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Validity of major osteoporotic fracture diagnosis codes in the Clinical Data Analysis and Reporting System in Hong
Chor-Wing Sing1, Yu-Cho Woo2, Alan C H Lee2
1Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong.
Insights
The International Classification of Diseases, 9th Revision (ICD-9) code algorithm accurately identifies major osteoporotic fractures in Hong Kong
Area of Science:
- Epidemiology
- Medical Informatics
- Orthopedics
Background:
- Large medical record databases are crucial for fracture epidemiology research.
- Ensuring data validity is essential for reliable epidemiological studies.
- The Clinical Data Analysis and Reporting System (CDARS) in Hong Kong is a valuable resource for research.
Purpose of the Study:
- To assess the validity of International Classification of Diseases, 9th Revision (ICD-9) code algorithms for identifying major osteoporotic fractures.
- To determine the positive predictive value (PPV) of ICD-9 codes in the CDARS database.
Main Methods:
- Utilized ICD-9 code algorithms to identify major osteoporotic fractures (vertebral, humerus, forearm/wrist, hip) in CDARS (2005-2016).
- Validated fracture diagnostic codes against radiography imaging and clinical notes for a randomly selected sample of 380 cases.
- Calculated the positive predictive value (PPV) to measure diagnostic accuracy.
Main Results:
- The overall positive predictive value (PPV) for major osteoporotic fractures was 96.8%.
- High PPVs of 100% were observed for hip, humerus, and forearm/wrist fractures.
- A PPV of 86% was noted for vertebral fractures, indicating a need for careful interpretation.
Conclusions:
- The ICD-9 code algorithm is a valid and highly accurate tool for identifying major osteoporotic fractures in the CDARS database.
- While generally reliable, cautious interpretation is advised when focusing on incident vertebral fractures.
- This validates the use of CDARS data for large-scale fracture research.
Purpose:
Large medical record databases facilitate epidemiology research in fracture. However, the validity of fracture in the databases is needed to ensure the reliability of data. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD-9) code algorithms for identifying major osteoporotic fracture in the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong.
Methods:
The CDARS is a database developed by the Hong Kong Hospital Authority for research purpose. We used ICD-9 code algorithm for identifying major osteoporotic fracture, including vertebral fracture, humerus fracture, forearm/wrist fracture, and hip fracture, in CDARS in 2005-2016. As high positive predictive value (PPV) is critically important in epidemiology research, we sought to determine the PPV of fracture diagnostic code in terms of ICD-9 relative to the radiography imaging and clinical notes. A total of 380 major osteoporotic fracture cases (vertebral fracture: 101 cases; humerus fracture: 81 cases; forearm/wrist fracture: 94 cases; and hip fracture: 104 cases) were randomly selected and validated.
Results:
In 380 fracture cases, the overall PPV was 96.8%. In subgroup analysis, PPV of 100% was observed for hip, humerus, and forearm/wrist fractures, whereas PPV of 86% was observed for vertebral fracture.
Conclusions:
The use of ICD-9 code algorithm to identify major osteoporotic fracture in CDARS is a valid tool with a very high PPV. However, cautious interpretation is required when the study focuses on incident vertebral fracture. Copyright © 2017 John Wiley & Sons, Ltd.