Making Inroads in Addressing Population Health in Underserved Communities With Type 2 Diabetes

Multisite Quality Improvement Program Within the Project ECHO Diabetes Remote Network

BACKGROUND

The telementoring Project ECHO (Extension for Community Healthcare Outcomes) model has been shown to improve disease management in diabetes in many underserved communities. The authors aim to evaluate if ECHO could also be an effective tool for quality improvement (QI) of diabetes care in these communities.

METHODS

Thirteen clinics in underserved communities in California and Florida participating in Project ECHO Diabetes were recruited for a 12-month QI program. The program provided weekly tele-education sessions, including a didactic presentation and case-based discussion. In addition, clinics chose their own set of quality measures to improve and met remotely to discuss their efforts, successes, and setbacks every quarter with mentorship from QI experts.

RESULTS

Of the 31 QI initiatives attempted by different clinics, all had either made improvements (25 initiatives, 80.6%) or were in the process of making improvements (6 initiatives, 19.4%) in structural, process, and outcome measures. Examples of these measures include whether clinics have protocols to identify high-risk patients (structure), numbers of continuous glucose monitor prescriptions submitted by the clinics (process), and percentage of patients with diabetes whose most recent HbA1c are > 9% (outcome). For one measure, 40.0% of the clinics had achieved a higher percentage of cumulative HbA1c measurement in the third quarter of the year, compared to the fourth quarter in the previous year. The cost of QI implementation varied widely due to different number of personnel involved across sites.

CONCLUSION

A QI program delivered via Project ECHO Diabetes can facilitate quality improvements in underserved communities.

Benefits of Electronic Consultations in Improving Diabetes Care Within a Safety-Net Health System

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes. The following article describes an initiative aimed at improving access to diabetes specialty care for patients within a safety-net health system in Dallas County, TX, through the implementation of electronic consultations.

The sonographic quantitative assessment of the deltoid muscle to detect type 2 diabetes mellitus: a potential noninvasive and sensitive screening method?

BACKGROUND

In our previous published study, we demonstrated that a qualitatively assessed elevation in deltoid muscle echogenicity on ultrasound was both sensitive for and a strong predictor of a type 2 diabetes (T2DM) diagnosis. This study aims to evaluate if a sonographic quantitative assessment of the deltoid muscle can be used to detect T2DM.

METHODS

Deltoid muscle ultrasound images from 124 patients were stored: 31 obese T2DM, 31 non-obese T2DM, 31 obese non-T2DM and 31 non-obese non-T2DM. Images were independently reviewed by 3 musculoskeletal radiologists, blinded to the patient's category. Each measured the grayscale pixel intensity of the deltoid muscle and humeral cortex to calculate a muscle/bone ratio for each patient. Following a 3-week delay, the 3 radiologists independently repeated measurements on a randomly selected 40 subjects. Ratios, age, gender, race, body mass index, insulin usage and hemoglobin A_1c were analyzed. The difference among the 4 groups was compared using analysis of variance or chi-square tests. Both univariate and multivariate linear mixed models were performed. Multivariate mixed-effects regression models were used, adjusting for demographic and clinical variables. Post hoc comparisons were done with Bonferroni adjustments to identify any differences between groups. The sample size achieved 90% power. Sensitivity and specificity were calculated based on set threshold ratios. Both intra- and inter-radiologist variability or agreement were assessed.

RESULTS

A statistically significant difference in muscle/bone ratios between the groups was identified with the average ratios as follows: obese T2DM, 0.54 (P < 0.001); non-obese T2DM, 0.48 (P < 0.001); obese non-T2DM, 0.42 (P = 0.03); and non-obese non-T2DM, 0.35. There was excellent inter-observer agreement (intraclass correlation coefficient 0.87) and excellent intra-observer agreements (intraclass correlation coefficient 0.92, 0.95 and 0.94). Using threshold ratios, the sensitivity for detecting T2DM was 80% (95% CI 67% to 88%) with a specificity of 63% (95% CI 50% to 75%).

CONCLUSIONS

The sonographic quantitative assessment of the deltoid muscle by ultrasound is sensitive and accurate for the detection of T2DM. Following further studies, this process could translate into a dedicated, simple and noninvasive screening method to detect T2DM with the prospects of identifying even a fraction of the undiagnosed persons worldwide. This could prove especially beneficial in screening of underserved and underrepresented communities.

Impact of Quality Improvement (QI) Program on 5-Year Risk of Diabetes-Related Complications: A Simulation Study

OBJECTIVE

We successfully implemented the American Diabetes Association's (ADA) Diabetes INSIDE (INspiring System Improvement with Data-Driven Excellence) quality improvement (QI) program at a university hospital and safety-net health system (Tulane and Parkland), focused on system-wide improvement in poorly controlled type 2 diabetes (HbA1c >8.0% [64 mmol/mol]). In this study, we estimated the 5-year risk reduction in complications and mortality associated with the QI program.

RESEARCH DESIGN AND METHODS

The QI implementation period was 1 year, followed by the postintervention period of 6 months to evaluate the impact of QI on clinical measures. We measured the differences between the baseline and postintervention clinical outcomes in 2,429 individuals with HbA1c >8% (64 mmol/mol) at baseline and used the Building, Relating, Assessing, and Validating Outcomes (BRAVO) diabetes model to project the 5-year risk reduction of diabetes-related complications under the assumption that intervention benefits persist over time. An alternative assumption that intervention benefits diminish by 30% every year was also tested.

RESULTS

The QI program was associated with reductions in HbA1c (-0.84%) and LDL cholesterol (LDL-C) (-5.94 mg/dL) among individuals with HbA1c level >8.0% (64 mmol/mol), with greater reduction in HbA1c (-1.67%) and LDL-C (-6.81 mg/dL) among those with HbA1c level >9.5% at baseline (all P < 0.05). The implementation of the Diabetes INSIDE QI program was associated with 5-year risk reductions in major adverse cardiovascular events (MACE) (relative risk [RR] 0.78 [95% CI 0.75-0.81]) and all-cause mortality (RR 0.83 [95% CI 0.82-0.85]) among individuals with baseline HbA1c level >8.0% (64 mmol/mol), and MACE (RR 0.60 [95% CI 0.56-0.65]) and all-cause mortality (RR 0.61 [95% CI 0.59-0.64]) among individuals with baseline HbA1c level >9.5% (80 mmol/mol). Sensitivity analysis also identified a substantially lower risk of diabetes-related complications and mortality associated with the QI program.

CONCLUSIONS

Our modeling results suggest that the ADA's Diabetes INSIDE QI program would benefit the patients and population by substantially reducing the 5-year risk of complications and mortality in individuals with diabetes.