Linking administrative data sets of inpatient infectious diseases diagnoses in far North Queensland: a cohort profile.

PURPOSE: To design a linked hospital database using administrative and clinical information to describe associations that predict infectious diseases outcomes, including long-term mortality. PARTICIPANTS: A retrospective cohort of Townsville Hospital inpatients discharged with an International Classification of Diseases and Related Health Problems 10th Revision Australian Modification code for an infectious disease between 1 January 2006 and 31 December 2016 was assembled. This used linked anonymised data from: hospital administrative sources, diagnostic pathology, pharmacy dispensing, public health and the National Death Registry. A Created Study ID was used as the central identifier to provide associations between the cohort patients and the subsets of granular data which were processed into a relational database. A web-based interface was constructed to allow data extraction and evaluation to be performed using editable Structured Query Language. FINDINGS TO DATE: The database has linked information on 41 367 patients with 378 487 admissions and 1 869 239 diagnostic/procedure codes. Scripts used to create the database contents generated over 24 000 000 database rows from the supplied data. Nearly 15% of the cohort was identified as Aboriginal or Torres Strait Islanders. Invasive staphylococcal, pneumococcal and Group A streptococcal infections and influenza were common in this cohort. The most common comorbidities were smoking (43.95%), diabetes (24.73%), chronic renal disease (17.93%), cancer (16.45%) and chronic pulmonary disease (12.42%). Mortality over the 11-year period was 20%. FUTURE PLANS: This complex relational database reutilising hospital information describes a cohort from a single tropical Australian hospital of inpatients with infectious diseases. In future analyses, we plan to explore analyses of risks, clinical outcomes, healthcare costs and antimicrobial side effects in site and organism specific infections.