Citation

Patrick AR, Miller M, Barber CW, Wang PS, Canning CF, Schneeweiss S. Pharmacoepidemiol. Drug Saf. 2010; 19(12): 1263-1275.

Affiliation

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Copyright

(Copyright © 2010, John Wiley and Sons)

DOI

10.1002/pds.2037

PMID

20922709

PMCID

PMC2992076

Abstract

CONTEXT: Suicidal behavior has gained attention as an adverse outcome of prescription drug use. Hospitalizations for intentional self-harm, including suicide, can be identified in administrative claims databases using external cause of injury codes (E-codes). However, rates of E-code completeness in US government and commercial claims databases are low due to issues with hospital billing software. OBJECTIVE: To develop an algorithm to identify intentional self-harm hospitalizations using recorded injury and psychiatric diagnosis codes in the absence of E-code reporting. METHODS: We sampled hospitalizations with an injury diagnosis (ICD-9 800-995) from two databases with high rates of E-coding completeness: 1999-2001 British Columbia, Canada data and the 2004 US Nationwide Inpatient Sample. Our gold standard for intentional self-harm was a diagnosis of E950-E958. We constructed algorithms to identify these hospitalizations using information on type of injury and presence of specific psychiatric diagnoses. RESULTS: The algorithm that identified intentional self-harm hospitalizations with high sensitivity and specificity was a diagnosis of poisoning, toxic effects, open wound to elbow, wrist, or forearm, or asphyxiation; plus a diagnosis of depression, mania, personality disorder, psychotic disorder, or adjustment reaction. This had a sensitivity of 63%, specificity of 99% and positive predictive value (PPV) of 86% in the Canadian database. Values in the US data were 74, 98, and 73%. PPV was highest (80%) in patients under 25 and lowest those over 65 (44%). CONCLUSIONS : The proposed algorithm may be useful for researchers attempting to study intentional self-harm in claims databases with incomplete E-code reporting, especially among younger populations. Copyright © 2010 John Wiley & Sons, Ltd.

Language: en