P063 SystmOne clinical reporting to identify high-risk rheumatology patients for shielding

Kirby, David; Nadesalingam, Kavitha

Background/Aims At the start of the COVID-19 pandemic, shielding guidance was issued by Public Health England with a risk stratification guide developed by the BSR to assist with patient identification. At BTHFT we benefited with all GP practices in the region using TPP SystmOne (S1) for medical records. We describe how we used S1 to help identify high risk patients under our care. Methods We did not appreciate the full extent we could use S1 to identify patients in our initial shielding identification process. As such, we reviewed notes of patients on biologic prescriptions and SC MTX from Homecare prescription lists. To capture patients on high dose prednisolone, we identified patients with a recent diagnosis of GCA and patients with recent prescriptions of > 20mg prednisolone through pharmacy records. On recognising the ability of S1 to identify patients that had glucocorticoid exposure through primary care and/or on cDMARDS we used S1 reporting mechanisms to identify these patients. Clinical record sharing enabled BTHFT’s rheumatology department to access S1 for all patients under their care. S1’s clinical reporting function was used to search for patients within at least one of the following cohorts before being combined in a single cohort of ‘at risk’ patients (heart, lung or kidney disease, ≥70 years, diabetes or hypertension [including pulmonary artery hypertension]). Reports were created for patients on any DMARD issued within primary care within the previous 12 weeks. High dose steroid use was more challenging to demonstrate, but a report was devised to include all patients with an issued prescription for prednisolone 5mg tablets within the preceding 8 weeks (for any reason). An additional report was created for patients with a rheumatological diagnosis co-existing with an interstitial lung disease. Using S1's report joining function, the different drugs and ‘at risk’ cohorts were combined to provide an accurate list of patients with features increasing their vulnerability to COVID-19. This list was easily modifiable and searches were re-run to update lists once inclusion on the shielding list was updated. Results Patients meeting the criteria for shielding were then advised in writing including signposting to BTHFT’s rheumatology website and helpline for further information if required. By searching for all prednisolone prescriptions, this would have included patients given prednisolone for other reasons. 5mg tablet strength ensured patients on low dose were excluded, but we recognise some patients were likely over-recruited into this cohort. Conclusion We can update our searching methods to easily include patients on biologics and SC MTX by some additional bulk coding in preparation for future shielding specifications thereby bypassing the need to review individual notes for patients. We were able to achieve an accurate shielding list in a relatively short space of time to reduce patient risk. Disclosure D. Kirby: None. K. Nadesalingam: None.