Beth Waitzfelder

Glycemic control in youth with diabetes: the SEARCH for diabetes in Youth Study.

OBJECTIVE To assess correlates of glycemic control in a diverse population of children and youth with diabetes. STUDY DESIGN This was a cross-sectional analysis of data from a 6-center US study of diabetes in youth, including 3947 individuals with type 1 diabetes (T1D) and 552 with type 2 diabetes (T2D), using hemoglobin A(1c) (HbA(1c)) levels to assess glycemic control. RESULTS HbA(1c) levels reflecting poor glycemic control (HbA(1c) >or= 9.5%) were found in 17% of youth with T1D and in 27% of those with T2D. African-American, American Indian, Hispanic, and Asian/Pacific Islander youth with T1D were significantly more likely to have higher HbA(1c) levels compared with non-Hispanic white youth (with respective rates for poor glycemic control of 36%, 52%, 27%, and 26% vs 12%). Similarly poor control in these 4 racial/ethnic groups was found in youth with T2D. Longer duration of diabetes was significantly associated with poorer glycemic control in youth with T1D and T2D. CONCLUSIONS The high percentage of US youth with HbA(1c) levels above the target value and with poor glycemic control indicates an urgent need for effective treatment strategies to improve metabolic status in youth with diabetes.

Prevalence of overweight and obesity in youth with diabetes in USA: the SEARCH for Diabetes in Youth study.

Liu LL, Lawrence JM, Davis C, Liese AD, Pettitt DJ, Pihoker C, Dabelea D, Hamman R, Waitzfelder B, Kahn HS. Prevalence of overweight and obesity in youth with diabetes in USA: the SEARCH for Diabetes in Youth Study.

Prevalence and Correlates of Depressed Mood Among Youth With Diabetes: The SEARCH for Diabetes in Youth Study

OBJECTIVE.The objective of this study was to determine if depressed mood among youth with diabetes was associated with type and duration of diabetes, mean glycosylated hemoglobin (HbA1c) level, and the frequency of diabetic ketoacidosis (DKA) and hypoglycemic episodes, hospitalizations, and emergency department (ED) visits. METHODS.A total of 2672 youth (aged 10–21 years) who had diabetes for a mean duration of 5 years completed a SEARCH study visit, in which their HbA1c was measured and information about their demographic characteristics, diabetes type and duration, and episodes of DKA, hypoglycemia, hospitalizations, and ED visits over the previous 6 months was collected. Their level of depressed mood was measured using the Center for Epidemiologic Studies Depression Scale (CES-D). RESULTS.Among these youth, 14% had mildly (CES-D 16–23) and 8.6% had moderately or severely (CES-D ≥24) depressed mood. Females had a higher mean CES-D score than males. After adjusting for demographic factors, and duration of diabetes, we found the prevalence of depressed mood to be higher among males with type 2 diabetes than those with type 1 diabetes and to be higher among females with comorbidities than those without comorbidities. Higher mean HbA1c and frequency of ED visits were associated with depressed mood. The prevalence of depressed mood among youth with diabetes was similar to that of published estimates of depressed mood among youth without diabetes. CONCLUSIONS.Physicians and other health care professionals should consider screening youth with diabetes for depressed mood in clinical settings, particularly youth with poor glycemic control, those with a history of frequent ED visits, males with type 2 diabetes, and females with comorbidities.

The Association between Quality of Care and the Intensity of Diabetes Disease Management Programs

Context Little is known about the effects of quality-of-care improvement programs on the process of care and outcomes of diabetes. Contribution The study involved 8661 patients with diabetes, 63 provider groups, and 3 disease management strategies (provider feedback, reminders, and structured care). The quality measures included 8 processes of care, 3 intermediate diabetes outcomes, and medication management of these outcomes. More intense disease management strategies predicted higher measures of many processes of care but only 1 intermediate outcome and 1 medication management outcome. Implications The disease management strategies improved processes of care but not outcomes. Experts in quality improvement may need to refocus their efforts. The Editors Persons with diabetes continue to receive suboptimal care (16). To improve quality, many health systems have implemented disease management programs for diabetes and other chronic conditions (79). These programs typically incorporate population-based strategies, such as disease registries, clinical guidelines, performance feedback, physician reminders, self-management support for patients, and targeted case management for high-risk patients (10). Evidence for the effectiveness of disease management comes primarily from small efficacy trials (1020). Such studies consistently found improved processes of diabetes care; however, improvements in outcomes (such as control of cardiovascular disease risk factors) were less consistent (12, 17, 18, 2022). Furthermore, most studies evaluated only 1 or 2 strategies (instead of multicomponent programs) in selected clinical settings. It is unclear how well findings from these smaller studies apply to entire patient populations. Many components of disease management focus on improving processes of care. Early performance measurement projects, such as the Health Plan Employer Data Information System (23) and the Diabetes Quality Improvement Program (5), emphasized the importance of such processes as annual retinal screening or hemoglobin A1c determination. Particularly for health plans, process measures are more readily available than are outcomes data. However, if disease management is to improve patient outcomes, it must also improve intermediate outcomes, such as hemoglobin A1c levels, systolic blood pressure, and serum low-density lipoprotein (LDL) cholesterol levels. Translating Research into Action for Diabetes (TRIAD) (24) is a multicenter study of diabetes care in managed care. The TRIAD studys central hypothesis is that health care systems features can affect quality of care. Here, we examine how 3 disease management strategies vary in intensity across physician groups and whether physician groups with more intensive disease management have higher quality of diabetes care. We assess quality by processes of care, by levels of intermediate outcomes, and by current clinical management of these outcomes. Methods Overview of the TRIAD Study and Sample The TRIAD studys sampling frame, methods, key hypotheses, and power calculations are detailed elsewhere (24). The study comprised 6 collaborating translational research centers that were partnered with 10 managed care health plans in 7 states. Of the 10 plans, 7 contracted with 1 to 26 physician groups (total, 68 groups), whereas 4 plans directly contracted with individual physicians. A standard algorithm was applied to automated pharmacy, laboratory utilization, and inpatient and outpatient diagnostic data (25) to identify all community-dwelling patients with diabetes who were 18 years of age and older and who had been continuously enrolled in the TRIAD health plan for at least 18 months. The study cohort was randomly sampled from this population. Sampled patients were recruited between July 2000 and October 2001 by using computer-assisted telephone interviews or written surveys that were conducted in English or Spanish. Eligibility was confirmed if patients verified that they had had diabetes for at least 12 months and had received most of their diabetes care through the TRIAD health plan. Permission was sought from all respondents to request copies of their outpatient medical records for the previous 18 months. All health plan and physician group directors received mailed surveys (Appendix Figure) during the same interval. Face-to-face or telephone interviews were used to complete and clarify responses. Each director was offered

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

100 for completing the survey. Appendix Figure. Translating Research into Action for Diabetes (TRIAD) Physician Group Survey. The TRIAD study was reviewed and approved by the institutional review boards of each research center and by the Centers for Disease Control and Prevention (CDC). Informed consent was obtained from all survey respondents. Data Sources Patient surveys included questions on health status, diabetes duration, current diabetes treatment, and demographic characteristics. Of 13086 contacted and eligible persons, 11927 (91%) completed the survey (56.6% by computer-assisted telephone interview and 43.4% by written survey) (Figure). We were unable to contact many individuals. Using a practice that is endorsed by the Council of American Survey Research Organizations (26), we assumed that persons whom we could not contact or for whom we could not confirm eligibility had the same eligibility rate as those contacted. Under that assumption, the response rate was 69%. Figure. Description of sampling and response rate. xx Of 11927 patients who completed a survey, 8661 (73%) consented to medical record review and subsequently had charts available for review. Centrally trained reviewers used standardized data collection software to abstract process measures, most recent levels of hemoglobin A1c, upper limits of normal for hemoglobin A1c measurements that were recorded, serum LDL cholesterol levels, systolic blood pressure, current medications, and comorbid conditions. Interrater reliability () for the main quality measures ranged from 0.86 to 0.94. All 10 health plan directors and 52 of 68 physician group directors completed surveys. Surveys assessed organizational age, size, structure, profit status, insurance products, contracting arrangements, history of involvement with managed care, and detailed information on the organizations use of diabetes disease management strategies. Of the physician groups that did not respond (443 participants), 11 existed solely for the purpose of contracting with plans and had no diabetes disease management. These physician groups were assumed to have no care management strategies and were included in the analyses, as were patient groups (1150 participants) from the 4 health plans that contracted directly with physicians. The remaining 5 groups (159 participants) did not respond and were excluded from analyses (Figure). Consequently, the resulting sample included a total of 8661 survey respondents with charts available for review and data from 63 physician groups and 4 additional health plans (Figure). Mean duration of diabetes, body mass index, and health status did not meaningfully differ between persons whose medical records and physician group variables were available to the study team and those whose records were unavailable. Predictors, End Points, and Covariates The primary predictors were 3 measures of the intensity of disease management strategies: physician reminders, performance feedback, and structured care. These were calculated for physician groups and health plans from multiple survey items. A detailed description of the methods used to calculate composite intensity scores is provided in Appendix 2. Selected item-level responses for physician groups in the most intense versus least intense tercile of each strategy are displayed in Table 1. Table 1. Selected Item-Level Responses for Provider Groups for Each Disease Management Strategy* The physician reminders intensity score was derived from 2 questions, which detailed the types and content of the reminders physicians received. Groups whose use of reminders represented the upper tercile of intensity were found to have reminded physicians about 4 care processes on average. Most groups in the upper tercile delivered reminders electronically at the point of care. Performance feedback intensity was obtained by tallying responses to a checklist of possible diabetes process and outcome feedback items. A total of 86% and 82% of groups in the upper tercile included levels of hemoglobin A1c and serum LDL cholesterol, respectively, in feedback to physicians (Table 1). Physician feedback focused on many of the same elements of care as reminders. The use of formal case management, diabetes guidelines, patient reminders, and diabetes education correlated highly in physician groups (Pearson correlation coefficients ranged from 0.63 to 0.88); therefore, we could not look at these approaches independently. Consequently, we combined the 4 approaches into a single composite score for structured diabetes care management. Use of formal case management was assessed by the proportion of patients with diabetes who were enrolled, the number of case managers per 10000 patients, the extent to which the program targeted high-risk patients, and a checklist of case management activities. The clinical guidelines were scored to reflect the extent of implementation. The highest score was assigned to physician groups that incorporated guidelines into automated physician or patient reminders. Patient reminder intensity incorporated the number, type, and frequency of reminders sent. On average, physician groups in the upper tercile had diabetes education as a covered benefit, whereas those in the lowest tercile generally did not have these programs. Because of the differing numbers of questions and wide range of possible values within each intensity score, each question was z-transformed to a mean of 0.0 and standard deviation near or equal to 1.0 to facilitate comparison. Sco

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

OBJECTIVE: 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. METHODS: Analyses included 185 adolescent participants with recently diagnosed type 1 diabetes in the SEARCH for Diabetes in Youth Study with pediatric care at baseline who were age ≥18 years at follow-up. Demographic and clinical factors were measured by survey and laboratory results. Survival analysis was used to estimate the age of transition. Logistic regression analysis assessed the association of demographic and clinical factors with the transition of care and poor glycemic control at follow-up. RESULTS: Fifty-seven percent of participants had transitioned to adult diabetes care providers by the follow-up visit. The estimated median age of transition of care was 20.1 years (95% confidence interval 19.8–20.4). Older age, lower baseline glycosylated hemoglobin, and less parental education were independently associated with increased odds of transition. The odds of poor glycemic control at follow-up were 2.5 times higher for participants who transitioned to adult care compared with those who remained in pediatric care. CONCLUSIONS: Transferring from pediatric to adult care, experienced by more than half the sample, was associated with an increased risk of poor glycemic control at follow-up. These findings suggest that young adults need additional support when moving to adult care.

Type 1 and Type 2 Diabetes in Asian and Pacific Islander U.S. Youth: The SEARCH for Diabetes in Youth 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.

Health-related quality of life of children and adolescents with type 1 or type 2 diabetes mellitus: SEARCH for Diabetes in Youth Study.

OBJECTIVE—Given limited reports on diabetes among U.S. Asian and Pacific Islander youth, we describe the clinical characteristics, incidence, and prevalence of diabetes among Asian, Pacific Islander, and mixed Asian–Pacific Islander youth. RESEARCH DESIGN AND METHODS—Data were collected from 245 Asian, Pacific Islander, and Asian–Pacific Islander participants in the SEARCH for Diabetes in Youth Study, a population-based study of diabetes in youth (aged <20 years). Additionally, we estimated the incidence and prevalence of type 1 and type 2 diabetes for Asian, Pacific Islander, and Asian–Pacific Islander youth combined. RESULTS—Most participants with type 2 diabetes were obese (range Asian 71% to Pacific Islander 100%) with mean BMI >33 kg/m2. In those with type 1 diabetes, Pacific Islanders were more likely to be obese, with a mean BMI of 26 vs. 20 kg/m2 for Asian and Asian–Pacific Islander youth (P < 0.0001). The incidence of type 1 diabetes for youth aged 0–9 years was 6.4 per 100,000 person-years and 7.4 per 100,000 person-years for youth aged 10–19 years. The incidence of type 2 diabetes was 12.1 per 100,000 person-years for youth aged 10–19 years. CONCLUSIONS—While Asian and Asian–Pacific Islanders with type 1 and type 2 diabetes had lower mean BMIs than Pacific Islanders, all Asian, Pacific Islander, and Asian–Pacific Islanders with type 2 diabetes had mean BMIs above adult ethnicity-specific definitions of obesity. While the majority of Asian, Pacific Islander, and Asian–Pacific Islander youth had type 1 diabetes, older Asian, Pacific Islander, and Asian–Pacific Islander youth (aged 10–19 years) have an incidence of type 2 diabetes almost double that of type 1 diabetes. Public health efforts to prevent type 2 diabetes and obesity in Asian, Pacific Islander, and Asian–Pacific Islander adolescents are needed.

Health behaviors and quality of care among Latinos with diabetes in managed care.

OBJECTIVE To examine the associations between demographic and diabetes management variables and the health-related quality of life (HRQOL) of youths with type 1 or type 2 diabetes mellitus (DM). DESIGN Cross-sectional study. SETTINGS Selected populations in Ohio, Washington, South Carolina, Colorado, Hawaii, and California; health service beneficiaries in 3 American Indian populations; and participants in the Pima Indian Study in Arizona. PARTICIPANTS Two thousand four hundred forty-five participants aged 8 to 22 years in the SEARCH for Diabetes in Youth Study. MAIN OUTCOME MEASURE Pediatric Quality of Life Inventory scores. RESULTS Among youths with type 2 DM, HRQOL was lower compared with those with type 1. Among those with type 1 DM, worse HRQOL was associated with a primary insurance source of Medicaid or another government-funded insurance, use of insulin injections vs an insulin pump, a hemoglobin A(1c) value of at least 9%, and more comorbidities and diabetes complications. There was a significant age x sex interaction, such that, in older groups, HRQOL was lower for girls but higher for boys. For youths with type 2 DM, injecting insulin at least 3 times a day compared with using an oral or no diabetes medication was associated with better HRQOL, and having 2 or more emergency department visits in the past 6 months was associated with worse HRQOL. CONCLUSIONS Youths with types 1 and 2 DM reported HRQOL differences by type of treatment and complications. The significant age x sex interaction suggests that interventions to improve HRQOL should consider gender differences in diabetes adjustment and management in different age groups.

Prevalence and Correlates of Elevated Blood Pressure in Youth with Diabetes Mellitus: The Search for Diabetes in Youth Study

OBJECTIVES We evaluated whether ethnicity and language are associated with diabetes care for Latinos in managed care. METHODS Using data from 4685 individuals in the Translating Research Into Action for Diabetes (TRIAD) Study, a multicenter study of diabetes care in managed care, we constructed multivariate regression models to compare health behaviors, processes of care, and intermediate outcomes for Whites and English- and Spanish-speaking Latinos. RESULTS Latinos had lower rates of self-monitoring of blood glucose and worse glycemic control than did Whites, higher rates of foot self-care and dilated-eye examinations, and comparable rates of other processes and intermediate outcomes of care. CONCLUSIONS Although self-management and quality of care are comparable for Latinos and Whites with diabetes, important ethnic disparities persist in the managed care settings studied.