Hillary Samples1, Elizabeth A Stuart2, Brendan Saloner2, Colleen L Barry2, Ramin Mojtabai2,3. 1. Columbia University Mailman School of Public Health, New York, NY, USA. h.samples@columbia.edu. 2. Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 3. Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract
BACKGROUND: Primary care providers encounter a large proportion of the population with depression. Yet, many primary care patients with depression remain undiagnosed and untreated. OBJECTIVE: This study aims to examine depression screening patterns and the role of screening in depression diagnosis and treatment in the outpatient primary care setting. DESIGN: This is a cross-sectional analysis of nationally representative survey data of visits to outpatient physician offices from the 2005 to 2015 National Ambulatory Medical Care Surveys. PARTICIPANTS: The sample included the first visit in the past year to a primary care provider by patients 12 years and older (N = 16,887). METHODS: The associations of visit characteristics with depression screening and of depression screening with depression diagnosis and treatment during the visit were assessed using logistic regression. Logistic regression with propensity score weighting was used to estimate the odds of depression diagnosis and treatment under the counterfactual scenario in which patients who visited providers with lower depression screening rates had visited providers with higher screening rates instead. All models were adjusted for patient and visit characteristics. KEY RESULTS: A small proportion of sample visits involved depression screening (3.0%). Visits by patients with depressive symptom complaints were associated with higher odds of depression screening than other visits. When visits were weighted to have similar demographic and clinical characteristics, visits to providers with higher screening rates had higher odds of diagnosis (OR = 1.99, p < 0.001) and treatment (OR = 1.61, p = 0.001) compared to visits to providers with lower screening rates. CONCLUSIONS: Physicians appear to use depression screening selectively based on patients' presenting symptoms. Higher screening rates were associated with higher odds of depression diagnosis and treatment, and even modest increases in screening rates could meaningfully increase population-level rates of depression identification and treatment in primary care. Future research is needed to identify barriers to depression care and implement systematic interventions to improve services and patient outcomes.
BACKGROUND: Primary care providers encounter a large proportion of the population with depression. Yet, many primary care patients with depression remain undiagnosed and untreated. OBJECTIVE: This study aims to examine depression screening patterns and the role of screening in depression diagnosis and treatment in the outpatient primary care setting. DESIGN: This is a cross-sectional analysis of nationally representative survey data of visits to outpatient physician offices from the 2005 to 2015 National Ambulatory Medical Care Surveys. PARTICIPANTS: The sample included the first visit in the past year to a primary care provider by patients 12 years and older (N = 16,887). METHODS: The associations of visit characteristics with depression screening and of depression screening with depression diagnosis and treatment during the visit were assessed using logistic regression. Logistic regression with propensity score weighting was used to estimate the odds of depression diagnosis and treatment under the counterfactual scenario in which patients who visited providers with lower depression screening rates had visited providers with higher screening rates instead. All models were adjusted for patient and visit characteristics. KEY RESULTS: A small proportion of sample visits involved depression screening (3.0%). Visits by patients with depressive symptom complaints were associated with higher odds of depression screening than other visits. When visits were weighted to have similar demographic and clinical characteristics, visits to providers with higher screening rates had higher odds of diagnosis (OR = 1.99, p < 0.001) and treatment (OR = 1.61, p = 0.001) compared to visits to providers with lower screening rates. CONCLUSIONS: Physicians appear to use depression screening selectively based on patients' presenting symptoms. Higher screening rates were associated with higher odds of depression diagnosis and treatment, and even modest increases in screening rates could meaningfully increase population-level rates of depression identification and treatment in primary care. Future research is needed to identify barriers to depression care and implement systematic interventions to improve services and patient outcomes.
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