Factors Associated with Stroke Coding Quality: A Comparison of Registry and Administrative Data.

Affiliation

Ryan OF(1), Riley M(2), Cadilhac DA(3), Andrew NE(4), Breen S(5), Paice K(6), Shehata S(7), Sundararajan V(8), Lannin NA(9), Kim J(10), Kilkenny MF(11).
Author information:
(1)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia. Electronic address: [Email]
(2)Department of Public Health, School of Psychology and Public Health, College of Science, Health and Engineering, La Trobe University, Bundoora, VIC, Australia. Electronic address: [Email]
(3)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia; Translational Public Health & Evaluation Division, Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia. Electronic address: [Email]
(4)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia; Peninsula Clinical School, Central Clinical School, Monash University, VIC, Australia. Electronic address: [Email]
(5)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia. Electronic address: [Email]
(6)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia. Electronic address: [Email]
(7)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia. Electronic address: [Email]
(8)Department of Public Health, School of Psychology and Public Health, College of Science, Health and Engineering, La Trobe University, Bundoora, VIC, Australia. Electronic address: [Email]
(9)Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia; Alfred Health, Melbourne, VIC, Australia. Electronic address: [Email]
(10)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia; Translational Public Health & Evaluation Division, Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia. Electronic address: [Email]
(11)Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia; Translational Public Health & Evaluation Division, Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia. Electronic address: [Email]

Abstract

BACKGROUND: The International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Australian Modification (ICD-10-AM) codes are commonly used to identify patients with diseases or clinical conditions for epidemiological research. We aimed to determine the diagnostic agreement and factors associated with a clinician-assigned stroke diagnosis in a national registry and the ICD-10-AM codes recorded in government-held administrative data. MATERIALS AND METHODS: Data from 39 hospitals (2009-2013) participating in the Australian Stroke Clinical Registry (AuSCR) were linked and merged with person-level administrative data. The AuSCR clinician-assigned stroke diagnosis was the reference standard. Concordance was defined as agreement between the clinician-assigned diagnosis and the ICD-10-AM codes for acute stroke or transient ischemic attack (TIA) (ICD-10-AM codes: I61-I64, G45.9). Multivariable logistic regression was undertaken to assess factors associated with coded diagnostic concordance. RESULTS: A total of 14,716 patient admissions were included (46% female, 63% ischemic, 14% intracerebral hemorrhage [ICH], 18% TIA and 5% unspecified stroke based on the reference standard). Principal ICD-10-AM code concordance was ICH: 76.7%; ischemic stroke: 72.2%; TIA: 80.2%; unspecified stroke: 50.8%. Factors associated with a greater odds of ischemic stroke concordance included: treatment in a stroke unit (adjusted Odds Ratio, aOR:1.58; 95% confidence interval (CI) 1.37, 1.82); length of stay >4 days (aOR:1.30; 95% CI 1.17, 1.45); and discharge destination other than home (Residential care aOR:1.57; 95% CI 1.24, 1.96; Inpatient rehabilitation aOR:1.63; 95% CI 1.43, 1.86). CONCLUSIONS: Diagnostic concordance varied based on stroke type. Future research to improve the quality of coding for stroke should focus on patients not treated in stroke units or with shorter lengths of stay where documentation in medical records may be limited.