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Utilising multiple discharge coding will improve identification of patients with giant cell arteritis: a
Andrew Dermawan1, Julia Murdoch2, Jean Louis De Sousa3
1Department of General Medicine, Royal Perth Hospital, Perth, Australia. andrew.dermawan@health.wa.gov.au.
Insights
Discharge diagnosis codes for Giant Cell Arteritis (GCA) in hospitals are not always accurate. Only two-thirds of patients with a GCA code were confirmed to have the condition, impacting research data quality.
Area of Science:
- Rheumatology
- Medical Informatics
Background:
- Giant Cell Arteritis (GCA) is a systemic vasculitis affecting large arteries.
- Accurate diagnostic coding is crucial for epidemiological and clinical research.
Purpose of the Study:
- To assess the accuracy of International Classification of Diseases (ICD) codes for GCA in tertiary hospital discharge data.
- To determine if multiple coded GCA episodes improve diagnostic specificity.
Main Methods:
- Retrospective review of 157 hospital admissions with GCA ICD codes (M31.5, M31.6) in Perth, Western Australia.
- Expert opinion and 2022 ACR/EULAR criteria used to confirm GCA diagnosis at 6-month follow-up.
- Analysis of ICD code specificity based on the number of GCA-coded discharges per patient.
Main Results:
- 65.6% of patients initially coded for GCA had confirmed GCA by expert opinion at 6 months.
- 88.2% met the 2022 ACR/EULAR GCA diagnostic criteria.
- ICD code specificity increased with multiple coded episodes: 67.4% (1 episode), 80% (2 episodes), 100% (3+ episodes).
- Significant proportion of patients without GCA retained the diagnosis in records; few had alternative diagnoses documented.
Conclusions:
- Discharge diagnosis coding for GCA shows poor correlation with confirmed diagnoses, potentially compromising health administrative data quality.
- Using multiple GCA-coded episodes may enhance cohort homogeneity for research, but further studies are needed.
Abstract:
To determine whether the discharge diagnosis codes used within tertiary hospitals accurately identified patients with Giant Cell Arteritis (GCA), as determined by expert opinion at 6 months. The study was performed across three major hospitals within Perth, Western Australia. Patients with an International Classification of Diseases (ICD) code for GCA (M31.5 and M31.6) at discharge on first inpatient presentation were identified. Review of case notes, discharge summaries, letters, pathology, and imaging results were undertaken. The percentage of patients with an ICD code for GCA at initial discharge with confirmed GCA by expert opinion at 6 months (as the anchor diagnosis) was calculated. As validation of the anchor diagnosis, the percentage who fulfilled the 2022 ACR/EULAR criteria was also calculated, the number of hospital discharges per patient with an ICD code for GCA was calculated, to determine if multiple discharges with an ICD code for GCA increased the specificity of the ICD coding. 93 out of 157 admissions with an ICD for GCA were identified as a first inpatient presentation. At 6 months follow up, 65.6%, 95 CI [55.0%, 75.1%] had confirmed GCA by expert opinion. 88.2%, 95 CI [79.8%, 93.9%] met the 2022 ACR/EULAR criteria for GCA. The specificity of the ICD coding increased with increasing number of discharges- 67.4% with single episode, 80% with two episodes, and 100% with three or more episodes (p = 0.1373). Only 43.8%, 95 CI [26.4%, 62.3%] of patients who did not have GCA had an alternative diagnosis provided. 31.3%, 95 CI [16.1%, 50.0%] of patients who did not have GCA still have the GCA diagnosis listed in their subsequent clinical records and discharge summaries. Only 2/3rds of those patients with an initial discharge ICD code for GCA were found to have confirmed GCA at follow-up. This poor correlation between the ICD coding and confirmed diagnosis of GCA will impact the quality of data extracted from administrative health datasets for epidemiological and longitudinal studies. Selecting patients with two or more GCA coded episodes could improve the homogeneity of the cohort for recruitment into GCA studies, but a larger sample size study is required.
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