Correlates of depression among people with diabetes: The Translating Research Into Action for Diabetes (TRIAD) study

Aim The broad objective of this study was to examine multiple dimensions of depression in a large, diverse population of adults with diabetes. Specific aims were to measure the association of depression with: (1) patient characteristics(2) outcomesand (3) diabetes-related quality of care. Methods Cross-sectional analyses were performed using survey and chart data from the Translating Research Into Action for Diabetes (TRIAD) study, including 8790 adults with diabetes, enrolled in 10 managed care health plans in 7 states. Depression was measured using the Patient Health Questionnaire (PHQ-8). Patient characteristics, outcomes and quality of care were measured using validated survey items and chart data. Results Nearly 18% of patients had major depression, with prevalence 2-3 times higher among patients with low socioeconomic status. Pain and limited mobility were strongly associated with depression, controlling for other patient characteristics. Depression was associated with slightly worse glycemic control, but not other intermediate clinical outcomes. Depressed patients received slightly fewer recommended diabetes-related processes of care. Conclusions In a large, diverse cohort of patients with diabetes, depression was most prevalent among patients with low socioeconomic status and those with pain, and was associated with slightly worse glycemic control and quality of care

Predictors and Impact of Intensification of Antihyperglycemic Therapy in Type 2 Diabetes: Translating Research into Action for Diabetes (TRIAD)

ObjectiveThe purpose of this study was to examine the predictors of intensification of antihyperglycemic therapy in patients with type 2 diabetes; its impact on A1C, body weight, symptoms of anxiety/depression, and health status; and patient characteristics associated with improvement in A1C.Research design and methodsWe analyzed survey, medical record, and health plan administrative data collected in Translating Research into Action for Diabetes (TRIAD). We examined patients who were using diet/exercise or oral antihyperglycemic medications at baseline, had A1C >7.2%, and stayed with the same therapy or intensified therapy (initiated or increased the number of classes of oral antihyperglycemic medications or began insulin) over 18 months.ResultsOf 1,093 patients, 520 intensified therapy with oral medications or insulin. Patients intensifying therapy were aged 58 +/- 12 years, had diabetes duration of 11 +/- 9 years, and had A1C of 9.1 +/- 1.5%. Younger age and higher A1C were associated with therapy intensification. Compared with patients who did not intensify therapy, those who intensified therapy experienced a 0.49% reduction in A1C (P < 0.0001), a 3-pound increase in weight (P = 0.003), and no change in anxiety/depression (P = 0.5) or health status (P = 0.2). Among those who intensified therapy, improvement in A1C was associated with higher baseline A1C, older age, black race/ethnicity, lower income, and more physician visits.ConclusionsTreatment intensification improved glycemic control with no worsening of anxiety/depression or health status, especially in elderly, lower-income, and minority patients with type 2 diabetes. Interventions are needed to overcome clinical inertia when patients might benefit from treatment intensification and improved glycemic control

Race/Ethnicity and Economic Differences in Cost-Related Medication Underuse Among Insured Adults With Diabetes The Translating Research Into Action for Diabetes Study

ObjectiveTo examine racial/ethnic and economic variation in cost-related medication underuse among insured adults with diabetes.Research design and methodsWe surveyed 5,086 participants from the multicenter Translating Research Into Action for Diabetes Study. Respondents reported whether they used less medication because of cost in the past 12 months. We examined unadjusted and adjusted rates of cost-related medication underuse, using hierarchical regression, to determine whether race/ethnicity differences still existed after accounting for economic, health, and other demographic variables.ResultsParticipants were 48% white, 14% African American, 14% Latino, 15% Asian/Pacific Islander, and 8% other. Overall, 14% reported cost-related medication underuse. Unadjusted rates were highest for Latinos (23%) and African Americans (17%) compared with whites (13%), Asian/Pacific Islanders (11%), and others (15%). In multivariate analyses, race/ethnicity significantly predicted cost-related medication underuse (P = 0.048). However, adjusted rates were only slightly higher for Latinos (14%) than whites (10%) (P = 0.026) and were not significantly different for African Americans (11%), Asian/Pacific Islanders (7%), and others (11%). Income and out-of-pocket drug costs showed the greatest differences in adjusted rates of cost-related medication underuse (15 vs. 5% for participants with income $50,000 and 24 vs. 7$150 per month vs. ConclusionsOne in seven participants reported cost-related medication underuse. Rates were highest among African Americans and Latinos but were related to lower incomes and higher out-of-pocket drug costs in these groups. Interventions to decrease racial/ethnic disparities in cost-related medication underuse should focus on decreasing financial barriers to medications

Predicting suicide attempts and suicide deaths among adolescents following outpatient visits

BACKGROUND: Few studies report on machine learning models for suicide risk prediction in adolescents and their utility in identifying those in need of further evaluation. This study examined whether a model trained and validated using data from all age groups works as well for adolescents or whether it could be improved. METHODS: We used healthcare data for 1.4 million specialty mental health and primary care outpatient visits among 256,823 adolescents across 7 health systems. The prediction target was 90-day risk of suicide attempt following a visit. We used logistic regression with least absolute shrinkage and selection operator (LASSO) and generalized estimating equations (GEE) to predict risk. We compared performance of three models: an existing model, a recalibrated version of that model, and a newly-learned model. Models were compared using area under the receiver operating curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The AUC produced by the existing model for specialty mental health visits estimated in adolescents alone (0.796; [0.789, 0.802]) was not significantly different than the AUC of the recalibrated existing model (0.794; [0.787, 0.80]) or the newly-learned model (0.795; [0.789, 0.801]). Predicted risk following primary care visits was also similar: existing (0.855; [0.844, 0.866]), recalibrated (0.85 [0.839, 0.862]), newly-learned (0.842, [0.829, 0.854]). LIMITATIONS: The models did not incorporate non-healthcare risk factors. The models relied on ICD9-CM codes for diagnoses and outcome measurement. CONCLUSIONS: Prediction models already in operational use by health systems can be reliably employed for identifying adolescents in need of further evaluation

Changes in antidepressant use by young people and suicidal behavior after FDA warnings and media coverage: quasi-experimental study

Objective To investigate if the widely publicized warnings in 2003 from the US Food and Drug Administration about a possible increased risk of suicidality with antidepressant use in young people were associated with changes in antidepressant use, suicide attempts, and completed suicides among young people. Design Quasi-experimental study assessing changes in outcomes after the warnings, controlling for pre-existing trends. Setting Automated healthcare claims data (2000-10) derived from the virtual data warehouse of 11 health plans in the US Mental Health Research Network. Participants Study cohorts included adolescents (around 1.1 million), young adults (around 1.4 million), and adults (around 5 million). Main outcome measures Rates of antidepressant dispensings, psychotropic drug poisonings (a validated proxy for suicide attempts), and completed suicides. Results Trends in antidepressant use and poisonings changed abruptly after the warnings. In the second year after the warnings, relative changes in antidepressant use were −31.0% (95% confidence interval −33.0% to −29.0%) among adolescents, −24.3% (−25.4% to −23.2%) among young adults, and −14.5% (−16.0% to −12.9%) among adults. These reflected absolute reductions of 696, 1216, and 1621 dispensings per 100 000 people among adolescents, young adults, and adults, respectively. Simultaneously, there were significant, relative increases in psychotropic drug poisonings in adolescents (21.7%, 95% confidence interval 4.9% to 38.5%) and young adults (33.7%, 26.9% to 40.4%) but not among adults (5.2%, −6.5% to 16.9%). These reflected absolute increases of 2 and 4 poisonings per 100 000 people among adolescents and young adults, respectively (approximately 77 additional poisonings in our cohort of 2.5 million young people). Completed suicides did not change for any age group. Conclusions Safety warnings about antidepressants and widespread media coverage decreased antidepressant use, and there were simultaneous increases in suicide attempts among young people. It is essential to monitor and reduce possible unintended consequences of FDA warnings and media reporting

Transition From Pediatric to Adult Care for Youth Diagnosed With Type 1 Diabetes in Adolescence

Youth with type 1 diabetes mellitus are at risk for poor glycemic control as they age into adulthood. The aim of this study was to describe sociodemographic and clinical correlates of poor glycemic control associated with the transfer of care from pediatric to adult diabetes providers among a cohort of youth with type 1 diabetes diagnosed in adolescence

Interactive Video Assists in Clinical Decision Making

AbstractThe Hawaii Quality and Cost Consortium began a project in 1993 to implement and evaluate interactive videodisk programs to assist in clinical decision-making for breast cancer. Communication problems between physicians and patients, limitations of available outcomes data and varying preferences of individual patients can result in treatment outcomes that are less than satisfactory. Shared Decision-making Programs (SDPs) were developed by the Foundation for Informed Medical Decision Making (FIMDM) in Hanover, New Hampshire, to assist in the treatment decision-making process. Utilizing interactive videodisks, the programs provide patients with clear, unbiased information about available treatment options. With this information, patients can become more active participants in making treatment decisions. The SDPs for breast cancer were implemented at two sites in Hawaii. Evaluation data from 103 patients overwhelmingly indicate that patients find the programs clear, balanced and very good or excellent in terms of the amount of information presented and overall rating.</jats:p