Spatio-temporal analysis of non-attendance for the National Abdominal Aortic Aneurysm Screening Program in Cambridgeshire, Peterborough and West Suffolk region between 2018 and 2022 and its link to socioeconomic deprivation

Abstract

Objective: Non-attendance for National Abdominal Aortic Aneurysm Screening Program (NAAASP) screening scans results in a lost opportunity to improve public health and has financial implications for the healthcare system as a whole. This study aimed to assess the spatio-temporal distribution of the ‘did-not-attend’ (DNA) rate and identify high-risk geographical areas and associated risk factors for future policy making and allocation of healthcare resources. Methods: This was a retrospective spatio-temporal analysis of non-attendance to the NAAASP in Cambridgeshire, Peterborough and West Suffolk from 2018 to 2022. With the data from the national AAA screening system, Screening Management and Referral Tracking (SMaRT), the DNA rate was established for each postcode district and compared with the overall DNA rate. Using the number of ‘non-attenders’ in each postcode district, optimised hotspot analysis was performed to identify hotspots of non-attendance for each year between 2018 and 2022. Multiple logistic regression was used to investigate the association between degree of deprivation and non-attendance. Results: Overall, 6,364 of 23,957 people (26.6%) being called for screening did not attend from 2018 to 2022. Optimised hotspot analysis identified eight statistically significant hotspots of non-attendance. Postcode districts PE10 (n=8, 80%), PE1 (n=433, 44.5%), CB4 (n=331, 40.2%), CB3 (n=114, 36.7%) and CB1 (n=320, 35.8%) were identified as areas with statistically significantly higher DNA rates. PE1, CB1, CB3 and CB4 were high-risk areas with both high DNA rates and high numbers of non-attenders. A consistent spatial pattern of hotspots was observed while there was a significant drop in the DNA rate in 2020/21. While degree of deprivation was closely linked to non-attendance in Peterborough, the link was less obvious in Cambridge with little socioeconomic deprivation. Conclusion: PE1, CB1, CB3 and CB4 were identified as high-risk postcodes. These areas comprise 12.6% of the total screened population. The degree of deprivation is found to be a major contributing factor to non-attendance. Focusing resources to try and improve attendance in these cohorts should be a more cost-effective approach than targeting the population as a whole. Future research is needed to explore the risk factors associated with high non-attendance in these postcode districts in order to identify actions to improve uptake and access to the screening services.