Advancing Diabetes Quality Measurement in the Era of Continuous Glucose Monitoring.

PURPOSE: The purpose of this research is to develop a set of continuous glucose monitoring (CGM)-related measure concepts to be tested in a health care system. Existing measures assessing the quality of diabetes care do not include modern approaches to diabetes management, such as CGM. Continuous glucose monitors rival traditional methods of measuring diabetes management by providing real-time, longitudinal data and demonstrating glucose variability over time. The Improving Diabetes Quality Initiative seeks to address this gap in diabetes quality measurement. METHODS: A Technical Expert Panel (TEP) was convened to curate a diabetes quality measures portfolio and conceptualize three new CGM-related quality measures within the portfolio. From the additional measure concepts identified in the portfolio, the TEP prioritized three for conceptualization. High-level measure concept specifications were made available during a public comment period. RESULTS: The measure concepts prioritized by the TEP included a shared decision-making measure to assess the value of initiating CGM for disease management, a utilization measure to address disparities in access and use of CGM, and a patient-provider review of CGM data to promote routine consideration of these assessments in treatment and ongoing management. Clinical literature, public comments, and TEP feedback informed full measure specifications. CONCLUSIONS: The evolution of diabetes technology reflects the need to shift diabetes quality of care. The measure concepts will be tested in a flexible pilot setting to understand the future of diabetes care and communicate the value of CGM to people with diabetes, providers, and payers.

Hemoglobin A1C testing frequency among patients with type 2 diabetes within a US payer system: a retrospective observational study.

OBJECTIVE: The American Diabetes Association (ADA) guidelines recommend A1C testing schedules for patients with type 2 diabetes; however, level of real-world guideline adherence remains unclear. The current study evaluated A1C testing frequency and its association with glycemic control and cardiovascular outcomes. METHODS: A retrospective study was conducted utilizing Aetna's Enterprise Data Warehouse. Adult patients with a medical claim for type 2 diabetes in 2017 (index date) were included. Patients had continuous enrollment through December 2019 and ≥1 reported A1C measurement from 2017 to 2019. Follow-up was up to 36 months post-index date. RESULTS: Of the 112,572 eligible patients, 50.0% were female and median age was 70 years; 32.9% of patients with controlled baseline A1C (<8%, 64 mmol/mol) received less than the 2 tests/year recommended by the ADA, while 60.6% of patients with uncontrolled baseline A1C received less than the quarterly testing recommended by the ADA. More frequent testing was associated with age (65-75 years), uncontrolled baseline A1C and presence of comorbidities. In separate multivariable models, 2-3 A1C tests/year were associated with greater likelihood of A1C < 8% (64 mmol/mol) vs. <2 tests/year (OR = 1.07, 95% confidence interval [CI] 1.02-1.12), while >3 tests/year was associated with a modestly increased risk of cardiovascular events vs. <2 tests/year (OR = 1.08, 95% CI 1.01-1.15). CONCLUSIONS: A large proportion of type 2 diabetes patients were not tested per guideline recommendations. The relationship between A1C testing frequency and glycemic control was inconsistent, though there was a significant association between more frequent testing and experiencing a CV event.

Evaluating the relationship between clinical and demographic characteristics of insulin-using people with diabetes and their health outcomes: a cluster analysis application.

BACKGROUND: The aim of this study was to determine how clusters or subgroups of insulin-treated people with diabetes, based upon healthcare resource utilization, select social demographic and clinical characteristics, and diabetes management parameters, are related to health outcomes including acute care visits and hospital admissions. METHODS: This was a non-experimental, retrospective cluster analysis. We utilized Aetna administrative claims data to identify insulin-using people with diabetes with service dates from 01 January 2015 to 30 June 2018. The study included adults over the age of 18 years who had a diagnosis of type 1 (T1DM) or type 2 diabetes mellitus (T2DM) on insulin therapy and had Aetna medical and pharmacy coverage for at least 18 months (6 months prior and 12 months after their index date, defined as either their first insulin prescription fill date or their earliest date allowing for 6 months' prior coverage). We used K-means clustering methods to identify relevant subgroups of people with diabetes based on 13 primary outcome variables. RESULTS: A total of 100,650 insulin-using people with diabetes were identified in the Aetna administrative claims database and met study criteria, including 11,826 (11.7%) with T1DM and 88,824 (88.3%) with T2DM. Of these 79,053 (78.5%) people were existing insulin users. Seven distinct clusters were identified with different characteristics and potential risks of diabetes complications. Overall, clusters were significantly associated with differences in healthcare utilization (emergency room visits, inpatient admissions, and total inpatient days) after multivariable adjustment. CONCLUSIONS: This analysis of healthcare claims data using clustering methodologies identified meaningful subgroups of patients with diabetes using insulin. The subgroups differed in comorbidity burden, healthcare utilization, and demographic factors which could be used to identify higher risk patients and/or guide the management and treatment of diabetes.

Effects of conformance to type 2 diabetes guidelines on health care resource utilization, clinical outcomes, and cost: A retrospective claims analysis.

OBJECTIVES: To determine if there is a difference in the outcomes of diabetes patients managed with high, intermediate, or low conformance to diabetes guidelines. STUDY DESIGN: Retrospective database analysis. METHODS: This was a retrospective database analysis of adults diagnosed with type 2 diabetes and with glycated hemoglobin (HbA1c) ≥7% (53 mmol/mol) who were commercially insured by, or receiving Medicare benefits through, Aetna. Subjects were classified as having high, intermediate, or low conformance to current guidelines. Six, 12, and 18 months later, health care resource utilization, clinical outcomes, and costs were assessed using multivariable regression analysis to determine whether differences existed between patients with high, intermediate, and low conformance. Regression models were adjusted using pre-index variables, and the results were expressed as incidence rate ratios (IRRs) with 95% confidence intervals (CIs). RESULTS: A total of 21,171 individuals were included in the analysis. In analyses of patients with low versus high conformance, pharmacy costs were significantly lower over 18 months of outcome assessment (P < 0.001), but diabetes-related outpatient costs were significantly higher (P < 0.001). In analyses of patients with intermediate versus high conformance, diabetes-related outpatient costs were significantly greater at 12 and 18 months (P < 0.001 for both). CONCLUSIONS: Reduced conformance to guidelines leads to higher diabetes-related costs.

Impact of the Coventry complex case management program in the Kentucky Medicaid population.

A case management program implemented by Coventry Healthcare in one of the nation's poorest areas produced positive, measurable results among patients with diabetes.

Health care clinicians in sexual health medicine: focus on erectile dysfunction.

A consensus guidelines model was developed for managing erectile dysfunction (ED) by urology nurses and other health care clinicians. The model emphasizes identification of ED in all males older than 40, education and counseling as keys to intervention, and inclusion of partners whenever possible. These guidelines are intended to provide a comprehensive care model for ED patients and their partners, which would be optimally cost effective and clinically relevant. If successful, this new model will allow quality sexual health care to be provided to increasing numbers of patients and their partners.