OBJECTIVES: : Older adults in the VA Healthcare System may have an increased risk for depression than those in the general population. These factors may also be associated with the likelihood of receiving depression treatment. This study examined the associations between sociodemographic characteristics, psychiatric comorbidities, and medical comorbidities and the receipt of depression treatment among depressed older adults in the VA. DESIGN: : Secondary analysis of data obtained from the VA's National Registry for Depression, a linkage of several administrative data sources with detailed services and pharmacy data for all VA patients diagnosed with depression. SETTING: : VA healthcare system. PARTICIPANTS: : The sample included 147,631 VA patients who were at least 50 years old and received a new diagnosis of depression in FY08. MEASUREMENTS: : The associations between the depression treatment conditions (antidepressants, psychotherapy, both, and none) as outcome variables and sociodemographic characteristics, psychiatric comorbidities, and medical comorbidities as independent variables were assessed using χ tests and multinomial logistic regression analysis. RESULTS: : Approximately one-third (35.9%) of the depressed older adults did not receive any treatment. The odds receiving depression treatment decreased with increasing age. Those who were white, female and married were more likely to receive antidepressants, while those who were male of minority race/ethnicity, and unmarried were more likely to receive psychotherapy. Medical comorbidities and psychiatric comorbidities were also associated with the type of depression treatment received. CONCLUSIONS: : Many depressed older adults may have limited or no treatment. Future outreach and intervention efforts should be targeted toward this vulnerable population.
OBJECTIVES: : Older adults in the VA Healthcare System may have an increased risk for depression than those in the general population. These factors may also be associated with the likelihood of receiving depression treatment. This study examined the associations between sociodemographic characteristics, psychiatric comorbidities, and medical comorbidities and the receipt of depression treatment among depressed older adults in the VA. DESIGN: : Secondary analysis of data obtained from the VA's National Registry for Depression, a linkage of several administrative data sources with detailed services and pharmacy data for all VA patients diagnosed with depression. SETTING: : VA healthcare system. PARTICIPANTS: : The sample included 147,631 VA patients who were at least 50 years old and received a new diagnosis of depression in FY08. MEASUREMENTS: : The associations between the depression treatment conditions (antidepressants, psychotherapy, both, and none) as outcome variables and sociodemographic characteristics, psychiatric comorbidities, and medical comorbidities as independent variables were assessed using χ tests and multinomial logistic regression analysis. RESULTS: : Approximately one-third (35.9%) of the depressed older adults did not receive any treatment. The odds receiving depression treatment decreased with increasing age. Those who were white, female and married were more likely to receive antidepressants, while those who were male of minority race/ethnicity, and unmarried were more likely to receive psychotherapy. Medical comorbidities and psychiatric comorbidities were also associated with the type of depression treatment received. CONCLUSIONS: : Many depressed older adults may have limited or no treatment. Future outreach and intervention efforts should be targeted toward this vulnerable population.
Authors: Joseph A Carley; Jordan F Karp; Angela Gentili; Zachary A Marcum; M Carrington Reid; Eric Rodriguez; Michelle I Rossi; Joseph Shega; Stephen Thielke; Debra K Weiner Journal: Pain Med Date: 2015-11-05 Impact factor: 3.750
Authors: Elisheva R Danan; Erin E Krebs; Kristine Ensrud; Eva Koeller; Roderick MacDonald; Tina Velasquez; Nancy Greer; Timothy J Wilt Journal: J Gen Intern Med Date: 2017-09-14 Impact factor: 5.128
Authors: Elizabeth A DiNapoli; Jeffrey A Cully; Juliette M Mott; Natalie E Hundt; Joseph Mignogna; Shubhada Sansgiry; Hong Jen Yu; Lisa H Trahan; Mark E Kunik Journal: SAGE Open Med Date: 2015-01-08