Accounting for reporting fatigue is required to accurately estimate incidence in voluntary reporting health schemes

J Clin Epidemiol. 2017 Jan:81:77-85. doi: 10.1016/j.jclinepi.2016.09.006. Epub 2016 Sep 17.

Abstract

Objective: Accurate estimation of the true incidence of ill-health is a goal of many surveillance systems. In surveillance schemes including zero reporting to remove ambiguity with nonresponse, reporter fatigue might increase the likelihood of a false zero case report in turn underestimating the true incidence rate and creating a biased downward trend over time.

Study design and setting: Multilevel zero-inflated negative binomial models were fitted to incidence case reports of three surveillance schemes running between 1996 and 2012 in the United Kingdom. Estimates of the true annual incidence rates were produced by weighting the reported number of cases by the predicted excess zero rate in addition to the within-scheme standard adjustment for response rate and the participation rate.

Results: Time since joining the scheme was associated with the odds of excess zero case reports for most schemes, resulting in weaker calendar trends. Estimated incidence rates (95% confidence interval) per 100,000 person years, were approximately doubled to 30 (21-39), 137 (116-157), 33 (27-39), when excess zero-rate adjustment was applied.

Conclusion: If we accept that excess zeros are in reality nonresponse by busy reporters, then usual estimates of incidence are likely to be significantly underestimated and previously thought strong downward trends overestimated.

Keywords: Excess zeros; Incidence estimation; Reporter fatigue; Surveillance; Trends; Voluntary reporting; Work-related ill-health; Zero-inflated negative binomial.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bias
  • Data Interpretation, Statistical*
  • Fatigue
  • Humans
  • Incidence
  • Models, Statistical
  • Occupational Diseases / epidemiology*
  • Population Surveillance
  • Reproducibility of Results
  • United Kingdom / epidemiology