Citation

Brent DA, Hur K, Gibbons RD. JAMA Psychiatry 2019; ePub(ePub): ePub.

Affiliation

Department of Psychiatry, University of Chicago, Chicago, Illinois.

Copyright

(Copyright © 2019, American Medical Association)

DOI

10.1001/jamapsychiatry.2019.2342

PMID

31483456

Abstract

In Reply We would like to thank Pennap and colleagues for their thoughtful letter. We completely agree that the use of diagnostic data are likely to greatly underestimate the prevalence of suicide attempts, and we should have stated that explicitly in our article1 as a possible limitation. To emphasize this point, we cite a recent study of postpartum women that demonstrated that detection of suicidal behavior through natural language processing of clinical notes resulted in an 11-fold greater estimate of suicide attempts than in those based solely on diagnostic data.2 However, as Pennap and colleagues note in their Letter, while this underestimate most assuredly affects an estimate of the risk difference, it may not affect the relative risk of suicide attempts. Therefore, we believe that it is safe to conclude that while the diagnostic data reported in our study1 most likely underestimate the true prevalence of suicide attempts and the risk difference, it is probably a reasonable estimate of the relative risk of suicide attempts in the children of parents who use opioids on a regular basis. We also note that our sample was based on parents and children with private health insurance and the rate is likely to be lower than in a general emergency department sample, which includes patients with public health insurance and no health insurance. For example the background rate of acute liver injury based on International Classification of Diseases, Ninth Revision code 570 was 4 times higher in Medicaid claims data relative to claims based on people with private health insurance (ie, the same MarketScan data used in our article).3 Future work that studies suicidal behavior using medical records may benefit from augmenting estimates of the prevalence of suicidal behavior from diagnostic codes with the use of natural language processing to identify cases of suicidal behavior that are documented in the medical record but are not reflected in the diagnostic code.

Language: en