Identification of hospitalizations for intentional self-harm when E-codes are incompletely recorded
Article first published online: 3 OCT 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Volume 19, Issue 12, pages 1263–1275, December 2010
How to Cite
Patrick, A. R., Miller, M., Barber, C. W., Wang, P. S., Canning, C. F. and Schneeweiss, S. (2010), Identification of hospitalizations for intentional self-harm when E-codes are incompletely recorded. Pharmacoepidem. Drug Safe., 19: 1263–1275. doi: 10.1002/pds.2037
- Issue published online: 24 NOV 2010
- Article first published online: 3 OCT 2010
- Manuscript Accepted: 19 JUL 2010
- Manuscript Revised: 26 MAY 2010
- Manuscript Received: 21 OCT 2009
- intentional self-harm;
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.
To develop an algorithm to identify intentional self-harm hospitalizations using recorded injury and psychiatric diagnosis codes in the absence of E-code reporting.
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.
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%).
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.