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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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Detalles Bibliográficos
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
Descripción
Sumario: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.