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Carbon monoxide-related injury estimation using ICD-coded data: methodologic implications for public health
Lauren B Ball1, Steven C Macdonald, Joshua A Mott
1Indoor Air Solutions, Tallahassee, FL 32303, USA. LBALLIAQ@mindspring.com
Accurately estimating unintentional carbon monoxide (CO) poisoning deaths requires careful analysis of International Classification of Diseases, 9th Revision (ICD-9) codes. Multiple-cause-of-death analysis combined with specific injury codes offers the most reliable method for case ascertainment.
Area of Science:
- Public Health
- Epidemiology
- Medical Informatics
Background:
- National mortality data is used to estimate unintentional deaths from carbon monoxide (CO) poisoning.
- Accurate estimation of CO-related fatalities from International Classification of Diseases, 9th Revision (ICD-9) coded data presents challenges.
Purpose of the Study:
- To explore accurate methods for estimating CO-related deaths using ICD-9 coded U.S. mortality data.
- To evaluate different case ascertainment criteria and coding analyses for CO poisoning deaths.
Main Methods:
- Identified and classified CO-related ICD-9 codes into five certainty levels.
- Conducted single and multiple-cause-of-death analyses on 20 years of mortality data (1979-1998).
- Calculated sensitivity and positive predictive values for various case ascertainment criteria.
Main Results:
- Single-cause analysis using CO-exclusive E-codes was accurate but missed about one-third of CO deaths.
- Single-cause analysis with non-exclusive E-codes overestimated CO-related fatalities.
- Multiple-cause-of-death analysis, using the N986 nature-of-injury code, achieved 99.5% sensitivity for identifying true CO deaths.
Conclusions:
- Estimating CO deaths from ICD-coded data necessitates a deep understanding of coding rules and limitations.
- Multiple-cause-of-death analysis and specific injury codes (like N986) are crucial for accurate CO poisoning death ascertainment.
- Single-cause analysis alone is insufficient for comprehensive CO-related mortality estimation.
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