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Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort

STUDY DESIGN: Retrospective, non-randomised, registry controlled. OBJECTIVE: To develop a conceptual ICD-10 taxonomic framework for population health surveillance across all-phases of spinal cord injury and disorders (SCI/D). SETTING: Public Hospital Admitted Patient Care (APC) collection, South Aus...

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Autores principales: Clark, Jillian M., Marshall, Ruth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395265/
https://www.ncbi.nlm.nih.gov/pubmed/35210556
http://dx.doi.org/10.1038/s41393-022-00761-6
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author Clark, Jillian M.
Marshall, Ruth
author_facet Clark, Jillian M.
Marshall, Ruth
author_sort Clark, Jillian M.
collection PubMed
description STUDY DESIGN: Retrospective, non-randomised, registry controlled. OBJECTIVE: To develop a conceptual ICD-10 taxonomic framework for population health surveillance across all-phases of spinal cord injury and disorders (SCI/D). SETTING: Public Hospital Admitted Patient Care (APC) collection, South Australian Dept. Health, South Australia, Australia. METHODS: A core ICD-10-Australian Modification (AM) coded dataset was retrieved from the APC hospital patient admission collection (2012–2017). Search filters and key words referenced to the National Library of Medicine thesaurus identified and quantified incident SCI/D cases. Incident SCI/D case data held in the Australian Spinal Cord Injury Registry (ASCIR) of South Australia (2012–2017) tested fidelity. Data linkage to the South Australian Death Registry controlled for cohort attrition. Both unadjusted and case-mix adjusted core data set yields were evaluated. Outcomes were assessed in terms of APC frequency difference (Δ%) versus ASCIR. RESULTS: 3,504 APC cases were extracted, of which 504 (mean, SD age 55 ± 20 yrs; 348 [69%] male, 202 [39%] traumatic; 135 [32%]) cervical; 51 [10.1%] thoracic and (16 [3.2%]) lumbar met criteria. Comparator data were 385 ASCIR new index cases mean, SD age 56 ± 19 yrs, 229 [75%] male, 162 [42%] traumatic. Case-mix adjusted analysis yielded 336 (APC Δ33%) all-cause incident cases (vs. ASCIR −13 Δ%) and 131 incident cases of traumatic aetiologies (vs. ASCIR −19 Δ%). CONCLUSIONS: The ICD-10 core “Health Condition” data-set assembled extends our understanding of SCI/D epidemiology and with further development may create a cost-efficient and sustainable framework that will improve health system performance and equity within and between countries. SPONSORSHIP: The Lifetime Support Authority of South Australia sponsored the study.
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spelling pubmed-93952652022-08-24 Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort Clark, Jillian M. Marshall, Ruth Spinal Cord Article STUDY DESIGN: Retrospective, non-randomised, registry controlled. OBJECTIVE: To develop a conceptual ICD-10 taxonomic framework for population health surveillance across all-phases of spinal cord injury and disorders (SCI/D). SETTING: Public Hospital Admitted Patient Care (APC) collection, South Australian Dept. Health, South Australia, Australia. METHODS: A core ICD-10-Australian Modification (AM) coded dataset was retrieved from the APC hospital patient admission collection (2012–2017). Search filters and key words referenced to the National Library of Medicine thesaurus identified and quantified incident SCI/D cases. Incident SCI/D case data held in the Australian Spinal Cord Injury Registry (ASCIR) of South Australia (2012–2017) tested fidelity. Data linkage to the South Australian Death Registry controlled for cohort attrition. Both unadjusted and case-mix adjusted core data set yields were evaluated. Outcomes were assessed in terms of APC frequency difference (Δ%) versus ASCIR. RESULTS: 3,504 APC cases were extracted, of which 504 (mean, SD age 55 ± 20 yrs; 348 [69%] male, 202 [39%] traumatic; 135 [32%]) cervical; 51 [10.1%] thoracic and (16 [3.2%]) lumbar met criteria. Comparator data were 385 ASCIR new index cases mean, SD age 56 ± 19 yrs, 229 [75%] male, 162 [42%] traumatic. Case-mix adjusted analysis yielded 336 (APC Δ33%) all-cause incident cases (vs. ASCIR −13 Δ%) and 131 incident cases of traumatic aetiologies (vs. ASCIR −19 Δ%). CONCLUSIONS: The ICD-10 core “Health Condition” data-set assembled extends our understanding of SCI/D epidemiology and with further development may create a cost-efficient and sustainable framework that will improve health system performance and equity within and between countries. SPONSORSHIP: The Lifetime Support Authority of South Australia sponsored the study. Nature Publishing Group UK 2022-02-24 2022 /pmc/articles/PMC9395265/ /pubmed/35210556 http://dx.doi.org/10.1038/s41393-022-00761-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Clark, Jillian M.
Marshall, Ruth
Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort
title Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort
title_full Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort
title_fullStr Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort
title_full_unstemmed Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort
title_short Utilising International Statistical Classification of Diseases and Related Health Conditions (ICD)-10 Australian Modification Classifications of “Health Conditions” to Achieve Population Health Surveillance in an Australian Spinal Cord Injury Cohort
title_sort utilising international statistical classification of diseases and related health conditions (icd)-10 australian modification classifications of “health conditions” to achieve population health surveillance in an australian spinal cord injury cohort
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395265/
https://www.ncbi.nlm.nih.gov/pubmed/35210556
http://dx.doi.org/10.1038/s41393-022-00761-6
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