Evaluation of an electronic clinical algorithm to improve screening and evaluation of college students for depressive symptoms. Issue 9 (23rd September 2021)

• Record Type: Journal Article
• Authors: Webb, Chris; Owens, Heather; Hager, Kathy; Lindsay, Ta'Neka; Steinbock, Stacie
• Is Part Of: Journal of the American Association of Nurse Practitioners. Volume 33:Issue 9(2021)
• Page Start: 754
• Page End: 759
• Publication Date: 2021-09-23
• Subjects: Depression -- electronic health records -- sexual and gender minorities; Nurse practitioners -- Periodicals; Nursing -- Periodicals; 610.730692
• DOI: 10.1097/JXX.0000000000000493
• Languages: English
• ISSNs: 2327-6886

Abstract

ABSTRACT: Background: 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. Local problem: 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. Methods: 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. Interventions: 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. Results: 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. Conclusions: 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.