Evaluation of an electronic clinical algorithm to improve screening and evaluation of college students for depressive symptoms

病人健康调查表 性取向 数据收集 医学 萧条(经济学) 女同性恋 性少数派 变性人 临床心理学 机构审查委员会 家庭医学 精神科 抑郁症状 心理学 焦虑 经济 宏观经济学 统计 社会心理学 数学 精神分析
作者
Chris Webb,Heather Owens,Kathy Hager,T. Bruce Lindsay,Stacie Steinbock
出处
期刊:Journal of the American Association of Nurse Practitioners [Ovid Technologies (Wolters Kluwer)]
卷期号:33 (9): 754-759
标识
DOI:10.1097/jxx.0000000000000493
摘要

Depression is higher among college students compared with the general population, and lesbian, gay, bisexual, transgender and questioning/queer (LGBTQ+) persons have higher rates than heterosexuals. Evidence supports the implementation of automated depressive symptoms screenings to improve provider compliance.A student health clinic at a private, catholic university did not consistently collect Patient Health Questionnaire 2 (PHQ-2) and Patient Health Questionnaire 9 (PHQ-9) depressive screening scores or sexual orientation and gender identity (SOGI) data.The Plan-Do-Study-Act method of quality improvement was used to improve depressive symptom screenings and SOGI data collection. Baseline assessment included a review of patient medical records during a 10-week period before the intervention.Patient Health Questionnaire 2 data were collected electronically and PHQ-9 data were collected automatically when indicated. Sexual orientation and gender identity data were added to the electronic intake form. The project was evaluated by: (1) comparing preimplementation and postimplementation compliance of PHQ-2 and PHQ-9 screenings; (2) assessing SOGI data collection; and (3) comparing LGBTQ+ and heterosexual student's PHQ-2 scores.Preimplementation data revealed a PHQ-2 compliance rate of 44.3%, with 0% PHQ-9 compliance, and no self-reported SOGI data collection. Postimplementation, PHQ-2 and PHQ-9 compliance increased to 93.2% and 100%, respectively. Patient Health Questionnaire 2 scores did not differ between LGBTQ+ and heterosexual students.The electronic clinical algorithm increased PHQ-2 and PHQ-9 data collection, supporting automated screenings for depressive symptoms. Collection of SOGI data also improved, thus potentially improving health outcomes. No differences between LGBTQ+ and heterosexual student's depressive symptoms were identified.
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