Case identification of non-traumatic brain injury in youth using linked population data
Abstract Background Population-level administrative data provides a cost-effective means of monitoring health outcomes and service needs of clinical populations. This study aimed to present a method for case identification of non-traumatic brain injury in population-level data and to examine the ass...
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| Format: | Article |
| Language: | English |
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BMC
2024-03-01
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| Series: | BMC Neurology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12883-024-03575-6 |
| _version_ | 1797274242243362816 |
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| author | Rebecca F Slykerman Betony E Clasby Jimmy Chong Kathryn Edward Barry J Milne Helen Temperton Hiran Thabrew Nicholas Bowden |
| author_facet | Rebecca F Slykerman Betony E Clasby Jimmy Chong Kathryn Edward Barry J Milne Helen Temperton Hiran Thabrew Nicholas Bowden |
| author_sort | Rebecca F Slykerman |
| collection | DOAJ |
| description | Abstract Background Population-level administrative data provides a cost-effective means of monitoring health outcomes and service needs of clinical populations. This study aimed to present a method for case identification of non-traumatic brain injury in population-level data and to examine the association with sociodemographic factors. Methods An estimated resident population of youth aged 0–24 years was constructed using population-level datasets within the New Zealand Integrated Data Infrastructure. A clinical consensus committee reviewed the International Classification of Diseases Ninth and Tenth Editions codes and Read codes for inclusion in a case definition. Cases were those with at least one non-traumatic brain injury code present in the five years up until 30 June 2018 in one of four databases in the Integrated Data Infrastructure. Rates of non-traumatic brain injury were examined, both including and excluding birth injury codes and across age, sex, ethnicity, and socioeconomic deprivation groups. Results Of the 1 579 089 youth aged 0–24 years on 30 June 2018, 8154 (0.52%) were identified as having one of the brain injury codes in the five-years to 30 June 2018. Rates of non-traumatic brain injury were higher in males, children aged 0–4 years, Māori and Pacific young people, and youth living with high levels of social deprivation. Conclusion This study presents a comprehensive method for case identification of non-traumatic brain injury using national population-level administrative data. |
| first_indexed | 2024-03-07T14:55:34Z |
| format | Article |
| id | doaj.art-7d777f0aacf3452daee3fb42831421de |
| institution | Directory Open Access Journal |
| issn | 1471-2377 |
| language | English |
| last_indexed | 2024-03-07T14:55:34Z |
| publishDate | 2024-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Neurology |
| spelling | doaj.art-7d777f0aacf3452daee3fb42831421de2024-03-05T19:28:11ZengBMCBMC Neurology1471-23772024-03-0124111010.1186/s12883-024-03575-6Case identification of non-traumatic brain injury in youth using linked population dataRebecca F Slykerman0Betony E Clasby1Jimmy Chong2Kathryn Edward3Barry J Milne4Helen Temperton5Hiran Thabrew6Nicholas Bowden7Department of Psychological Medicine, Te Ara Hāro, University of AucklandDepartment of Women’s and Children’s Health, University of OtagoPaediatric Rehabilitation ServicePaediatric Rehabilitation ServiceCentre of Methods and Policy Application in the Social Sciences, University of AucklandPaediatric Rehabilitation ServiceDepartment of Psychological Medicine, Te Ara Hāro, University of AucklandDepartment of Women’s and Children’s Health, University of OtagoAbstract Background Population-level administrative data provides a cost-effective means of monitoring health outcomes and service needs of clinical populations. This study aimed to present a method for case identification of non-traumatic brain injury in population-level data and to examine the association with sociodemographic factors. Methods An estimated resident population of youth aged 0–24 years was constructed using population-level datasets within the New Zealand Integrated Data Infrastructure. A clinical consensus committee reviewed the International Classification of Diseases Ninth and Tenth Editions codes and Read codes for inclusion in a case definition. Cases were those with at least one non-traumatic brain injury code present in the five years up until 30 June 2018 in one of four databases in the Integrated Data Infrastructure. Rates of non-traumatic brain injury were examined, both including and excluding birth injury codes and across age, sex, ethnicity, and socioeconomic deprivation groups. Results Of the 1 579 089 youth aged 0–24 years on 30 June 2018, 8154 (0.52%) were identified as having one of the brain injury codes in the five-years to 30 June 2018. Rates of non-traumatic brain injury were higher in males, children aged 0–4 years, Māori and Pacific young people, and youth living with high levels of social deprivation. Conclusion This study presents a comprehensive method for case identification of non-traumatic brain injury using national population-level administrative data.https://doi.org/10.1186/s12883-024-03575-6Administrative dataNon-traumatic brain injuryCase identificationIntegrated data infrastructure |
| spellingShingle | Rebecca F Slykerman Betony E Clasby Jimmy Chong Kathryn Edward Barry J Milne Helen Temperton Hiran Thabrew Nicholas Bowden Case identification of non-traumatic brain injury in youth using linked population data BMC Neurology Administrative data Non-traumatic brain injury Case identification Integrated data infrastructure |
| title | Case identification of non-traumatic brain injury in youth using linked population data |
| title_full | Case identification of non-traumatic brain injury in youth using linked population data |
| title_fullStr | Case identification of non-traumatic brain injury in youth using linked population data |
| title_full_unstemmed | Case identification of non-traumatic brain injury in youth using linked population data |
| title_short | Case identification of non-traumatic brain injury in youth using linked population data |
| title_sort | case identification of non traumatic brain injury in youth using linked population data |
| topic | Administrative data Non-traumatic brain injury Case identification Integrated data infrastructure |
| url | https://doi.org/10.1186/s12883-024-03575-6 |
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