Prevalence of amputations amongst people with type 2 diabetes enrolled in primary care in England

Abstract

Abstract Background Different patterns of co-morbidities observed among people with type 2 diabetes (T2D) and lower extremity amputations (LEA) compared with those without may provide insights into the quality of care provided by general practitioners in England. We analysed routinely recorded clinical data to build predictive models for benchmarking and continuous improvement. Methods A cross-sectional computerized data extraction of clinical records from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database of people with T2D in England. Key target cases were defined as adults with T2D and a record of major/minor LEA between 2008-2019 vs all subjects with T2D without amputation. Quality of care was assessed in terms of percentage of patients treated with optimal medical therapy and diagnostic procedures and referred to specialized care according to their clinical profile. The association between quality of care and outcomes was explored using a logistic regression model, adjusting for case-mix. Results During the last decade, in a sample covering approximately 7.4% of all general practitioners in England, a total of 1,052 subjects out of 127,100 adults with T2D had a LEA (832 per 100,000). The median time since amputation was 3.4 years. Only 410 (38%) patients had a recorded DFU diagnosis prior to the amputation, with a median of 2 years from diagnosis to amputation. Major LEA was recorded in 280 (27%) cases. People with a record of retinopathy, peripheral arterial disease, renal disease, neuropathy and DFU had a higher risk of amputations. Quality of care was heterogeneous between patients with and without LEA. Conclusions People with T2D and LEA have a distinct pattern of co-morbidities some of which may be sensitive to improved primary care management, and differential quality of care. Models built using this national database can routinely monitor amputations in England. Variation in treatment should be properly investigated. Key messages The automated extraction of clinical cases from a national database may help shed light on clinical patterns among people with diabetes at high risk of amputations, based on evidence-based criteria. Variation in treatment and quality of care among amputated vs non-amputated subjects can be rapidly explored using a cross-sectional analysis of current records.