95% Confidence Intervals (CIs) = 1.34-2.41), acute (OR = 1.68, CIs = 1.13-2.53) and chronic (OR = 1.93, CIs = 1.40-2.64) ambulatory care sensitive hospital admissions. There were positive associations between disrupted access to appointments and procedures to measures of avoidable hospitalisations as well.
**Conclusions:** Our study presents novel evidence from linked individual-level data showing that people whose access to healthcare was disrupted were more likely to have an avoidable or potentially preventable hospitalisation. Our findings highlight the need to increase healthcare investment to tackle the short- and long-term implications of the pandemic beyond directly dealing with SARS-CoV-2 infections.

**Keywords:** COVID-19; avoidable hospitalisations; linked data; cohort; healthcare; disruption; UK LLC.