"Inaccuracy' in death certification--where are we now?

J Public Health Med. 1996 Mar;18(1):59-66. doi: 10.1093/oxfordjournals.pubmed.a024463.

Abstract

Background: This review aims to document and analyse aspects of death certification that are relevant to public health.

Methods: A literature review on death certification primarily used the computerized Index Medicus (1981 to mid-1995), and concentrated on completing death certificates, accuracy, standards, education and procedural requirements. Further sentinel publications pre-dating this were identified from the main literature base.

Results: The uses of mortality data, historical and procedural context for recording death, the philosophy of Underlying Cause of Death and its relationship to the truth, the extent and impact of "inaccuracy', the certificate and the certifier, and possible ways forward are discussed. It is argued that the question "How inaccurate are cause of death data?' is harder to answer than the literature suggests. Deriving a useful estimate is difficult because of inter-study differences in (1) definition, measurement (how and by whom?) and practical importance of error, and standards used; (2) focus (e.g. death certificate or mortality data), observing everyday practice or simulation exercises, diagnostic and/or semantic issues.

Conclusion: The traditional perspective on improving the quality of death certification has not worked. There is a need for reorientated thinking rather than just urging more education. Evidence-based educational interventions are needed. The flaws in the theoretical framework of cause of death and the routine nature of death certification are unavoidable, but require consideration. Certifiers need practical feedback mechanisms, integral to continuing quality assurance at all levels and fostering an understanding of the construction of mortality data. Continued development should be a core public health medicine role.

Publication types

  • Review

MeSH terms

  • Cause of Death*
  • Death Certificates*
  • Humans
  • Quality Control
  • Semantics