Description
Primary care providers (PCPs) are frequently the first line of treatment for suicidal ideation (SI) patients. Many PCPs report low self-efficacy in treating suicidal patients, leading to inappropriate treatment plans or avoidance of discussing SI. This quality improvement project based

Primary care providers (PCPs) are frequently the first line of treatment for suicidal ideation (SI) patients. Many PCPs report low self-efficacy in treating suicidal patients, leading to inappropriate treatment plans or avoidance of discussing SI. This quality improvement project based on the Uncertainty Reduction theory aimed to evaluate PCP's perceptions of an SI treatment algorithm and its impact on self-efficacy. Secondary aims included assessing PCP's confidence in treating suicidal patients and current treatment practices. A pre- then post-intervention survey design was utilized. All PCPs treating patients in a military medicine clinic were invited to participate in the project. Participants were sent a recruitment email containing the suicidal ideation treatment algorithm and a link to a survey developed with Qualtrics software. Participants were asked to review the SI algorithm, answer the baseline survey questions, and complete a second eight-week survey. For human subjects' protection, the survey responses were anonymous. Demographic data collected included years of clinical experience and licensure type. The data were evaluated with Intellectus software. Due to limited participation, N=4, there was insufficient data to determine the significance of implementing the SI algorithm in a primary care clinic. Central tendencies showed that most providers (n=3, 75.00%) felt less than confident treating suicidal patients. Half of the providers asked non-mental health patients about suicide less than 40% of the time (n=2, 50.00%). The data suggest that PCPs feel uncomfortable treating suicidal patients and may benefit from additional resources and training in this area.
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    Title
    • Implementation of a Suicidal Ideation Treatment Algorithm in a Military Medicine Primary Care Clinic
    Date Created
    2022-04-26
    Resource Type
  • Text
  • Collaborating institutions
    College of Nursing and Health Innovation

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