David G. Marrero

Translating the Diabetes Prevention Program into the Community The DEPLOY Pilot Study

BACKGROUND The Diabetes Prevention Program (DPP) found that an intensive lifestyle intervention can reduce the development of diabetes by more than half in adults with prediabetes, but there is little information about the feasibility of offering such an intervention in community settings. This study evaluated the delivery of a group-based DPP lifestyle intervention in partnership with the YMCA. METHODS This pilot cluster-randomized trial was designed to compare group-based DPP lifestyle intervention delivery by the YMCA to brief counseling alone (control) in adults who attended a diabetes risk-screening event at one of two semi-urban YMCA facilities and who had a BMI>or=24 kg/m2, >or=2 diabetes risk factors, and a random capillary blood glucose of 110-199 mg/dL. Multivariate regression was used to compare between-group differences in changes in body weight, blood pressures, HbA1c, total cholesterol, and HDL-cholesterol after 6 and 12 months. RESULTS Among 92 participants, controls were more often women (61% vs 50%) and of nonwhite race (29% vs 7%). After 6 months, body weight decreased by 6.0% (95% CI=4.7, 7.3) in intervention participants and 2.0% (95% CI=0.6, 3.3) in controls (p<0.001; difference between groups). Intervention participants also had greater changes in total cholesterol (-22 mg/dL vs +6 mg/dL controls; p<0.001). These differences were sustained after 12 months, and adjustment for differences in race and gender did not alter these findings. With only two matched YMCA sites, it was not possible to adjust for potential clustering by site. CONCLUSIONS The YMCA may be a promising channel for wide-scale dissemination of a low-cost approach to lifestyle diabetes prevention.

Adapting the Diabetes Prevention Program Lifestyle Intervention for Delivery in the Community The YMCA Model

The Diabetes Prevention Program (DPP) demonstrated that a structured diet and physical activity intervention that achieves and maintains modest weight loss for over-weight adults with impaired glucose tolerance can significantly reduce the development of diabetes. Although tens of millions of American adults could benefit from access to the DPP lifestyle intervention, there currently is no available model for nationwide dissemination of this highly beneficial and cost-effective approach to diabetes prevention. In this article, the authors describe the evolution of adaptations to improve DPP lifestyle intervention implementation and dissemination by a strong community partner, the YMCA. They also provide information about early field research and an ongoing clinical trial that will provide information about the feasibility and effectiveness of applying this new model on a national scale.

Barriers to Insulin Initiation The Translating Research Into Action for Diabetes Insulin Starts Project

OBJECTIVE Reasons for failing to initiate prescribed insulin (primary nonadherence) are poorly understood. We investigated barriers to insulin initiation following a new prescription. RESEARCH DESIGN AND METHODS We surveyed insulin-naïve patients with poorly controlled type 2 diabetes, already treated with two or more oral agents who were recently prescribed insulin. We compared responses for respondents prescribed, but never initiating, insulin (n = 69) with those dispensed insulin (n = 100). RESULTS Subjects failing to initiate prescribed insulin commonly reported misconceptions regarding insulin risk (35% believed that insulin causes blindness, renal failure, amputations, heart attacks, strokes, or early death), plans to instead work harder on behavioral goals, sense of personal failure, low self-efficacy, injection phobia, hypoglycemia concerns, negative impact on social life and job, inadequate health literacy, health care provider inadequately explaining risks/benefits, and limited insulin self-management training. CONCLUSIONS Primary adherence for insulin may be improved through better provider communication regarding risks, shared decision making, and insulin self-management training.

The prevention of type 2 diabetes

Type 2 diabetes mellitus (T2DM) affects more than 7% of adults in the US and leads to substantial personal and economic burden. In prediabetic states insulin secretion and action—potential targets of preventive interventions—are impaired. In trials lifestyle modification (i.e. weight loss and exercise) has proven effective in preventing incident T2DM in high-risk groups, although weight loss has the greatest effect. Various medications (e.g. metformin, thiazolidinediones and acarbose) can also prevent or delay T2DM. Whether diabetes-prevention strategies also ultimately prevent the development of diabetic vascular complications is unknown, but cardiovascular risk factors are favorably affected. Preventive strategies that can be implemented in routine clinical settings have been developed and evaluated. Widespread application has, however, been limited by local financial considerations, even though cost-effectiveness might be achieved at the population level.

The diabetes prevention program: Recruitment methods and results

The Diabetes Prevention Program (DPP) is a multicenter randomized controlled trial designed to test whether diet and exercise or medication can prevent or delay the onset of type 2 diabetes in persons with impaired glucose tolerance, who are at increased risk of the disease. This paper describes DPP recruitment methods, strategies, performance, and costs. The DPP developed an organizational structure for comprehensive management and continuous monitoring of recruitment efforts. The DPP utilized a variety of recruitment strategies, alone or in combination, and a stepped informed consent procedure leading to randomization. Studywide and clinic-specific recruitment data were monitored, analyzed, and used to modify recruitment approaches. DPP recruitment was completed slightly ahead of schedule, meeting goals for the proportion of women enrolled and nearly meeting goals for the proportion of racial/ethnic minorities. Clinics varied widely in the recruitment strategies they used, and these strategies also varied by participant age, gender, and race/ethnicity. Staff time devoted to recruitment averaged 86.8 hours per week per clinic, with the majority of effort by staff specifically assigned to recruitment. The number of staff hours required to recruit a participant varied by recruitment strategy. Recruitment cost (excluding staff cost) was about 1075 US dollars per randomized participant. The DPP experience offers lessons for those planning similar efforts: (1) a method for ongoing assessment and revision of recruitment strategies is valuable; (2) a range of recruitment strategies may be useful; (3) the most effective methods for recruiting potential subjects may vary according to the gender, age, and race/ethnicity of those individuals; (4) recruitment strategies vary in the amount of staff time required to randomize a participant; and (5) a stepped screening may make it easier to identify and recruit volunteers who understand the requirements of the study.

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

Sex Disparities in Control and Treatment of Modifiable Cardiovascular Disease Risk Factors Among Patients With Diabetes: Translating Research Into Action for Diabetes (TRIAD) Study

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

Development and Validation of the Insulin Treatment Satisfaction Questionnaire

OBJECTIVE—Cardiovascular disease (CVD) mortality has decreased in men but not in women with diabetes. We investigated whether sex differences in control and treatment of CVD risk factors might underlie this disparity. RESEARCH DESIGN AND METHODS—We performed cross-sectional analyses from a cohort of patients with diabetes sampled from 10 U.S. managed care health plans. Study end points included not being in control for CVD risk factors (≥140 mmHg for systolic blood pressure [SBP], ≥3.35 mmol/l for LDL cholesterol, and ≥8.0% for A1C) and the intensity of medication management (number of medication classes) for patients not in control. Logistic regression models with random intercepts were used to adjust probabilities of control and management for demographics, clinical characteristics, and clustering within health plans. RESULTS—There were 1,315 women and 1,575 men with a history of CVD and 3,415 women and 2,516 men without a history of CVD. Among patients with CVD, adjusted estimated probabilities for not being in control and risk differences varied significantly between men and women for SBP (men 41.2%, women 46.6%; risk difference −5.4% [95% CI −9.5 to −1.3]) and LDL cholesterol (men 22.4%, women 28.3%; risk difference −5.9% [−9.9 to −1.8]). There were no significant sex differences in intensity of medication management for patients not in control. In patients without CVD there were no significant differences in control or intensity of medication management. CONCLUSIONS—In diabetic patients with CVD, poorer control of SBP and LDL cholesterol for women may contribute to the sex disparity in CVD mortality trends.

Fear of Hypoglycemia in the Parents of Children and Adolescents With Diabetes: Maladaptive or Healthy Response?

BACKGROUND Treatment of diabetes mellitus (DM) is complex, requiring multifaceted lifestyle change or regulation and, for many, self-regulation of insulin levels in the blood. Historically, daily insulin treatment has been viewed as burdensome to patients, prompting newer formulations and improved delivery methods. OBJECTIVE This multicenter, clinical study was designed to develop a conceptually sound, clinically meaningful, and psychometrically valid measure of insulin treatment satisfaction, applicable to a wide range of insulin therapies. METHODS A 3-phase iterative process was employed to develop and validate the Insulin Treatment Satisfaction Questionnaire (ITSQ): (1) conceptual development of items, (2) preliminary validation among patients with DM, and (3) confirmatory validation among patients with DM. RESULTS The ITSQ was validated with 170 patients in phase 2 and 402 patients in phase 3. Confirmatory factor analysis produced a 5-factor, 22-item instrument assessing regimen inconvenience, lifestyle flexibility, glycemic control, hypoglycemic control, and satisfaction with the insulin delivery device. Results for reliability and construct validity of the final version were consistent in both samples of patients treated with insulin, with different data collection methods. Internal consistency (using Cronbach alpha coefficient) of the subscales ranged from 0.79 to 0.91. Test-retest reliability (using Spearman rank correlation coefficients) ranged from 0.63 to 0.94. ITSQ scores showed moderate to high correlation with related measures of treatment burden. The ITSQ differentiated among insulin delivery methods, glycosylated hemoglobin values, the number of times the patient required assistance administering insulin, and insulin adherence. CONCLUSION In our study samples, the ITSQ appeared to be conceptually and psychometrically sound and applicable to a wide range of insulin therapies.

Twenty-First Century Behavioral Medicine: A Context for Empowering Clinicians and Patients With Diabetes A consensus report

Sixty-one parents of children with insulin-dependent diabetes mellitus completed modified versions of the Hypoglycemic Fear Survey (HFS) and the Diabetes Quality of Life (DQOL) scale. They also indicated their childs history ofhypoglycemic related seizures or loss of consciousness (SLC) events. Parental HFS scores were significantly greater if their child had ever experienced a SLC event or experienced a SLC event within the past year. Parental HFS scores were positively correlated with general parental worry about their child having diabetes. Adolescent children who experienced a SLC event during the past year reported greater HFS scores, greater general worry about diabetes, and a greater negative impact of having diabetes compared with adolescents with no such history. Despite the greater fear of hypoglycemia in prrrents and adolescents, there was no significant difference in HbA 1 values between children with or without any history of SLC events or children with or without a SLC event within the past year.