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Background  Currently there are only two population studies on sepsis incidence in Asia. The burden of sepsis in Hong Kong is unknown. We developed a sepsis surveillance method to estimate sepsis incidence from a population electronic health record (EHR) in Hong Kong using objective clinical data. The study objective was to assess our method’s performance in identifying sepsis using a retrospective cohort. We compared its accuracy to administrative sepsis surveillance methods such as Angus’ and Martin’s methods.    Method  In this single centre retrospective study we applied our sepsis surveillance method on adult patients admitted to a tertiary hospital in Hong Kong. Two clinicians independently reviewed the clinical notes to determine which patients had sepsis. Performance was assessed by sensitivity, specificity, positive predictive value, negative predictive value and area under the curve (AUC) of Angus’, Martin’s and our surveillance methods using clinical review as “gold standard.”    Results  Between January 1 and February 28, 2018, our sepsis surveillance method identified 1352 adult patients hospitalised with suspected infection. We found that 38.9% (95%CI 36.3–41.5) of these patients had sepsis. Using a 490 patient validation cohort, two clinicians had good agreement with weighted kappa of 0.75 (95% CI 0.69–0.81) before coming to consensus on diagnosis of uncomplicated infection or sepsis for all patients. Our method had sensitivity 0.93 (95%CI 0.89–0.96), specificity 0.86 (95%CI 0.82–0.90) and an AUC 0.90 (95%CI 0.87–0.92) when validated against clinician review. In contrast, Angus’ and Martin’s methods had AUCs 0.56 (95%CI 0.53–0.58) and 0.56 (95%CI 0.52–0.59), respectively.    Conclusions  A sepsis surveillance method based on objective data from a population EHR in Hong Kong was more accurate than administrative methods. It may be used to estimate sepsis population incidence and outcomes in Hong Kong.    Trial registration  This study was retrospectively registered at  clinicaltrials.gov  on October 3, 2019 ( NCT04114214 ).

A surveillance method to identify patients with sepsis from electronic health records in Hong Kong: a single centre retrospective study