Table 1.

Ethical Framework to Guide Implementation of Suicide Risk Prediction Models

		Issues	Questions Suicide Risk Prediction Model Adopters Need to Consider
Ethical Principles	1 Autonomy	Informed Consent	How will the health system exercise its obligation to ensure patients have a clear understanding of the types of predictors that will be accessed from their data, or what the inclusion of that data means for benefits and risks associated with a suicide risk identification dataset and the alternatives?
		Patient Choice to Conceal or Disclose Suicide Risk	How can patients’ rights to autonomy (e.g., to exercise choice to participate or be excluded from suicide risk identification, to conceal or disclose suicide behavior) be balanced with the potential lost opportunity to identify at-risk individuals who might opt out??
			How will the health system operationalize informed consent/opt-out in a manner that fosters trust?
	2 Explainability	Application of Suicide Risk Models in Populations They Were Not Developed For	On what population was the suicide risk prediction model developed and validated?
			In which populations is implementation appropriate?
			How should subgroup representation in the development/validation datasets inform implementation decisions?
			Are there subgroups that might not benefit as much as others or could be disproportionately harmed?
		Limitations of Electronic Health Records Data	What kinds of predictors are in the model? What known risk factors are not included because they are not adequately documented in health records? How does the health system ensure that clinicians understand this? How will the health system educate clinicians and patients (when necessary) about what the risk scores mean and do not mean?
			How will the health system update the model over time with improved capture of important risk factors (e.g., demographic, social determinants of health)?
			How frequently does the model need to be run so that recently documented predictors (e.g., yesterday’s suicide attempt) are captured? How does the health system ensure that clinicians understand this?
		Ambiguity of Risk Predictors	How should clinicians use the risk score with patients, particularly if risk predictors (and interactions) are not discernable?
	3 Beneficence, Distributive Justice	Selecting Actionable Risk Thresholds	What is a reasonable threshold where the health system can expect to have sufficient resources to appropriately follow up with at-risk individuals?
			What resources are available?
			What resources will be (re-) allocated to support follow up?
			Is the goal to identify and follow up with the highest risk patients (targeted reach, high intensity intervention) or to prevent the most suicide attempts (broad reach, low intensity intervention)?
	4 Privacy	Access to Risk Information & Stigma	How, if at all, should risk identification information (i.e., risk score) appear in the electronic health record? Who should it be visible to within the health system? Outside the system?
			Should the risk score become part of the patient’s permanent record (versus a transient flag that is not stored)?
			Which staff should be responsible for following up with patients identified high-risk?
			How would the health system know if patients experienced stigma as a result of risk identification?
	5 Non-maleficence	Risk Models Could Introduce Unanticipated Harms, Lead to Inappropriate Intervention, or Be Used to Deny Services	Have we thoroughly considered and mitigated possible harms?
			How will the health system monitor and respond to unintended consequences?
			What would cause us to halt automated suicide risk identification?
	6 Stewardship	Risk models will drift over time and require evaluation, maintenance, and recalibration	Does the health system have resources allocated (i.e., dedicated staff with modeling expertise) to continuously monitor drift and recalibrate models as needed over time?
			How will the health system measure interventions that would result from automated risk identification so that receipt of the interventions can become predictors in the model?
		Ongoing oversight	What kind of governing board or ethical oversight committee does the health system need to review implementation plans, monitor appropriate use of the model, surveil harms, and maintain patient trust?