Data linkage and computerised algorithmic coding to enhance individual clinical care for Aboriginal people living with chronic hepatitis B in the Northern Territory of Australia – Is it feasible?

Background: Chronic hepatitis B (CHB) is endemic in the Aboriginal population of Australia’s Northern Territory (NT). However, many people’s hepatitis B virus (HBV) status remains unknown. Objective: 1. To maximise the utility of existing HBV test and vaccination data in the NT by creating a linked dataset and computerised algorithmic coding. 2. To undertake rigorous quality assurance processes to establish feasibility of using the linked dataset and computerised algorithmic coding for individual care for people living with CHB. Methods: Step 1: We used deterministic data linkage to merge information from three separate patient databases. HBV testing and vaccination data from 2008–2016 was linked and extracted for 19,314 people from 21 remote Aboriginal communities in the Top End of the NT. Step 2: A computerised algorithm was developed to allocate one of ten HBV codes to each individual. Step 3: A quality assurance process was undertaken by a clinician, using standardised processes, manually reviewing all three databases, for a subset of 5,293 Aboriginal people from five communities to check the accuracy of each allocated code. Results: The process of data linking individuals was highly accurate at 99.9%. The quality assurance process detected an overall error rate of 17.7% on the HBV code generated by the computerised algorithm. Errors occurred in source documentation, primarily from the historical upload of paper-based records to electronic health records. An overall HBV prevalence of 2.6% in five communities was found, which included ten cases of CHB who were previously unaware of infection and not engaged in care. Conclusions: Data linkage of individuals was highly accurate. Data quality issues and poor sensitivity in the codes produced by the computerised algorithm were uncovered in the quality assurance process. By systematically, manually reviewing all available data we were able to allocate a HBV status to 91% of the study population.