Predicting risk of suicidal behavior from insurance claims data vs. linked data from insurance claims and electronic health records.

PURPOSE: Observational studies assessing effects of medical products on suicidal behavior often rely on health record data to account for pre-existing risk. We assess whether high-dimensional models predicting suicide risk using data derived from insurance claims and electronic health records (EHRs) are superior to models using data from insurance claims alone. METHODS: Data were from seven large health systems identified outpatient mental health visits by patients aged 11 or older between 1/1/2009 and 9/30/2017. Data for the 5 years prior to each visit identified potential predictors of suicidal behavior typically available from insurance claims (e.g., mental health diagnoses, procedure codes, medication dispensings) and additional potential predictors available from EHRs (self-reported race and ethnicity, responses to Patient Health Questionnaire or PHQ-9 depression questionnaires). Nonfatal self-harm events following each visit were identified from insurance claims data and fatal self-harm events were identified by linkage to state mortality records. Random forest models predicting nonfatal or fatal self-harm over 90 days following each visit were developed in a 70% random sample of visits and validated in a held-out sample of 30%. Performance of models using linked claims and EHR data was compared to models using claims data only. RESULTS: Among 15 845 047 encounters by 1 574 612 patients, 99 098 (0.6%) were followed by a self-harm event within 90 days. Overall classification performance did not differ between the best-fitting model using all data (area under the receiver operating curve or AUC = 0.846, 95% CI 0.839-0.854) and the best-fitting model limited to data available from insurance claims (AUC = 0.846, 95% CI 0.838-0.853). Competing models showed similar classification performance across a range of cut-points and similar calibration performance across a range of risk strata. Results were similar when the sample was limited to health systems and time periods where PHQ-9 depression questionnaires were recorded more frequently. CONCLUSION: Investigators using health record data to account for pre-existing risk in observational studies of suicidal behavior need not limit that research to databases including linked EHR data.

Determinants and Predictive Value of Clinician Assessment of Short-Term Suicide Risk.

We examine the interrelations among clinicians' judgment of patients' suicide risk, clinicians' emotional responses, and standard risk factors in the short-term prediction of suicidal thoughts and behaviors. Psychiatric outpatients (n = 153) with a lifetime history of suicide ideation/attempt and their treating clinicians (n = 67) were evaluated at intake. Clinicians completed a standard suicide risk instrument (modified SAD PERSONS scale), a 10-point Likert scale assessment of judgment of patient suicide risk (Clinician Prediction Scale), and a measure of their emotional responses to the patient (Therapist Response Questionnaire-Suicide Form). The Columbia Suicide Severity Rating Scale and the Beck Scale for Suicide Ideation were administered at a one-month follow-up assessment (n = 114, 74.5%). Clinician judgment of risk significantly predicted suicidal thoughts and behaviors at follow-up. Both the standard suicide risk instrument and clinician emotional responses contributed independently to the clinician assessment of risk, which, in turn, mediated their relationships with suicidal thoughts and behaviors. Our findings validate the importance of clinical judgment in assessing suicide risk. Clinical judgment appears to be informed both by concrete risk factors and clinicians' emotional responses to suicidal patients, highlighting emotional awareness as a promising area for research and training.

Prediction of suicidal behavior in high risk psychiatric patients using an assessment of acute suicidal state: The suicide crisis inventory.

BACKGROUND: We have developed the Suicide Crisis Inventory (SCI) to evaluate the intensity of the Suicidal Crisis Syndrome, an acute state hypothesized to precede suicide attempt. The psychometric properties of the SCI, including predictive validity for suicidal behavior (SB), were assessed. METHODS: Adult psychiatric patients (n = 201) hospitalized for high suicide risk were assessed. Logistic regression models assessed the SCI's predictive validity for SB in the 4-8 weeks following hospital discharge and its incremental predictive validity over traditional risk factors (n = 137, 64% f/u rate). Internal structure, reliability, convergent and discriminant validity, and state versus trait properties were also assessed. RESULTS: The SCI had excellent internal consistency (Cronbach's α 0.970). The SCI total score at discharge predicted short-term SB with 64% sensitivity 88% specificity (OR = 13, P = .003) at its optimal cut score. In a test of its incremental predictive validity, SCI total score at discharge improved prediction of SB over traditional risk factors (Chi-squared 5.597, P = .024, model P = .001), with AOR 2.02 (P = .030). The SCI admission versus discharge test-retest reliability and score distributions showed it to be an acute state measure. CONCLUSION: The SCI was predictive of future SB in high-risk psychiatric inpatients during the crucial weeks following their hospital discharge. Further validation in diverse patient populations is needed.

The Modular Assessment of Risk for Imminent Suicide (MARIS): A proof of concept for a multi-informant tool for evaluation of short-term suicide risk.

BACKGROUND: To date, no diagnostic tool has demonstrated clinical value for the assessment of short-term suicide risk among high-risk individuals. To this end we have developed the Modular Assessment of Risk for Imminent Suicide (MARIS), a modular patient and clinician informed risk evaluation instrument. Here we assess its predictive validity for suicidal behavior (SB) in psychiatric patients following discharge from an inpatient unit. METHODS: The MARIS and a psychological test battery were administered to 136 adult psychiatric patients hospitalized for high risk of suicide. Eighty-six participants had complete data at discharge and 59 (69.8%) were reached for follow-up. Logistic regressions were used to assess the predictive validity of the MARIS for SB over the 4-8weeks following hospital discharge and its incremental predictive validity over standard risk factors. RESULTS: Patients who exhibited SB in the period between initial assessment and follow-up had significantly higher MARIS scores. ROC analysis indicated good sensitivity and specificity of MARIS in identifying risk (OR=19). Further, MARIS total score significantly improved predictive validity by the standard risk factors when added to a model comprising global depression severity, hopelessness, and lifetime number of suicide attempts, and was the only factor that approached independent significance. CONCLUSION: The MARIS appears to be a practical and effective tool for detecting short-term suicide risk following hospital discharge, supporting the validity of modular multi-informant approach to suicide risk evaluation. Replication of these findings and further investigation of the applications of such an approach are warranted.

Assessment of Sexual Fantasies in Psychiatric Inpatients With Mood and Psychotic Disorders and Comorbid Personality Disorder Traits.

INTRODUCTION: Sexuality is an important aspect of quality of life and sexual fantasies comprise a normal part of human sexuality. However, the nature of sexuality and sexual fantasies of patients with mental illness remains an understudied area. AIM: To investigate the nature and frequency of sexual fantasies in psychiatric patients, the present study compared the frequency of four types of sexual fantasies across four different mood and psychotic diagnoses and three personality disorder clusters. METHODS: Study participants included 133 psychiatric inpatients recruited from an urban hospital. Sexual fantasies were compared across patients with schizophrenia, bipolar disorder, schizoaffective disorder, major depressive disorder and three nonclinical samples from the literature and then correlated with personality cluster scores. MAIN OUTCOME MEASURES: Subjects were administered the Structured Clinical Interview for DSM-IV for Axis I and for Axis II Disorders. Sexual fantasies were assessed by the Wilson Sexual Fantasies Questionnaire, which measures four types of sexual fantasies (exploratory, intimate, impersonal, and sadomasochistic). RESULTS: Within the entire sample, there were significant differences across sexual fantasy types, with subjects scoring highest on intimate sexual fantasies and then exploratory, impersonal, and sadomasochistic. There were no significant differences across mood and psychotic diagnostic groups for any of the sexual fantasy scales and the scores were within the normative range of nonclinical samples. Patients with high cluster B scores scored significantly higher on all four fantasy scales than those without. Patients with high cluster A scores scored lower on intimate fantasies, but there was no association between cluster C scores and sexual fantasies. The association between cluster B and sexual fantasies remained consistent across Structured Clinical Interview for DSM-IV for Axis I diagnoses (no interaction effect). CONCLUSION: Patients with severe mental illness report sexual fantasies that are largely affiliative in nature and consistent with normative patterns. This suggests that assessment and treatment of sexual issues in the mentally ill should be part of the clinical routine as it is in healthy individuals.

Teaching evidence-based approaches to suicide risk assessment and prevention that enhance psychiatric training.

This report describes one in a series of National Institute of Health (NIH) supported conferences aimed at enhancing the ability of leaders of psychiatry residency training to teach research literacy and produce both clinician-scholars and physician-scientists in their home programs. Most psychiatry training directors would not consider themselves research scholars or even well-schooled in evidence based practice. Yet they are the front line educators to prepare tomorrow's psychiatrists to keep up with, critically evaluate, and in some cases actually participate in the discovery of new and emerging psychiatric knowledge. This annual conference is meant to help psychiatry training directors become more enthusiastic, knowledgeable and pedagogically prepared to create research-friendly environments at their home institutions, so that more trainees will, in turn, become research literate, practice evidence-based psychiatry, and enter research fellowships and careers. The overall design of each year's meeting is a series of plenary sessions introducing participants to new information pertaining to the core theme of that year's meeting, integrated with highly interactive small group teaching sessions designed to consolidate knowledge and provide pragmatic teaching tools appropriate for residents at various levels of training. The theme of each meeting, selected to be a compelling and contemporary clinical problem, serves as a vehicle to capture training directors' attention while teaching relevant brain science, research literacy and effective pedagogy. This report describes the content and assessment of the 2011 annual pre-meeting, "Evidence-based Approaches to Suicide Risk Assessment and Prevention: Insights from the Neurosciences and Behavioral Sciences for use in Psychiatry Residency Training."

Can depression be diagnosed by response to mother's face? A personalized attachment-based paradigm for diagnostic fMRI.

OBJECTIVE: Objective measurement of depression remains elusive. Depression has been associated with insecure attachment, and both have been associated with changes in brain reactivity in response to viewing standard emotional and neutral faces. In this study, we developed a method to calculate predicted scores for the Beck Depression Inventory II (BDI-II) using personalized stimuli: fMRI imaging of subjects viewing pictures of their own mothers. METHODS: 28 female subjects ages 18-30 (14 healthy controls and 14 unipolar depressed diagnosed by MINI psychiatric interview) were scored on the Beck Depression Inventory II (BDI-II) and the Adult Attachment Interview (AAI) coherence of mind scale of global attachment security. Subjects viewed pictures of Mother (M), Friend (F) and Stranger (S), during functional magnetic resonance imaging (fMRI). Using a principal component regression method (PCR), a predicted Beck Depression Inventory II (BDI-II) score was obtained from activity patterns in the paracingulate gyrus (Brodmann area 32) and compared to clinical diagnosis and the measured BDI-II score. The same procedure was performed for AAI coherence of mind scores. RESULTS: Activity patterns in BA-32 identified depressed subjects. The categorical agreement between the derived BDI-II score (using the standard clinical cut-score of 14 on the BDI-II) and depression diagnosis by MINI psychiatric interview was 89%, with sensitivity 85.7% and specificity 92.8%. Predicted and measured BDI-II scores had a correlation of 0.55. Prediction of attachment security was not statistically significant. CONCLUSIONS: Brain activity in response to viewing one's mother may be diagnostic of depression. Functional magnetic resonance imaging using personalized paradigms has the potential to provide objective assessments, even when behavioral measures are not informative. Further, fMRI based diagnostic algorithms may enhance our understanding of the neural mechanisms of depression by identifying distinctive neural features of the illness.