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Suicide Risk Assessments in Hospitals Using Systematic Expert Risk Assessment for Suicide (SERAS)

Robert R. Althoff, MD, PhD Associate Professor of Psychiatry, Pediatrics, & Psychological Science Director of Adirondack Division of Psychiatry Larner College of Medicine at the University of Vermont VT Suicide Prevention Symposium June 5, 2018

Conflict of Interest Disclosure

• Co-Inventor of SERAS (Systematic Expert Risk Assessment for

Suicide).

• Equity stake in WISER Systems, LLC – holds license from UVM to

commercialize SERAS.

The Team

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William Cats-Baril, PhD

Associate Professor, UVM Grossman School of Business; Founding Director of MBA on Sustainable Entrepreneurship

Isabelle Desjardins, MD

General and Geriatric Psychiatrist, Associate Professor, UVM-COM; Chief Medical Officer, University of Vermont Medical Center

Sanchit Maruti, MD

Addiction Psychiatrist, Assistant Professor, UVM- COM; Medical Director, UVM-Medical Center Suboxone Program.

Robert Althoff, MD, PhD

Child and Adolescent Psychiatrist; Associate Professor, UVM-COM; Director, Adirondack Division of Psychiatry, New York

William Hudenko, PhD

Assistant Professor, Dartmouth College. CEO Incente llc, Winner of the 2016 Dartmouth Entrepreneurial Forum StartUp Competition.

Donna Rizzo, PhD

Professor and Dorothean Chair, UVM College of Engineering and Mathematical Sciences. Expert in complex systems.

John Helzer, MD

Professor Emeritus, UVM; 40 years of research experience and 15 years of eHealth approaches to alcohol assessment, smoking, ECT, and pain management

Michael Goedde, MD, MS

UVM-COM graduate and training in psychiatry and research methods.

Epidemiology of Suicide in Hospitals

• 2nd most frequently reported of the five serious events

reported to the Joint Commission since 1995

• Many patients who kill themselves in general hospital

inpatient units are “unknown at risk” for suicide

– No psychiatric history or – No history of suicide attempt

• The Sentinel Event Database includes 827 reports of

inpatient suicides:

The Joint Commission, Sentinel Event Alert, Issue 46, November 17, 2010 Bostwick JM, Rackley, SJ: Completed Suicide in Medical/Surgical Patients: Who is At Risk? Current Psychiatry Reports, 2007;9:242‐246

Joint Commission Sentinel Alert #56

• Detecting and treating suicide ideation in all settings;
• Most individuals who die by suicide receive health care

services in the year prior to death, usually for reasons unrelated to suicide or mental health.

• National Patient Safety Goal 15.01.01 requires General

hospitals to identify individuals at risk for suicide.

• …requires…“general hospitals treating individuals for emotional or

behavioral disorders, to conduct a risk assessment that identifies specific individual characteristics and environmental features that may increase the risk of suicide and to address safety needs such as placing a patient under constant observation if the patient exhibits warning signs.”

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Detection Tools

PHQ2/PHQ9

• Detects Major

Depression ED‐SAFE Patient Safety Screener

• PHQ2 and

portions of C‐ SSRS

• Holds

predictive validity for lifetime suicide risk SBQ‐R/ASQ

• Assesses

suicide related thoughts and behaviors

• Differentiates

suicidal from nonsuicidal patients overall

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Secondary Screening

ED‐SAFE Patient Safety Secondary Screener for EDs SAFE‐T Pocket Card

• Assess dimensions of suicide risk to help the clinician come to a

risk assessment. C‐SSRS

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The Need

• Tools to specifically assess imminent/near term risk
• Tools that use accumulated risk factor information and

also account for expert weighting of risk factors and clinical data

Brown GK. (2002). A review of suicide assessment measures for intervention research in adults and older adults. Technical report submitted to NIMH under Contract No. 263- MH914950. 8

Hypothesis

We can replicate the judgment of Board-Certified Psychiatrists in assessing the near-term risk of suicide (next 72-hours) and the associated expert intervention recommendations

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Phase 1: Model Development

Expert Panel

• Convened Panel of National Experts
• Comprehensive Literature Review
• Discussed important components of an ideal suicide risk

assessment tool

Case Review/Revision

• Revised and Added Cases to cover full range of suicide risk
• Reviewed Cases
• Rated patient profiles based on likelihood of Acute suicide

in the hospital setting in the next 72 hours

Group Consensus Process

• Utilized Nominal Group Technique (NGT)to identify risk variables,

ranges and weights on those variables and discussed aggregation methods (compensatory/non‐compensatory, etc.)

• Compared the experts’ rankings and addressed inconsistencies

and disagreements

• Created a preliminary model that included critical features that

should be in the computerized screening

Suicide Risk Assessment Questions

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Discovery Sample

• Testing of algorithm against expert consensus in

the ED patient population

• Psychiatrists examining patients in ED were

trained using the same cases as the Expert Panel

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S Discovery Samplea2

Mean Age: 42.6 [SD 17 years] Male: 48% Primary Psych Complaint: 8%

%

Categories of Risk (RISK)

High

Even considering mitigating protective factors, the acute risk

• f suicide – in the

following 72 hours‐ is high Suicide Possible and Likely

Moderate

The combination of risk factors and mitigating protective factors yield a risk of suicide in the following 72 hours that is only moderate Suicide Possible, but Unlikely

Low

Although there may be suicide risk factors present, the combination of risk factors and mitigating protective factors yield a relatively low risk of suicide in the following 72 hours Suicide Very Unlikely

Minimal

The risk of suicide in the following 72 hours is minimal.

Categories of Interventions (INT)

TYPE OF INTERVENTION ROUTINE SPECIALIZED HIGHLY SPECIALIZED SECURED Psychiatric Assessment No Psychiatry or Crisis Consultation Psychiatry or Crisis Consultation Psychiatry or Crisis Consultation Environment of Care Modification No No Environment of care free of harmful hazards Environment of care free of harmful hazards Level of Observation Routine Routine Routine Constant Observation After Care Referral Routine Yes Yes Yes Education re Suicide Prevention Resources at Discharge Yes Yes Yes Yes

Neural

Neural Network Model ‐ RISK Model -

RISK

Classification Errors: Psych Chief Complaint in 100% of cases

Ne

Neural Network Model ‐ INT r Model

• INT

Classification Errors: Psych Chief Complaint in 100% of cases

Replication and Extension Samples ED Med-Surg Inpatient Psychiatry

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Partnership

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Partnership

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EMR Integration

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EMR Integration

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Conclusions

Novel Approach to Suicide Risk Assessment in hospitals

– Expert Systems Approach/ Neural Network mathematical model – User Friendly – iPad based and patient self-administered – Time Efficient – Able to replicate the Risk Assessment and Intervention recommendations of expertly-trained clinicians for ED and Med- Surg populations – Only predicts expert assessment of near-term risk (72 hours) – Risk assessment is contextual to the environment of care

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Next Steps

• Have just completed a new trial of 480 participants in

emergency room setting who received SERAS, C-SSRS, expert risk assessment, and 72 hour follow up

• Finalizing data analysis now
• Can report that SERAS did again detect several individuals who

had not reported suicidal ideation in any other format

• We see SERAS as an easy to use general tool that can direct

the need for more refined assessment

• Integration with social media
• Enhancement with VOI to include REACH – a

mechanism for incorporating social supports

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Acknowledgements

• Funding:

– Fletcher Allen Foundation – University of Vermont Medical Group (UVMMG) Research and Education Committee – SPARK-VT – National Institute of Mental Health

• Contributors:

– University of Vermont EMRAP program – Jeffords Quality Institute – Ms. Diantha Howard – Ms. Abigail Wager – Ms. Chelsea Manning – Conor Carpenter, MD – Judy Lewis, MD, Isabel Norian, MD, Anne Rich, MD, Tobey Horn, MD for their contribution to the Expert Assessments

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