Inaccurate Ascertainment of Morbidity and Mortality due to Influenza in Administrative Databases: A Population-Based Record Linkage Study

Abstract

BackgroundHistorically, counting influenza recorded in administrative health outcome databases has been considered insufficient to estimate influenza attributable morbidity and mortality in populations. We used database record linkage to evaluate whether modern databases have similar limitations.MethodsPerson-level records were linked across databases of laboratory notified influenza, emergency department (ED) presentations, hospital admissions and death registrations, from the population (∼6.9 million) of New South Wales (NSW), Australia, 2005 to 2008.ResultsThere were 2568 virologically diagnosed influenza infections notified. Among those, 25% of 40 who died, 49% of 1451 with a hospital admission and 7% of 1742 with an ED presentation had influenza recorded on the respective database record. Compared with persons aged ≥65 years and residents of regional and remote areas, respectively, children and residents of major cities were more likely to have influenza coded on their admission record. Compared with older persons and admitted patients, respectively, working age persons and non-admitted persons were more likely to have influenza coded on their ED record. On both ED and admission records, persons with influenza type A infection were more likely than those with type B infection to have influenza coded. Among death registrations, hospital admissions and ED presentations with influenza recorded as a cause of illness, 15%, 28% and 1.4%, respectively, also had laboratory notified influenza. Time trends in counts of influenza recorded on the ED, admission and death databases reflected the trend in counts of virologically diagnosed influenza.ConclusionsA minority of the death, hospital admission and ED records for persons with a virologically diagnosed influenza infection identified influenza as a cause of illness. Few database records with influenza recorded as a cause had laboratory confirmation. The databases have limited value for estimating incidence of influenza outcomes, but can be used for monitoring variation in incidence over time.

Epidemiology of influenza B in Australia: 2001‐2014 influenza seasons

“…Our study included data only from notified cases, and thus, laboratory‐confirmed influenza notifications may underestimate the true incidence of influenza infections in the population 12. Only a small proportion of persons infected with influenza will seek medical attention and therefore have the opportunity to be tested.…”

“…Like influenza A, influenza B has caused localised outbreaks, including in mass gatherings 2, 8, 9, 10, 11. Moreover, influenza B infection may be underidentified compared with influenza A in healthcare settings,12 so the true burden of influenza B may be underestimated.…”

Human temperatures for syndromic surveillance in the emergency department: data from the autumn wave of the 2009 swine flu (H1N1) pandemic and a seasonal influenza outbreak

“…Because the ED has the potential to both detect and warn the community about possible outbreaks or hazards, studies of the ED have multiplied as local syndromic surveillance has become technologically achievable. For example, Hiller et al [1] noted 24 individual systems of ED-based syndromic surveillance of influenza in a 2013 review, and additional studies have been published since [2,3].…”

Flucast: a real-time tool to predict severity of an influenza season (Preprint)

“…The severity indexes and predicted seasonal activities by the models are described in Table 3. In validating the impact of actual seasons with predicted estimates, the reported data may be underestimated [27]; however, these data at least showed a seasonal trend for the years studied. Using the Flucast tool as a real-time assessment in 2017 by early June, the tool predicted the season as severe (severity index score of 60%).…”