Depression is a major cause of mortality, morbidity, disability, and economic costs in theUnited States. Everyday millions of Americans navigate our complex healthcare field to find the best solution to their problem. Due to a shortage of specialized psychiatric providers, often these people must rely on the primary care settings to get the help they need. However, the lack of knowledge in screening and management of mood disorders causes many of these patients to fall through the cracks or get substandard quality of mental health care. The goal of this quality improvement project was to develop and implement a screening algorithm for depression diagnosis, management, and referrals in primary care; it sought to improve the identification and treatment of patients with major depressive disorder while flagging those that could potentially have bipolar spectrum disorder for referrals for further assessment and treatment. Over a 6-week implementation period, 30 patients, constituting 5.3% of all screened patients were identified with depressive symptoms suggestive of mood disorder. Out of those, 24 were confirmed to have a major depressive disorder (MDD) and started on antidepressants at primary care level and 6 were flagged for assessment for bipolar disorder (BPAD). All 30 patients were referred to have intake appointments at the mental health department, constituting a 20% increase in referrals. Five out of 6 patients flagged for potential BPAD were confirmed with the diagnosis. This was a significant finding as only one patient was referred and diagnosed with bipolar disorder at the previous baseline. Patients started on antidepressants had marked improvements in their clinical picture as noticed by the decrease in mean PHQ9 from 19.4 at baseline to 13.03 at follow-up (P<0.0001). There was also a significant increase in providers ordering baseline labs. The algorithm effectively improved the overall mental health care delivered at primary care levels by bettering provider knowledge about screening, diagnosing, and managing mood disorders. Future studies should aim for a more extensive implementation for higher sample size and assess long-term responses to interventions. Key words: Depression, major depressive disorder, screening algorithm, bipolar disorder.
","abstract_html":"<p>Depression is a major cause of mortality, morbidity, disability, and economic costs in theUnited States. Everyday millions of Americans navigate our complex healthcare field to find the best solution to their problem. Due to a shortage of specialized psychiatric providers, often these people must rely on the primary care settings to get the help they need. However, the lack of knowledge in screening and management of mood disorders causes many of these patients to fall through the cracks or get substandard quality of mental health care. The goal of this quality improvement project was to develop and implement a screening algorithm for depression diagnosis, management, and referrals in primary care; it sought to improve the identification and treatment of patients with major depressive disorder while flagging those that could potentially have bipolar spectrum disorder for referrals for further assessment and treatment. Over a 6-week implementation period, 30 patients, constituting 5.3% of all screened patients were identified with depressive symptoms suggestive of mood disorder. Out of those, 24 were confirmed to have a major depressive disorder (MDD) and started on antidepressants at primary care level and 6 were flagged for assessment for bipolar disorder (BPAD). All 30 patients were referred to have intake appointments at the mental health department, constituting a 20% increase in referrals. Five out of 6 patients flagged for potential BPAD were confirmed with the diagnosis. This was a significant finding as only one patient was referred and diagnosed with bipolar disorder at the previous baseline. Patients started on antidepressants had marked improvements in their clinical picture as noticed by the decrease in mean PHQ9 from 19.4 at baseline to 13.03 at follow-up (P<0.0001). There was also a significant increase in providers ordering baseline labs. The algorithm effectively improved the overall mental health care delivered at primary care levels by bettering provider knowledge about screening, diagnosing, and managing mood disorders. Future studies should aim for a more extensive implementation for higher sample size and assess long-term responses to interventions. Key words: Depression, major depressive disorder, screening algorithm, bipolar disorder.</p>","abstract_has_math":false,"creators":["Correia, Jorge"],"institution":null,"degree_name":"Doctor of Nursing Practice (DNP)","degree_level":"Open Access Thesis","degree_discipline":"Yale University School of Nursing","degree_department":null,"school":null,"contributors":["Mary Powell"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T06:16:14Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://elischolar.library.yale.edu/ysndt/1185","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mary Powell"]},{"key":"dc:creator","label":"Author","values":["Correia, Jorge"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Yale University School of Nursing"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Nursing Practice (DNP)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://elischolar.library.yale.edu/ysndt/1185"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Depression is a major cause of mortality, morbidity, disability, and economic costs in theUnited States. Everyday millions of Americans navigate our complex healthcare field to find the best solution to their problem. Due to a shortage of specialized psychiatric providers, often these people must rely on the primary care settings to get the help they need. However, the lack of knowledge in screening and management of mood disorders causes many of these patients to fall through the cracks or get substandard quality of mental health care. The goal of this quality improvement project was to develop and implement a screening algorithm for depression diagnosis, management, and referrals in primary care; it sought to improve the identification and treatment of patients with major depressive disorder while flagging those that could potentially have bipolar spectrum disorder for referrals for further assessment and treatment. Over a 6-week implementation period, 30 patients, constituting 5.3% of all screened patients were identified with depressive symptoms suggestive of mood disorder. Out of those, 24 were confirmed to have a major depressive disorder (MDD) and started on antidepressants at primary care level and 6 were flagged for assessment for bipolar disorder (BPAD). All 30 patients were referred to have intake appointments at the mental health department, constituting a 20% increase in referrals. Five out of 6 patients flagged for potential BPAD were confirmed with the diagnosis. This was a significant finding as only one patient was referred and diagnosed with bipolar disorder at the previous baseline. Patients started on antidepressants had marked improvements in their clinical picture as noticed by the decrease in mean PHQ9 from 19.4 at baseline to 13.03 at follow-up (P<0.0001). There was also a significant increase in providers ordering baseline labs. The algorithm effectively improved the overall mental health care delivered at primary care levels by bettering provider knowledge about screening, diagnosing, and managing mood disorders. Future studies should aim for a more extensive implementation for higher sample size and assess long-term responses to interventions. Key words: Depression, major depressive disorder, screening algorithm, bipolar disorder.
"]},{"key":"dc:title","label":"Title","values":["Implementing A Screening Algorithm For Depression Diagnosis, Management And Referrals In Primary Care"]}]}],"canonical_facts":{"dc:contributor":["Mary Powell"],"dc:creator":["Correia, Jorge"],"dc:description.abstract":["Depression is a major cause of mortality, morbidity, disability, and economic costs in theUnited States. Everyday millions of Americans navigate our complex healthcare field to find the best solution to their problem. Due to a shortage of specialized psychiatric providers, often these people must rely on the primary care settings to get the help they need. However, the lack of knowledge in screening and management of mood disorders causes many of these patients to fall through the cracks or get substandard quality of mental health care. The goal of this quality improvement project was to develop and implement a screening algorithm for depression diagnosis, management, and referrals in primary care; it sought to improve the identification and treatment of patients with major depressive disorder while flagging those that could potentially have bipolar spectrum disorder for referrals for further assessment and treatment. Over a 6-week implementation period, 30 patients, constituting 5.3% of all screened patients were identified with depressive symptoms suggestive of mood disorder. Out of those, 24 were confirmed to have a major depressive disorder (MDD) and started on antidepressants at primary care level and 6 were flagged for assessment for bipolar disorder (BPAD). All 30 patients were referred to have intake appointments at the mental health department, constituting a 20% increase in referrals. Five out of 6 patients flagged for potential BPAD were confirmed with the diagnosis. This was a significant finding as only one patient was referred and diagnosed with bipolar disorder at the previous baseline. Patients started on antidepressants had marked improvements in their clinical picture as noticed by the decrease in mean PHQ9 from 19.4 at baseline to 13.03 at follow-up (P<0.0001). There was also a significant increase in providers ordering baseline labs. The algorithm effectively improved the overall mental health care delivered at primary care levels by bettering provider knowledge about screening, diagnosing, and managing mood disorders. Future studies should aim for a more extensive implementation for higher sample size and assess long-term responses to interventions. Key words: Depression, major depressive disorder, screening algorithm, bipolar disorder.
"],"dc:identifier":["https://elischolar.library.yale.edu/ysndt/1185"],"dc:title":["Implementing A Screening Algorithm For Depression Diagnosis, Management And Referrals In Primary Care"],"thesis:degree_discipline":["Yale University School of Nursing"],"thesis:degree_level":["Open Access Thesis"],"thesis:degree_name":["Doctor of Nursing Practice (DNP)"]},"updated_at":"2026-07-24T06:16:14Z"}