Assessing the accuracy of opioid overdose and poisoning codes in diagnostic information from electronic health records, claims data, and death records
| Autor: | Howard D. Chilcoat, Carla A. Green, Cynthia I. Campbell, Shannon L. Janoff, Paul Coplan, Nancy Perrin |
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| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Epidemiology business.industry Medical record 010102 general mathematics Poison control Opioid overdose Pharmacoepidemiology medicine.disease 01 natural sciences 03 medical and health sciences 0302 clinical medicine Opioid Injury prevention Emergency medicine Medicine Pharmacology (medical) 030212 general & internal medicine Diagnosis code Medical emergency 0101 mathematics business Adverse effect medicine.drug |
| Zdroj: | Pharmacoepidemiology and Drug Safety. 26:509-517 |
| ISSN: | 1053-8569 |
| Popis: | Purpose The purpose of this study is to assess positive predictive value (PPV), relative to medical chart review, of International Classification of Diseases (ICD)-9/10 diagnostic codes for identifying opioid overdoses and poisonings. Methods Data were obtained from Kaiser Permanente Northwest and Northern California. Diagnostic data from electronic health records, submitted claims, and state death records from Oregon, Washington, and California were linked. Individual opioid-related poisoning codes (e.g., 965.xx and X42), and adverse effects of opioids codes (e.g., E935.xx) combined with diagnoses possibly indicative of overdoses (e.g., respiratory depression), were evaluated by comparison with chart audits. Results Opioid adverse effects codes had low PPV to detect overdoses (13.4%) as assessed in 127 charts and were not pursued. Instead, opioid poisoning codes were assessed in 2100 individuals who had those codes present in electronic health records in the period between the years 2008 and 2012. Of these, 10/2100 had no available information and 241/2100 were excluded potentially as anesthesia-related. Among the 1849 remaining individuals with opioid poisoning codes, 1495 events were accurately identified as opioid overdoses; 69 were miscodes or misidentified, and 285 were opioid adverse effects, not overdoses. Thus, PPV was 81%. Opioid adverse effects or overdoses were accurately identified in 1780 of 1849 events (96.3%). Conclusions Opioid poisoning codes have a predictive value of 81% to identify opioid overdoses, suggesting ICD opioid poisoning codes can be used to monitor overdose rates and evaluate interventions to reduce overdose. Further research to assess sensitivity, specificity, and negative predictive value are ongoing. Copyright © 2017 John Wiley & Sons, Ltd. |
| Databáze: | OpenAIRE |
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