Consolidated Person Level Health Data Improve Tuberculosis Surveillance and Patient Care

Abstract

Introduction Electronic tuberculosis (TB) register systems influence policy decisions, resource allocation and patient care in many ways, but their limitations have been demonstrated in many high-burden settings like South Africa. While digital health systems in the Western Cape, South Africa have improved over time and benefited from implementation of a unique patient identifier, questions about quality and completeness of register data remain. A Health Information Exchange (HIE), established in 2015, daily integrates routinely-collected person level health data from electronic sources in the Province, including laboratory, dispensing, clinical and encounter data, as well as disease register data for HIV and TB. Objectives and Approach Using TB-related datapoints from various electronic platforms and resources, an algorithm was developed to infer cases, visit and treatment information, comorbidities and mortality - defined as a “cascade”. The cascade is recompiled daily incorporating new information added to the HIE, and presented to health care workers and managers as filterable, downloadable reports on an electronic platform. TB Register and inferred cascade data were compared for 2018. Results There were 40,227 cases in the register after 3,010 duplicate entries were eliminated by consolidating personal identifiers and duplicate entries across facilities into single TB episodes. 13,729 additional cases were identified in the HIE cascade. Of these, 6,984 had evidence of treatment; 4,143 were diagnosed and treated only in hospitals - thus less likely to be recorded in the registers. Updated patient contact details and allocation of a primary care facility based on patient visit history, aided in patient care. Conclusion / Implications Leveraging a consolidated environment for person-level health data can substantially enhance and verify disease registers. Appropriate tools can render these data accessible and actionable to improve patient care, minimise errors and missed opportunities to close treatment gaps, and increase accuracy of surveillance and reporting on a programmatic level.