The COVID-19 pandemic has resulted in significant disruptions across the entire cancer care pathway. Healthcare systems have remobilized services to cope with the rising wave of COVID-19 positive patients, causing an indirect impact on the care of patients with non-COVID-19 chronic conditions. Patients with cancer are vulnerable, not only to the adverse outcomes of COVID-19 infection but also to delays in diagnosis and treatment for cancer resulting in suboptimal care. In this study, we aim to evaluate the impact of the pandemic on health care contact among patients with cancer. We will investigate the changes in primary care and hospital attendances to identify periods of reduced attendance. We will also investigate the impact of missed attendances on mortality. Patients with cancer who have pre-existing conditions may be at greater risk of developing poor outcomes. Our analyses will account for the burden of pre-existing conditions, socioeconomic deprivation, age and ethnicity to identify potential variations in health care attendances and mortality. Results will inform the planning of how routine health and care can be sustained in future pandemics. The study will also shed light on the management of long-term chronic conditions and reveal the unwarranted indirect cost of COVID-19.
This study aims to evaluate the impact of the pandemic on change in health care service provision for patients with cancer. We aim to retrospectively evaluate previous attendances using the interrupted time series study design. A time series is a continuous sequence of observations within a population over a specific time interval. Focusing on patients with newly diagnosed cancer (incident cancers), we will analyze trends in GP and hospital attendances for cancer patients (counts by month and percentage change year-on-year by month). We will perform interrupted time series analysis of primary care and hospital attendances (weekly counts) by cancer type, number and types of comorbidities, index of multiple deprivation and sex. We will estimate the impact of missed attendances on excess mortality using an instrumented difference-in-differences design, using the COVID-19 pandemic as the instrument. To define the level of the instrumental variable, we will select time periods when a marked decrease in attendances is observed. The relationship between weekly attendances and mortality will be estimated using the least-squares method. This study can help establish the scale of the indirect effects of the pandemic to ascertain the long-term effects of reduced contact with health and care systems. By estimating the unintended harm that may have resulted from the pandemic's response on health care seeking behavior and the provision of health care for non-COVID19 conditions, these findings could help alert policymakers on the importance of ensuring that measures put in place to control COVID-19 will not adversely impact the management of cancer.
GP attendances, hospital in-patient admissions; hospital outpatient admissions; mortality all-cause; mortality cause-specific
Alvina Lai - Chief Investigator - University College London ( UCL )
Alvina Lai - Corresponding Applicant - University College London ( UCL )
Arturo Gonzalez-Izquierdo - Collaborator - University College London ( UCL )
Muhammad Qummer ul Arfeen - Collaborator - University College London ( UCL )
Wai Chang - Collaborator - University College London ( UCL )
Yen Yi Tan - Collaborator - University College London ( UCL )
Yulei Fan - Collaborator - University College London ( UCL )
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation