Individualized Glycemic Control for U.S. Adults With Type 2 Diabetes: A Cost-Effectiveness Analysis.

Background: Intensive glycemic control in type 2 diabetes (glycated hemoglobin [HbA1c] level <7%) is an established, cost-effective standard of care. However, guidelines recommend individualizing goals on the basis of age, comorbidity, diabetes duration, and complications. Objective: To estimate the cost-effectiveness of individualized control versus uniform intensive control (HbA1c level <7%) for the U.S. population with type 2 diabetes. Design: Patient-level Monte Carlo-based Markov model. Data Sources: National Health and Nutrition Examination Survey 2011-2012. Target Population: The approximately 17.3 million persons in the United States with diabetes diagnosed at age 30 years or older. Time Horizon: Lifetime. Perspective: Health care sector. Intervention: Individualized versus uniform intensive glycemic control. Outcome Measures: Average lifetime costs, life-years, and quality-adjusted life-years (QALYs). Results of Base-Case Analysis: Individualized control saved $13 547 per patient compared with uniform intensive control ($105 307 vs. $118 854), primarily due to lower medication costs ($34 521 vs. $48 763). Individualized control decreased life expectancy (20.63 vs. 20.73 years) due to an increase in complications but produced more QALYs (16.68 vs. 16.58) due to fewer hypoglycemic events and fewer medications. Results of Sensitivity Analysis: Individualized control was cost-saving and generated more QALYs compared with uniform intensive control, except in analyses where the disutility associated with receiving diabetes medications was decreased by at least 60%. Limitation: The model did not account for effects of early versus later intensive glycemic control. Conclusion: Health policies and clinical programs that encourage an individualized approach to glycemic control for U.S. adults with type 2 diabetes reduce costs and increase quality of life compared with uniform intensive control. Additional research is needed to confirm the risks and benefits of this strategy. Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases.

Use of Decision Aids with Minority Patients: a Systematic Review.

BACKGROUND: One potential approach to reducing health disparities among minorities is through the promotion of shared decision making (SDM). The most commonly studied SDM intervention is the decision aid (DA). While DAs have been extensively studied, we know relatively little about their use in minority populations. We conducted a systematic review to characterize the application and effectiveness of DAs in racial, ethnic, sexual, and gender minorities. METHODS: We searched PubMed for randomized controlled trials (RCTs) evaluating DAs between 2004 and 2013. We included trials that enrolled adults (> 18 years of age) with > 50 % representation by minority patients. Four reviewers independently assessed 597 initially identified articles, and those with inconclusive results were discussed to consensus. We abstracted decision quality, patient-doctor communication, and clinical treatment decision outcomes. Results were considered significantly modified by the DA if the study reported p < 0.05. RESULTS: We reviewed 18 RCTs of DA interventions in minority populations. The majority of interventions (78 %) addressed cancer screening. The most common mode of delivery for the DAs was personal counseling (46 %), followed by multi-media (29 %), and print materials (25 %). Most of the trials studied racial (78 %) or ethnic (17 %) minorities with only one trial focused on sexual minorities and none on gender minorities. Ten studies tailored their interventions for their minority populations. Comparing intervention vs. control, decision quality outcomes improved in six out of eight studies and patient-doctor communication improved in six out of seven studies. Of the 15 studies that reported on clinical decisions, eight demonstrated significant changes in decisions with DAs. DISCUSSION: DAs have been effective in improving patient-doctor communication and decision quality outcomes in minority populations and could help address health disparities. However, the existing literature is almost non-existent for sexual and gender minorities and has not included the full breadth of clinical decisions that affect minority populations.

A roadmap to equitable school mental health screening.

Youth in the United States are experiencing mental health concerns at alarming rates. Considering the nation's legacy of racism and growing recognition of the impact of social determinants of health on educational and mental health inequities, it is imperative to re-envision how we approach mental health screening in schools to center equity. A focus on mental health screening for the sole purpose of identifying individual at-risk students ignores key contextual considerations, is ineffective in addressing health and educational inequities, and has the potential to perpetuate oppressive practices in schools. Equity-focused mental health screening requires a shift from individual- and deficit-focused approaches to systems- and holistic-focused approaches that (a) identify strengths and stressors among individuals, groups, and communities; (b) dismantle structural forms of oppression; and (c) promote positive mental health outcomes for minoritized youth. Integrating recommendations from the educational equity literature and critical school mental health frameworks, this paper identifies core considerations for equitable school mental health screening and provides guiding principles for each phase of the screening process, from screening readiness to execution to follow up. To implement these recommendations and transform school-based mental health care, schools should (a) incorporate multiple perspectives; (b) prioritize student, family, and community voices; and (c) build collaborative partnerships to co-construct a vision for equitable school mental health.

Association of Metformin with Susceptibility to COVID-19 in People with Type 2 Diabetes.

OBJECTIVE: Diabetes has emerged as an important risk factor for mortality from COVID-19. Metformin, the most commonly prescribed glucose-lowering agent, has been proposed to influence susceptibility to and outcomes of COVID-19 via multiple mechanisms. We investigated whether, in patients with diabetes, metformin is associated with susceptibility to COVID-19 and its outcomes. RESEARCH DESIGN AND METHODS: We performed a propensity score-matched cohort study with active comparators using a large UK primary care dataset. Adults with type 2 diabetes patients and a current prescription for metformin and other glucose-lowering agents (MF+) were compared to those with a current prescription for glucose-lowering agents that did not include metformin (MF-). Outcomes were confirmed COVID-19, suspected/confirmed COVID-19, and associated mortality. A negative control outcome analysis (back pain) was also performed. RESULTS: There were 29 558 and 10 271 patients in the MF+ and MF- groups, respectively, who met the inclusion criteria. In the propensity score-matched analysis, the adjusted hazard ratios for suspected/confirmed COVID-19, confirmed COVID-19, and COVID-19-related mortality were 0.85 (95% CI 0.67, 1.08), 0.80 (95% CI 0.49, 1.30), and 0.87 (95% CI 0.34, 2.20) respectively. The negative outcome control analysis did not suggest unobserved confounding. CONCLUSION: Current prescription of metformin was not associated with the risk of COVID-19 or COVID-19-related mortality. It is safe to continue prescribing metformin to improve glycemic control in patients with.

Using Public Claims Data for Neighborhood Level Epidemiologie Surveillance of Breast Cancer Screening: Findings from Evaluating a Patient Navigation Program in Chicago's Chinatown.

OBJECTIVES: This study was designed to evaluate a patient navigation program undertaken with our community partners in Chicago's Chinatown. Inadvertently, the study collected data on two biannual mammography screening cycles that coincided almost exactly with implementation of the Affordable Care Act (ACA) in Illinois. METHODS: The study uses claims data to profile mammography screening rates for residents of an 18 zip code, 398 census tract area on Chicago's near south and southwest side. Patient addresses were geocoded from biannual (August 2011 to July 2103 and August 2103 to July 2015) Illinois Medicaid and Illinois Breast and Cervical Cancer Program (IBCCP) claims. Screening rates are presented separately for low-income women ages 40 to 49 and 50 to 64 years. We compare change between 16 tracts with greater than 20% Chinese ancestry, 85 tracts with 1% to 20% Chinese ancestry, and 297 tracts with less than 1% Chinese ancestry. RESULTS: There were more than 65,000 low-income women age 40 to 64 in the study area (mammogram patients were 63% Black, 23% Hispanic, 10% White, 2.5% Asian, and 2.5% other/unknown race and ethnicity). The increase in screening was greatest in Chinatown, although mean rates were not significantly different across the three areas (p = .07). DISCUSSION: Our results demonstrate large increases in mammography screening after ACA implementation in 20132014. The greatest increase occurred in the Chinatown patient navigation program area. The study provides a template for programs aimed at using public community-area data to evaluate programs for improving access to care and health equity.

Development and Validation of the Real-World Progression in Diabetes (RAPIDS) Model.

INTRODUCTION: To develop and validate the first real-world data-based type 2 diabetes progression model (RAPIDS) employing econometric techniques that can study the comparative effects of complex dynamic patterns of glucose-lowering drug use. METHODS: The US Department of Veterans Affairs (VA) electronic medical record and claims databases were used to identify over 500,000 diabetes patients in 2003 with up to 9-year follow-up. The RAPIDS model contains interdependent first-order Markov processes over quarters for each of the micro- and macrovascular events, hypoglycemia, and death, as well as predictive models for 8 biomarker levels. Model parameters varied by static demographic factors and dynamic factors, such as age, duration of diabetes, 13 possible glucose-lowering treatment combinations, any blood pressure and any cholesterol-lowering medications, and cardiovascular history. To illustrate model capabilities, a simple comparative study was set up to compare observed treatment use patterns to alternate patterns if perfect adherence is assumed following initiating the use of any of these medications. RESULTS: Data were randomly split into 307,288, 105,195, and 105,081 patients to perform estimation, out-of-sample calibration, and validation, respectively. Model predictions in the validation sample closely aligned with the observed longitudinal trajectory of biomarkers and outcomes. Perfect adherence among initiators increased proportion of days covered by only 6 months. Most of this increase came from increased adherence to monotherapies and did not lead to meaningful changes in any of the outcomes over the 9-year period. CONCLUSION: Future value of increasing medication adherence among VA patients with diabetes may lie among those who never initiate treatment or are late in initiating treatment. The first-of-its-kind real-world data-based model has the potential to carry out many complex comparative-effectiveness research (CER) studies of dynamic glucose-lowering drug regimens.

Building Cross-Institutional Collaborative Infrastructure and Processes: Early Lessons From the Chicago Cancer Health Equity Collaborative.

BACKGROUND: Addressing cancer health disparities requires a multitiered, comprehensive approach. The Chicago Cancer Health Equity Collaborative (ChicagoCHEC) was established as a tri-institutional partnership to advance cancer health equity through scientific discovery, education, and community engagement. OBJECTIVES: Large-scale partnerships rarely document the challenges encountered when establishing processes and operations in the formative years of engagement. We outline selected lessons learned from the first three years of ChicagoCHEC in hopes that future collaborations may be better poised to hit the ground running and create the needed infrastructure for a strong, effective, and sustainable partnership. LESSONS LEARNED: Unifying a diverse group of stakeholders under a shared mission is imperative. A shared governance structure, in which all individuals understand the aims of partnership and can facilitate progress, is crucial for success. Ongoing monitoring of collaborative processes should occur and attention should be given to the optimization of communications. CONCLUSIONS: Large-scale collaborative research and education projects across institutions can be challenging, particularly when establishing a working infrastructure and aligning priorities. However, the benefit of establishing key processes in the early years of the collaborative process can lead to high-quality research output, impact, and a sustainable partnership.

Diabetic foot ulcer severity predicts mortality among veterans with type 2 diabetes.

AIM: Diabetic foot ulcers are associated with an increased risk of death. We evaluated whether ulcer severity at presentation predicts mortality. METHODS: Patients from a national, retrospective, cohort of veterans with type 2 diabetes who developed incident diabetic foot ulcers between January 1, 2006 and September 1, 2010, were followed until death or the end of the study period, January 1, 2012. Ulcers were characterized as early stage, osteomyelitis, or gangrene at presentation. Cox proportional hazard regression identified independent predictors of death, controlling for comorbidities, laboratory parameters, and healthcare utilization. RESULTS: 66,323 veterans were included in the cohort and followed for a mean of 27.7months: 1-, 2-, and 5-year survival rates were 80.80%, 69.01% and 28.64%, respectively. Compared to early stage ulcers, gangrene was associated with an increased risk of mortality (HR 1.70, 95% CI 1.57-1.83, p<0.001). The magnitude of this effect was greater than diagnosed vascular disease, i.e., coronary artery disease, peripheral arterial disease, or stroke. CONCLUSION: Initial diabetic foot ulcer severity is a more significant predictor of subsequent mortality than coronary artery disease, peripheral arterial disease, or stroke. Unrecognized or under-estimated vascular disease and/or sepsis secondary to gangrene should be explored as possible causal explanations.

Ten-year hemoglobin A1c trajectories and outcomes in type 2 diabetes mellitus: The Diabetes & Aging Study.

AIMS: To classify trajectories of long term HbA1c values in patients after diagnosis of type 2 diabetes and examine each trajectory's associations with subsequent microvascular and macrovascular events and mortality. METHODS: A longitudinal follow-up of 28,016 patients newly diagnosed with type 2 diabetes was conducted. Latent growth mixture modeling was used to identify ten-year HbA1c trajectories. Cox proportional hazards models were used to assess how HbA1c trajectories were associated with events (microvascular and macrovascular) and mortality. RESULTS: We identified 5 HbA1c trajectories: "low stable" (82.5%), "moderate increasing late" (5.1%), "high decreasing early" (4.9%), "moderate peaking late" (4.1%) and "moderate peaking early" (3.3%). After adjusting for average HbA1c, compared to the low stable trajectory, all non-stable trajectories were associated with higher incidences of microvascular events (hazard ratio (HR) range, 1.28 (95% CI, 1.08-1.53) (high decreasing early) to 1.45 (95% CI, 1.20-1.75) (moderate peaking early)). The high decreasing early trajectory was associated with an increased mortality risk (HR, 1.27 (95% CI, 1.03-1.58)). Trajectories were not associated with macrovascular events. CONCLUSIONS: Non-stable HbA1c trajectories were associated with greater risk of microvascular events and mortality. These findings suggest a potential benefit of early diabetes detection, prioritizing good glycemic control, and maintaining control over time.

Impact and Feasibility of Personalized Decision Support for Older Patients with Diabetes: A Pilot Randomized Trial.

BACKGROUND: Diabetes guidelines recommend individualizing glycemic goals (A1C) for older patients. The aim of this study was to assess a personalized Web-based decision support tool. METHODS: We randomized physicians and their patients with type 2 diabetes (≥65 years of age) to a support tool or educational pamphlet (75:25 patients). Prior to a visit, intervention patients interacted with the tool, which provided personalized risk predictions and elicited treatment preferences. Main outcomes included 1) patient-doctor communication, 2) decisional conflict, 3) changes in goals, and 4) intervention acceptability. RESULTS: We did not find significant differences in proportions of patients who had an A1C discussion (91% intervention v. 76% control; P = 0.19). Intervention patients had larger declines in the informed subscale of decisional conflict (-20 v. 0, respectively; P = 0.04). There were no significant differences in proportions of patients with changes in goals (49% v. 28%, respectively; P = 0.08). Most intervention patients reported that the tool was easy to use (91%) and helped them to communicate (84%). A limitation was that this was a pilot trial at one academic institution. CONCLUSIONS: Web-based decision support tools may be a practical approach to facilitating the personalization of goals for chronic conditions. TRIAL REGISTRATION: NCT02169999 ( https://clinicaltrials.gov/show/NCT02169999 ).

Life Expectancy Predictions for Older Diabetic Patients as Estimated by Physicians and a Prognostic Model.

Background: Multiple medical organizations recommend using life expectancy (LE) to individualize diabetes care goals. We compare the performance of patient LE predictions made by physicians to LE predictions from a simulation model (the Chicago model) in a cohort of older diabetic patients. DESIGN: Retrospective cohort study of a convenience sample (n = 447) of diabetes patients over 65 years and their physicians. Measurements: Physicians provided LE estimates for individual patients during a baseline survey (2000-2003). The prognostic model included a comprehensive geriatric type 2 diabetes simulation model (the Chicago model) and combinations of the physician estimate and the Chicago model ("And," "Or," and "Average" models). Observed survival was determined based on the National Death Index through 31 December 2010. The predictive accuracy of LE predictions was assessed using c-statistic for 5-year mortality; Harrell's c-statistic, and Integrated Brier score for overall survival. Results: The patient cohort had a mean (SD) age of 73.4 (5.9) years. The majority were female (62.6%) and black (79.4%). At 5 years, 108 (24.2%) patients had died. The c-statistic for 5-year mortality was similar for physicians (0.69) and the Chicago model (0.68), while the average of estimates by physicians and Chicago model yielded the highest c-statistic of any method tested (0.73). The estimates of overall survival yielded a similar pattern of results. Limitations: Generalizability of patient cohort and lack of updated model parameters. Conclusions: Compared with individual methods, the average of LE estimates by physicians and the Chicago model had the best predictive performance. Prognostic models, such as the Chicago model, may complement and support physicians' intuitions as they consider treatment decisions and goals for older patients with chronic conditions like diabetes.

Geographic Variation in Rosiglitazone Use Surrounding FDA Warnings in the Department of Veterans Affairs.

BACKGROUND: Geographic variation in the use of prescription drugs, particularly those deemed harmful by the FDA, may lead to variation in patient exposure to adverse drug events. One such drug is the glucose-lowering drug rosiglitazone, for which the FDA issued a safety alert on May 21, 2007, following the publication of a meta-analysis that suggested a 43% increase in the risk of myocardial infarction with the use of rosiglitazone. This alert was followed by a black box warning on August 14, 2007, that was updated 3 months later. While large declines have been documented in rosiglitazone use in clinical practice, little is known about how the use of rosiglitazone and other glucose-lowering drugs varied within the Department of Veterans Affairs (VA), surrounding the FDA alerts. Understanding this variation within integrated health care systems is essential to formulating policies that enhance patient protection and quality of care. OBJECTIVE: To document variation in the use of rosiglitazone and other glucose- lowering drugs across 21 Veterans Integrated Service Networks (VISNs). METHODS: We conducted a retrospective analysis of drug use patterns for all major diabetes drugs in a national cohort of 550,550 veterans with diabetes from 2003 to 2008. This included the time periods when rosiglitazone was added to (November 2003) and removed from (October 2007) the VA national formulary (VANF). We employed multivariable logistic regression models to statistically estimate the association between a patient's location and the patient's odds of using rosiglitazone. RESULTS: Aggregate rosiglitazone use increased monotonically from 7.7%, in the quarter it was added to the VANF (November 4, 2003), to a peak of 15.3% in the quarter when the FDA issued the safety alert. Rosiglitazone use decreased sharply afterwards, reaching 3.4% by the end of the study period (September 30, 2008). The use of pioglitazone, another glucose-lowering drug in the same class as rosiglitazone, was low when the FDA issued the safety alert (0.4%) but increased sharply afterwards, reaching 3.6% by the end of the study period. Insulin use increased monotonically; metformin use remained relatively flat; and sulfonylurea use exhibited a general declining trend throughout the study period. Statistically significant geographic variation was observed in rosiglitazone use throughout the study period. The prevalence range, defined as the range of minimum to maximum use across VISNs was 3.7%-12.4% in the first quarter (January 1 to March 31, 2003); 1.0%-5.5% in the last quarter of study period (July 1 to September 30, 2008); and reached a peak of 9.6%-25.5% in the quarter when the FDA safety alert was issued (April 1 to March 31, 2007). In 5 VISNs, peak rosiglitazone use occurred before the FDA issued the safety alert. The odds ratio of using rosiglitazone in a given VISN varied from 0.55 (95% CI = 0.52-0.59; VISN 10) to 1.58 (95% CI = 1.50-1.66; VISN 15), with VISN 1 being the reference region. The variation was higher in the periods after the FDA issued the safety alert. Much less variation was observed in the use of pioglitazone, metformin, sulfonylurea, and insulin. CONCLUSIONS: Our results show statistically significant variation in the way VISNs within the VA responded to the FDA alerts, suggesting a need for mechanisms that disseminate information and guidelines for drug use in a consistent and reliable manner. Further study of regions that adopted ideal practices earlier may provide lessons for regional leadership and practice culture within integrated health care systems.