Author
Listed:
- Wenjie Wang
(University of Connecticut)
- Chongliang Luo
(Washington University School of Medicine in St. Louis)
- Robert H. Aseltine
(University of Connecticut Health Center
University of Connecticut Health Center)
- Fei Wang
(Cornell University)
- Jun Yan
(University of Connecticut
University of Connecticut Health Center)
- Kun Chen
(University of Connecticut
University of Connecticut Health Center)
Abstract
Motivated by the pressing need for suicide prevention through improving behavioral healthcare, we use medical claims data to study the risk of subsequent suicide attempts (SA) for patients who were hospitalized due to suicide attempts and later discharged. Understanding the risk behaviors of such patients at elevated suicide risk is an important step towards the goal of “Zero Suicide”. An immediate and unconventional challenge is that the identification of SA from medical claims contains substantial uncertainty: almost 20% of “suspected” SA are identified from diagnosis codes indicating external causes of injury and poisoning with undermined intent. It is thus of great interest to learn which of these undetermined events are more likely actual SA and how to properly utilize them in survival analysis with severe censoring. To tackle these interrelated problems, we develop an integrative Cox cure model with regularization to perform survival regression with uncertain events and a latent cure fraction. We apply the proposed approach to study the risk of subsequent SA after suicide-related hospitalization for the adolescent and young adult population, using medical claims data from Connecticut. The identified risk factors are highly interpretable; more intriguingly, our method distinguishes the risk factors that are most helpful in assessing either susceptibility or timing of subsequent attempts. The predicted statuses of the uncertain attempts are further investigated, leading to several new insights on suicide event identification.
Suggested Citation
Wenjie Wang & Chongliang Luo & Robert H. Aseltine & Fei Wang & Jun Yan & Kun Chen, 2025.
"Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses,"
Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(1), pages 35-61, April.
Handle:
RePEc:spr:stabio:v:17:y:2025:i:1:d:10.1007_s12561-023-09374-w
DOI: 10.1007/s12561-023-09374-w
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stabio:v:17:y:2025:i:1:d:10.1007_s12561-023-09374-w. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.