Introduction In the UK around 9 00 000 people have a diagnosis of COPD. Despite its high prevalence under-diagnosis is common in primary care with an additional 2 million cases suggested. Opportunities for early diagnosis and intervention are frequently missed. The best strategy for targeted case finding is unclear.

Methods The ASSIST study (Rec: 15/5C/598580) used a previously trialled, computerised case-finding algorithm,¹ applied remotely into primary care systems for case finding. It applies weighted risk factors as search terms (e.g., smoking history, history of breathlessness, use of inhalers and antibiotics). To date, eight GP Practices, serving 1 01 754 patients in Hampshire, UK have been screened (figure 1). The algorithm identified 1725 possible undiagnosed patients; 506 were excluded by their GP and study team. The remaining 1216 were invited for an hour long assessment with a specialist respiratory nurse at their surgery, which included medical and smoking history, vital signs and spirometry.

Results To date, response rates are 18% (222). Of respondees, 178 were eligible and attended for screening (Male 55%, mean age 64.1, SD 5.5, age range 48–72). 27% (48) had obstructive spirometry (FEV₁/FVC<0.7) without reversibility. 40% (19) of these had moderate obstruction (FEV₁50%–79% predicted) (mean FEV₁% predicted 88%, SD 15.6). Of those with obstructive lung function, 46% (22) have a MRC score of ≥2% and 8% (4) had exacerbations within the previous year. The mean pack year history was 31.9/34.9 (SD 24/108) for obstructed vs. non-obstructed.

• Download figure
• Open in new tab
• Download powerpoint

Abstract P28 Figure 1

Patient flow through the study.

Conclusion Early Results from the ASSIST study show 27% of primary care patients who were identified as at risk of having COPD by the algorithm and attended for screening were confirmed to have the disease. Many had a significant disease burden with 40% having moderate airflow obstruction and 46% having quality of life impairment. We are continuing to recruit further practices. Subsequent work will examine whether using this algorithm Results in earlier identification of COPD in a cost-effective manner and an improvement in quality of life for patients.

Reference

1. Jordan PPAet al. Targeted case-finding for chronic obstructive pulmonary disease versus routine practice in primary care (TargetCOPD): A cluster-randomised controlled trial2016. http://www.thelancet.com/journals/lanres/article/PIIS2213-2600(16)30149-7/fulltext