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Studying the implementation of Zero Suicide in a large health system: Challenges, adaptations, and lessons learned
Edwin D Boudreaux1, Celine Larkin2, Ana Vallejo Sefair1
1Departments of Emergency Medicine, Psychiatry, and Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, MA, USA.
Background:
Suicide remains the 10th leading cause of death in the United States. Many patients presenting to healthcare settings with suicide risk are not identified and their risk mitigated during routine care. Our aim is to describe the planned methodology for studying the implementation of the Zero Suicide framework, a systems-based model designed to improve suicide risk detection and treatment, within a large healthcare system.
Methods:
We planned to use a stepped wedge design to roll-out the Zero Suicide framework over 4 years with a total of 39 clinical units, spanning emergency department, inpatient, and outpatient settings, involving ∼310,000 patients. We used Lean, a widely adopted a continuous quality improvement (CQI) model, to implement improvements using a centralize "hub" working with smaller "spoke" teams comprising CQI personnel, unit managers, and frontline staff.
Results:
Over the course of the study, five major disruptions impacted our research methods, including a change in The Joint Commission's safety standards for suicide risk mitigation yielding massive system-wide changes and the COVID-19 pandemic. What had been an ambitious program at onset became increasingly challenging because of the disruptions, requiring significant adaptations to our implementation approach and our study methods.
Conclusions:
Real-life obstacles interfered markedly with our plans. While we were ultimately successful in implementing Zero Suicide, these obstacles led to adaptations to our approach and timeline and required substantial changes in our study methodology. Future studies of quality improvement efforts that cut across multiple units and settings within a given health system should avoid using a stepped-wedge design with randomization at the unit level if there is the potential for sentinel, system-wide events.
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