“Quantity over quality”
Regardless of those sobering reports,
One can reasonably argue that the periodic performance of a suicide risk assessment may have clinical utility in reminding us of modifiable risk factors such as intoxication, social isolation, and access to lethal means. One can also reasonably argue that these risk assessments may provide useful education to patients and their families on epidemiological risk factors such as gender, age, and marital status. But our pursuit of serial suicide risk assessments throughout the day is encouraging providers to focus on a particular risk factor that changes from moment to moment and has particularly low validity, that being self-reported suicidality.
Reported suicidality is one of the few risk factors that can change from shift to shift. But 80% of people who die by suicide had not previously expressed suicidality, and 98.3% of people who have endorsed suicidality do not die by suicide.14 While the former statistic may improve with increased assessment, the later will likely worsen.
Suicide is not a trivial matter. We admire those that study it and advocate for better interventions. We have compassion for those who have suffered the loss of a loved one to suicide. Our patients have died as a result of the human limitations surrounding suicide prevention. Recognizing the weight of suicide and making an effort to avoid minimizing its immense consequences drive our desire to be honest with ourselves, our patients and their families, and society. That includes the unfortunate truth regarding the current state of the evidence and our ability to enact change.
It is our concern that the rising fascination with repeated suicide risk assessment is misguided in its current form and serves the purpose of appeasing administrators more than reflecting a scientific understanding of the literature. More sadly, we are concerned that this “quantity-over-quality” approach is yet another barrier to practicing what may be one of the few interventions with any hope of meaningfully impacting a patient’s risk of suicide in the clinical setting – spending time connecting with our patients.
Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. Dr. Compton is a member of the psychiatry faculty at University of California, San Diego. His background includes medical education, mental health advocacy, work with underserved populations, and brain cancer research. Dr. Badre and Dr. Compton have no conflicts of interest.
References
1. Joint Economic Committee. (2019). Long Term Trends in Deaths of Despair. SCP Report 4-19.
2. Kroenke K and Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Psychiatr Ann. 2013;32(9):509-15. doi: 10.3928/0048-5713-20020901-06.
3. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Lifetime/Recent.
4. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Since Last Contact.
5. Franklin JC et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017 Feb;143(2):187-232. doi: 10.1037/bul0000084.
6. Beautrais AL. Further suicidal behavior among medically serious suicide attempters. Suicide Life Threat Behav. 2004 Spring;34(1):1-11. doi: 10.1521/suli.34.1.1.27772.
7. Belsher BE. Prediction models for suicide attempts and deaths: A systematic review and simulation. JAMA Psychiatry. 2019 Jun 1;76(6):642-651. doi: 10.1001/jamapsychiatry.2019.0174.
8. Carter G et al. Royal Australian and New Zealand College of Psychiatrists clinical practice guideline for the management of deliberate self-harm. Aust N Z J Psychiatry. 2016 Oct;50(10):939-1000. doi: 10.1177/0004867416661039.
9. Fosse R et al. Predictors of suicide in the patient population admitted to a locked-door psychiatric acute ward. PLoS One. 2017 Mar 16;12(3):e0173958. doi: 10.1371/journal.pone.0173958.
10. Kessler RC et al. Suicide prediction models: A critical review of recent research with recommendations for the way forward. Mol Psychiatry. 2020 Jan;25(1):168-79. doi: 10.1038/s41380-019-0531-0.
11. Mulder R. Problems with suicide risk assessment. Aust N Z J Psychiatry. 2011 Aug;45(8):605-7. doi: 10.3109/00048674.2011.594786.
12. Pokorny AD. Prediction of suicide in psychiatric patients: Report of a prospective study. Arch Gen Psychiatry. 1983 Mar;40(3):249-57. doi: 10.1001/archpsyc.1983.01790030019002.
13. Rosen A. Detection of suicidal patients: An example of some limitations in the prediction of infrequent events. J Consult Psychol. 1954 Dec;18(6):397-403. doi: 10.1037/h0058579.
14. McHugh CM et al. (2019). Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value. BJPsych Open. 2019 Mar;5(2):e18. doi: 10.1192/bjo.2018.88.