Abstract
Background: Depression, sometimes with suicidal manifestations, is a medical condition commonly seen in primary care clinics. Routine screening for depression and suicidal ideation is recommended of all adult patients in the primary care setting because it offers depressed patients a greater chance of recovery and response to treatment, yet such screening often is overlooked or omitted.
Objective: The purpose of this study was to develop, to implement, and to test the efficacy of a systematic depression screening process to increase the identification of depression in family members of active duty soldiers older than 18 years at a military family practice clinic located on an Army infantry post in the Pacific.
Methods: The Iowa Model of Evidence-Based Practice to Promote Quality Care was used to develop a practice guideline incorporating a decision algorithm for nurses to screen for depression. A pilot project to institute this change in practice was conducted, and outcomes were measured.
Results: Before implementation, approximately 100 patients were diagnosed with depression in each of the 3 months preceding the practice change. Approximately 130 patients a month were assigned a 311.0 Code 3 months after the practice change, and 140 patients per month received screenings and were assigned the correct International Classification of Diseases, Ninth Revision Code 311.0 at 1 year. The improved screening and coding for depression and suicidality added approximately 3 minutes to the patient screening process. The education of staff in the process of screening for depression and correct coding coupled with monitoring and staff feedback improved compliance with the identification and the documentation of patients with depression. Nurses were more likely than primary care providers to agree strongly that screening for depression enhances quality of care.
Discussion: Data gathered during this project support the integration of military and civilian nurse-facilitated screening for depression in the military primary care setting. The decision algorithm should be adapted and tested in other primary care environments.