OBJECTIVE: To determine the association between the frequencies of pharmaceutical exposures reported to a poison control center (PCC) and those seen in the emergency department (ED). DESIGN: A statewide population-based retrospective comparison of frequencies of ED pharmaceutical poisonings with frequencies of pharmaceutical exposures reported to a regional PCC. ED poisonings, identified by International Classification of Diseases, Version 9 (ICD-9) codes, were grouped into substance categories. Using a reproducible algorithm facilitated by probabilistic linkage, codes from the PCC classification system were mapped into the same categories. A readily identifiable subset of PCC calls was selected for comparison. MEASUREMENTS: Correlations between frequencies of quarterly exposures by substance categories were calculated using Pearson correlation coefficients and partial correlation coefficients with adjustment for seasonality. RESULTS: PCC reported exposures correlated with ED poisonings in nine of 10 categories. Partial correlation coefficients (r(p)) indicated strong associations (r(p)>0.8) for three substance categories that underwent large changes in their incidences (opiates, benzodiazepines, and muscle relaxants). Six substance categories were moderately correlated (r(p)>0.6). One category, salicylates, showed no association. Limitations Imperfect overlap between ICD-9 and PCC codes may have led to miscategorization. Substances without changes in exposure frequency have inadequate variability to detect association using this method. CONCLUSION: PCC data are able to effectively identify trends in poisonings seen in EDs and may be useful as part of a pharmaceutical poisoning surveillance system. The authors developed an algorithm-driven technique for mapping American Association of Poison Control Centers codes to ICD-9 codes and identified a useful subset of poison control exposures for analysis.
OBJECTIVE: To determine the association between the frequencies of pharmaceutical exposures reported to a poison control center (PCC) and those seen in the emergency department (ED). DESIGN: A statewide population-based retrospective comparison of frequencies of ED pharmaceutical poisonings with frequencies of pharmaceutical exposures reported to a regional PCC. ED poisonings, identified by International Classification of Diseases, Version 9 (ICD-9) codes, were grouped into substance categories. Using a reproducible algorithm facilitated by probabilistic linkage, codes from the PCC classification system were mapped into the same categories. A readily identifiable subset of PCC calls was selected for comparison. MEASUREMENTS: Correlations between frequencies of quarterly exposures by substance categories were calculated using Pearson correlation coefficients and partial correlation coefficients with adjustment for seasonality. RESULTS: PCC reported exposures correlated with ED poisonings in nine of 10 categories. Partial correlation coefficients (r(p)) indicated strong associations (r(p)>0.8) for three substance categories that underwent large changes in their incidences (opiates, benzodiazepines, and muscle relaxants). Six substance categories were moderately correlated (r(p)>0.6). One category, salicylates, showed no association. Limitations Imperfect overlap between ICD-9 and PCC codes may have led to miscategorization. Substances without changes in exposure frequency have inadequate variability to detect association using this method. CONCLUSION: PCC data are able to effectively identify trends in poisonings seen in EDs and may be useful as part of a pharmaceutical poisoning surveillance system. The authors developed an algorithm-driven technique for mapping American Association of Poison Control Centers codes to ICD-9 codes and identified a useful subset of poison control exposures for analysis.
Authors: William A Watson; Toby L Litovitz; Martin G Belson; Amy B Funk Wolkin; Manish Patel; Joshua G Schier; Nicole E Reid; Edwin Kilbourne; Carol Rubin Journal: Toxicol Appl Pharmacol Date: 2005-09-01 Impact factor: 4.219
Authors: Lawrence J Cook; Stacey Knight; Edward P Junkins; N Clay Mann; J Michael Dean; Lenora M Olson Journal: Acad Emerg Med Date: 2004-03 Impact factor: 3.451