Use of mixed methods to investigate case definitions to improve the identification of serious injury cases from hospital episode data

Author:

Cryer ColinORCID,Davie GabrielleORCID,Gulliver Pauline,Samaranayaka Ari

Abstract

IntroductionIt has been commonplace internationally, when using hospital data, to use the principal diagnosis to identify injury cases and the first external cause of injury code (E-code) to identify the main cause. Our purpose was to investigate alternative operational definitions of serious non-fatal injury to identify cases of interest for injury surveillance, both overall and for four common causes of injury.MethodsSerious non-fatal injury cases were identified from New Zealand (NZ) hospital discharge data using an alternative definition: that is, case selection using principal and additional diagnoses. Separately, identification of cause used all E-codes on the discharge record. Numbers of cases identified were contrasted with those captured using the usual definition. Views of NZ government stakeholders were sought regarding the acceptability of the additional cases found using these alternative definitions. Views of international experts were also canvassed.ResultsWhen using all diagnoses there was a 7% increase in ‘all injury’ cases identified, a 17% increase in self-harm cases and 8% increase in falls cases. Use of all E-codes resulted in a 4% increase in self-harm cases, 2% increase in assault cases and 1% increase in both falls and motor vehicle traffic crash cases.DiscussionA case definition based solely on principal diagnosis fails to count a material number of serious non-fatal injury cases that are of interest to the injury prevention community. There is a need, therefore, to use an alternative case definition that includes additional diagnoses. Use of multiple E-codes to classify cause of injury should be considered.

Funder

Official Statistics Research, Statistics New Zealand

Publisher

BMJ

Subject

Public Health, Environmental and Occupational Health

Reference22 articles.

1. Hip fracture incidence among the old and very old: a population-based study of 745,435 cases.

2. Trends in incidence of pediatric injury hospitalizations in Pennsylvania;Durbin;Am J Publ Health,2000

3. Harrison JE , Steencamp M . Technical review and documentation of current NHPA injury indicators and data sources. in: Injury Research and Statistics Series Number 14. Adelaide: Australian Institute of Health and Welfare, 2002. Available: https://www.aihw.gov.au/reports/injury/technical-review-documentation-nhpa-indictors/contents/table-of-contents [Accessed 20 Mar 2019].

4. Injury Surveillance Workgroup . Consensus recommendations for using hospital discharge data for injury surveillance. Marietta GA: State and Territorial Injury Prevention Directors Association, 2003. Available: https://c.ymcdn.com/sites/safestates.site-ym.com/resource/resmgr/imported/hdd.pdf [Accessed 20 Mar 2019].

5. Gulliver P , Cryer C , Davie G . Chartbook of the New Zealand Injury Prevention Strategy serious injury outcome indicators. Dunedin, New Zealand: Injury Prevention Research Unit, University of Otago, 2009. Available: http://psm-dm.otago.ac.nz/ipru/ReportsPDFs/OR081.pdf [Accessed 20 Mar 2019].

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