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The American Journal of Managed Care February 2013
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Are Benefits From Diabetes Self-Management Education Sustained?
JoAnn Sperl-Hillen, MD; Sarah Beaton, PhD; Omar Fernandes, MPH; Ann Von Worley, RN, BSHS, CCRP; Gabriela Vazquez-Benitez, PhD, MSc; Ann Hanson, BS; Jodi Lavin-Tompkins, RN, CNP, CDE, BC-ADM; William Parsons, MS; Kenneth Adams, PhD; and C. Victor Spain, DVM, PhD
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Are Benefits From Diabetes Self-Management Education Sustained?

JoAnn Sperl-Hillen, MD; Sarah Beaton, PhD; Omar Fernandes, MPH; Ann Von Worley, RN, BSHS, CCRP; Gabriela Vazquez-Benitez, PhD, MSc; Ann Hanson, BS; Jodi Lavin-Tompkins, RN, CNP, CDE, BC-ADM; William Parsons, MS; Kenneth Adams, PhD; and C. Victor Spain, DVM, PhD
Conventional individualized diabetes self-management education resulted in sustained improvement in self-efficacy and diabetes distress. Short-term improvements in A1C, nutrition, and physical activity were not sustained.
Objectives: To evaluate whether outcomes from diabetes self-management education for patients with suboptimal control were sustained.


Study Design: A randomized controlled trial of 623 adults with type 2 diabetes and glycated hemoglobin (A1C) >7% assigned to receive conventional individual education (IE), group education (GE) using US Diabetes Conversation Maps, or usual care (UC) with no education.


Methods: A1C tests, Problem Areas in Diabetes (PAID), Diabetes Self-Efficacy (DES), Recommended Food Score (RFS), physical activity, and medication use were quantified at baseline and 1 year of follow-up through electronic health records and quarterly mailed surveys. Short-term (mean 6.8 months) and long-term (12.8 months) outcomes were evaluated using linear mixed models. In addition, follow-up trajectories were plotted in a random effects generalized additive model with smooth splines.


Results: Compared with UC, IE resulted in longterm improved DES and PAID scores (DES, +.11, P = .03 and PAID, –2.94, P = .04), but not significantly improved long-term RFS or physical activity change. The A1C trajectory declined more steeply in IE than GE and UC for the first 150 days post randomization. However, by 250 days, there was no treatment group A1C difference. The model fit likelihood ratio test for A1C intervention trends was significant for 3 distinct non-linear trajectories (P = .02).


Conclusions: Conventional IE (but not GE) resulted in significant and sustained improvements in self-efficacy and reduced diabetes distress compared with UC, but short-term improvements in A1C, nutrition, and physical activity were not sustained. Patients may need ongoing reinforcement to achieve lasting behavioral change and glucose control.


(Am J Manag Care. 2013;19(2):104-112)
The study adds to the current literature on diabetes self-management education (DSME) by evaluating and demonstrating sustained improvement of patient-centered outcomes (self-efficacy and distress) for patients with suboptimally controlled diabetes of long duration. It informs healthcare reform in the following ways:
 
  •  Improvements in such patient-centered outcomes support referral to diabetes educators and reimbursement of conventional DSME for patients with suboptimal control of diabetes (glycated hemoglobin >7%).
 
  • Ongoing reinforcement may be needed to more fully realize the impact of diabetes education and to yield sustainable improvements in nutrition, exercise, and blood sugar control.
Many patients with diabetes have not achieved their optimal care goals and have difficulty following recommendations for self-management.1 A better understanding of how to help these patients improve and sustain self-management behaviors is important to overcoming the public health and cost concerns related to the increasing prevalence of diabetes in our population.2

Studies of outcomes related to diabetes self-management education (DSME) have shown mixed results, and a 2007 meta-analysis rated most studies on the topic as poor to moderate in quality.3 More recently published research has been judged of higher quality due to masking of outcome assessments, fewer numbers of subjects lost to follow-up, and analysis by intent-to-treat.4 These studies suggest that educational interventions that more strongly incorporate individual goal-setting and tailored behavioral change strategies, whether delivered in an individual or group setting, most successfully help patients improve blood sugar control in the short term (up to 6 months of follow-up).5,6 However, a large meta-analysis of the effect of self-management education on longer-term glycemic control showed that the glycated hemoglobin (A1C) effect from DSME was not sustained after 4 months.7 More research is needed to evaluate the effect of educational strategies on more long-term outcomes and on medication use.5,6

The Journey for Control of Diabetes Interactive Dialogue to Educate and Activate (IDEA) study was a randomized controlled trial that compared methods of individual education (IE) and group education (GE) with usual care (UC) in patients with relatively long-standing diabetes (mean duration, 11 years) and suboptimal control (mean A1C, 8.3%). Previously published short-term results (ie, about 6 months) demonstrated that subjects randomized to IE, but not GE, had improvement in psychosocial outcomes as well as glucose control and behavioral outcomes.5 In this analysis, we hypothesized these IE improvements would be sustained after a year of follow-up compared with the UC group, and that there would be no significant change in outcomes for the GE subjects after a year of follow-up.

METHODS

The study was reviewed in advance, approved, and monitored on an ongoing basis by the HealthPartners (HP) Institutional Review Board and Ethical and Independent Review Services, and registered at clinicaltrials. gov NCT00652509.

Study Population

Between 2008 and 2009, the study enrolled 623 patients from ABQ Health Partners in Albuquerque, New Mexico, and HP Clinics in Minneapolis, Minnesota, who met the eligibility criteria of type 2 diabetes and an A1C result of >7% in the last 6 months.8 Potentially eligible subjects were mailed a letter of invitation to participate and offered gift cards worth $50 for completing the baseline and enrollment visit and $25 for each of 4 mailed follow-up surveys. Consented subjects were randomly assigned to GE, IE, or UC using a random allocation sequence in a 2:2:1 ratio. Patients were scheduled for all of their IE and GE sessions at the enrollment visit but could call to reschedule at any time during the intervention period. See Figure 1 for the IDEA Study design and CONSORT (Consolidated Standards of Reporting Trials) patient flow. A1C outcomes of the non-enrolled (NE) population, consisting of 7977 patients who received letters of invitation to participate in the study but did not enroll, were also tracked.

Interventions

The IE intervention consisted of three 1-hour individual sessions spaced approximately 1 month apart and were delivered by either nurse or dietitian certified diabetes educators using the conventional method of the care system (the accredited education method used for members not enrolled in the study and reimbursable by Medicare). The first session included an assessment of patient needs pertaining to American Association of Diabetes Educators (AADE)-recommended content9 for 7 self-care behaviors (healthy eating, monitoring blood sugars, taking medications, problem solving, risk reduction, healthy coping, and being active). Follow-up sessions

focused on the patient’s individual concerns, reviewed selfmonitored blood sugars, and evaluated progress toward treatment targets. The sessions were intended to help the patient develop personalized behavioral modification goals needed to achieve care targets.

The GE intervention consisted of four 2-hour sessions scheduled 1 week apart delivered by the same certified diabetes educators (nurses and dietitians) using the US Diabetes Conversation Map program endorsed by the American Diabetes Association (ADA).10 The program was a non-didactic group approach that promoted patient interaction and was intended to help patients overcome barriers to self-management and to improve self-efficacy.11 Conversation Map programs are currently being used in an estimated 105 countries in 34 different languages.10 The content also meets the requirements for ADA diabetes education program accreditation, but currently a comprehensive program of this length is reimbursable by Medicare only in the first year of diagnosis and so was considered non-conventional for patients such as IDEA with a longer duration of diabetes. The study educators received expert training on the Conversation Map program, and a fidelity check of the interventions included high mean scores on facilitator self ratings as well as high patient satisfaction scores after each session.5,12

The UC group was not assigned any educational intervention throughout the study. The study did not prohibit selfmanagement education recommended by usual providers or sought by the study subjects.

Data Collection

All study subjects received surveys at the baseline visit and by mail at 1, 4, 7, and 10 months after the last scheduled educational intervention. For the UC group, a proxy date for the last scheduled intervention was calculated using the mean value of IE and GE intervention subjects. Survey outcome variables for this analysis were obtained from validated instruments that were previously defined and demonstrated to be responsive in the short-term results.5 These variables are described in Table 1.13-18

A1C values and measurement dates for all study subjects and the NE population were collected through passive surveillance of laboratory results contained in the electronic health record (EHR). A1C tests were analyzed at one of 2 accredited clinical laboratories using standard high-pressure liquid chromatography assay methods with a coefficient of variation (CV) of 1.14% at an A1C of 7.5% (HP Clinics) and a CV of 0.82% at an A1C of 6.2% (ABQ Health Partners). All A1C data were collected and retained for subjects for 6 months before the baseline randomization date and for 12.8 months post-randomization. The periods between the last scheduled educational session and the second survey mailing date (4 months after the last scheduled educational session) and fourth survey mailing date (10 months after the last scheduled educational session) were used to determine the short- and long-term follow-up intervals for A1C, equating to a mean of 6.8 months and 12.8 months of follow-up from the baseline visit.5 For the non-enrolled study population, a “baseline date” was imputed from the screening and baseline visit time patterns observed for consented subjects.

Medication data were obtained through surveillance of medical claims on the subset of subjects (n = 488, 78%) with health plan pharmacy coverage through the research-delivery organizations. Medication use was determined for 5 classes of glycemic medications (insulins, biguanides, sulfonylureas, dipeptidyl peptidase-4 [DPP4] inhibitors, and glucagon-like peptide [GLP1] agonists) at three 6-month measurement periods: 6 months prior to enrollment (baseline), the first 6 months after enrollment (short-term follow-up), and 6 to 12 months after enrollment (long-term follow-up). Medication use was defined as having any claim for a drug in that class in the measurement period. The number of drug classes used by the patient was tallied for each patient by measurement period. Medication intensification was defined in the short-term and long-term follow-up periods as an increase in the total number of drug classes, or newly identified insulin use, compared with the baseline period.

Additionally, the study tracked the number of diabetes education visits as a secondary outcome through claims data using patient visit codes for educational services. The variable was the sum of the number of visits obtained outside of the assigned study sessions from the baseline date to the end of the short-term and long-term follow-up measurement periods.

Analysis

The purpose of this analysis was to evaluate the effects of diabetes education of IDEA study subjects on glycemic control, psychosocial and behavioral outcomes, and medication use over a follow-up period of approximately 1 year. All statistical analyses were conducted with SAS version 9.2 software (Cary, North Carolina) and R 2.13.0.19 Study outcome trajectories were analyzed using a general linear mixed model for all normally distributed continuous variables (A1C, PAID, DES, RFS). A1C was log-transformed in the analysis and then retransformed back to its original scale (presented as geometric means). A generalized linear model with binomial distribution applying the generalized estimating equation (GEE) method was used to analyze the proportion of subjects meeting A1C control criteria, participating in moderate physical activity, and receiving medication intensification. Mean counts of medication classes and number of education encounters outside the intervention correspond to geometric means estimated with a generalized linear model with Poisson distribution. Pair-wise comparisons between intervention groups correspond to the ratio of the estimated geometric means.

Covariates included in the models were baseline A1C, age, study site, and duration of diabetes. Additional covariates were included specific to each model. Intervention effects for survey outcomes were tested using the second and fourth follow- up survey results. Intervention effects for A1C were tested using the A1C with the latest date collected in previously defined short-term and long-term follow-up intervals after randomization. Missing values for A1C and survey outcomes in the measurement period of interest were assigned the latest known result (eg, the baseline value if no subsequent datawere collected). Pair-wise comparisons of changes from baseline for GE and IE were conducted in relation to UC.

An additional analytic approach evaluated cross-sectional comparisons plotted with 95% confidence interval (CI) at baseline, and follow-up surveys (1, 4, 7, and 10 months after the last scheduled educational intervention). A generalized additive linear mixed model was used to produce a smooth function of A1C trajectory according to intervention group, using all A1C repeated measures occurring from 30 days before randomization date to 385 days after. The pre-intervention trend line before 30 days was eliminated due to increasingly scarce data points that could overly influence the A1C trajectory and limit valid interpretation. Differences in trajectories between intervention treatment groups were assessed using a likelihood ratio test (LR-T).

RESULTS

 
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