Michael E. Bowen

Increasing exposure to angiotensin-converting enzyme inhibitors in pregnancy.

OBJECTIVE The objective of the study was to identify angiotensin-converting enzyme (ACE) inhibitor prescription-filling trends in pregnant women. STUDY DESIGN This was a retrospective cohort study in women continuously enrolled in Tennessee Medicaid during pregnancy who delivered a live infant or had a fetal death between 1986-2003 (n = 262,179). RESULTS ACE inhibitor exposures increased more than 4-fold: from 11.2 per 10,000 pregnancies in 1986-1988 to 58.9 per 10,000 pregnancies by 2003 (adjusted risk ratio [RR], 4.49; 95% confidence interval [CI], 2.78-7.25). Exposures in the second and third trimesters nearly tripled (RR, 2.88; 95% CI, 1.45-5.75) and did not decrease following a US Food and Drug Administration black box warning against such use in 1992. Exposures were most common among women 35 years of age or older. CONCLUSION Despite evidence of fetal complications associated with ACE inhibitor use during pregnancy, the number of pregnant women with pregnancy-related ACE inhibitor exposures increased steadily between 1986-2003. Better methods are needed to reduce fetal exposure to potentially teratogenic prescribed medications.

Health Care Transition in Adolescents and Young Adults With Diabetes

IN BRIEF Improving health care transition in adolescents and young adults with diabetes is a challenge shared by both pediatric and adult practitioners. This article provides an overview of health care transitions, reviews selected approaches to transition, and provides recommendations for health care providers to facilitate and optimize transition in adolescents with diabetes.

Organizational factors associated with readiness to implement and translate a primary care based telemedicine behavioral program to improve blood pressure control: the HTN-IMPROVE study

BackgroundHypertension is prevalent and often sub-optimally controlled; however, interventions to improve blood pressure control have had limited success.ObjectivesThrough implementation of an evidence-based nurse-delivered self-management phone intervention to facilitate hypertension management within large complex health systems, we sought to answer the following questions: What is the level of organizational readiness to implement the intervention? What are the specific facilitators, barriers, and contextual factors that may affect organizational readiness to change?Study designEach intervention site from three separate Veterans Integrated Service Networks (VISNs), which represent 21 geographic regions across the US, agreed to enroll 500 participants over a year with at least 0.5 full time equivalent employees of nursing time. Our mixed methods approach used a priori semi-structured interviews conducted with stakeholders (n = 27) including nurses, physicians, administrators, and information technology (IT) professionals between 2010 and 2011. Researchers iteratively identified facilitators and barriers of organizational readiness to change (ORC) and implementation. Additionally, an ORC survey was conducted with the stakeholders who were (n = 102) preparing for program implementation.ResultsKey ORC facilitators included stakeholder buy-in and improving hypertension. Positive organizational characteristics likely to impact ORC included: other similar programs that support buy-in, adequate staff, and alignment with the existing site environment; improved patient outcomes; is positive for the professional nurse role, and is evidence-based; understanding of the intervention; IT infrastructure and support, and utilization of existing equipment and space.The primary ORC barrier was unclear long-term commitment of nursing. Negative organizational characteristics likely to impact ORC included: added workload, competition with existing programs, implementation length, and limited available nurse staff time; buy-in is temporary until evidence shows improved outcomes; contacting patients and the logistics of integration into existing workflow is a challenge; and inadequate staffing is problematic. Findings were complementary across quantitative and qualitative analyses.ConclusionsThe model of organizational change identified key facilitators and barriers of organizational readiness to change and successful implementation. This study allows us to understand the needs and challenges of intervention implementation. Furthermore, examination of organizational facilitators and barriers to implementation of evidence-based interventions may inform dissemination in other chronic diseases.

Understanding and managing variation: three different perspectives

Presentation Managing variation is essential to quality improvement. Quality improvement is primarily concerned with two types of variation – common-cause variation and specialcause variation. Common-cause variation is random variation present in stable healthcare processes. Special-cause variation is an unpredictable deviation resulting from a cause that is not an intrinsic part of a process. By careful and systematic measurement, it is easier to detect changes that are not random variation. The approach to managing variation depends on the priorities and perspectives of the improvement leader and the intended generalizability of the results of the improvement effort. Clinical researchers, healthcare managers, and individual patients each have different goals, time horizons, and methodological approaches to managing variation; however, in all cases, the research question should drive study design, data collection, and evaluation. To advance the field of quality improvement, greater understanding of these perspectives and methodologies is needed [1].

Multidisciplinary management of type 2 diabetes in children and adolescents

Although once considered a disease of adults, the prevalence of type 2 diabetes in youth is increasing at a significant rate. Similar to adults, youth with type 2 diabetes are at increased risk for developing hypertension, lipid abnormalities, renal disease, and other diabetes-related complications. However, children and adolescents with type 2 diabetes also face many unique management challenges that are different from adults with type 2 diabetes or children with type 1 diabetes. To deliver safe, effective, high-quality, cost-effective health care to adolescents with type 2 diabetes, reorganization and redesign of health care systems are needed. Multidisciplinary health care teams, which allow individuals with specialized training to maximally utilize their skills within an organized diabetes treatment team, may increase efficiency and effectiveness and may improve outcomes in children with type 2 diabetes. This review article provides a brief review of type 2 diabetes in children and adolescents, provides an overview of multidisciplinary health care teams, and discusses the role of multidisciplinary health care management in youth with type 2 diabetes.

The diabetes nutrition education study randomized controlled trial: A comparative effectiveness study of approaches to nutrition in diabetes self-management education

OBJECTIVE To compare the effectiveness of different approaches to nutrition education in diabetes self-management education and support (DSME/S). METHODS We randomized 150 adults with type 2 diabetes to either certified diabetes educator (CDE)-delivered DSME/S with carbohydrate gram counting or the modified plate method versus general health education. The primary outcome was change in HbA1C over 6 months. RESULTS At 6 months, HbA1C improved within the plate method [-0.83% (-1.29, -0.33), P<0.001] and carbohydrate counting [-0.63% (-1.03, -0.18), P=0.04] groups but not the control group [P=0.34]. Change in HbA1C from baseline between the control and intervention groups was not significant at 6 months (carbohydrate counting, P=0.36; modified plate method, P=0.08). In a pre-specified subgroup analysis of patients with a baseline HbA1C 7-10%, change in HbA1C from baseline improved in the carbohydrate counting [-0.86% (-1.47, -0.26), P=0.006] and plate method groups [-0.76% (-1.33, -0.19), P=0.01] compared to controls. CONCLUSION CDE-delivered DSME/S focused on carbohydrate counting or the modified plate method improved glycemic control in patients with an initial HbA1C between 7 and 10%. PRACTICE IMPLICATIONS Both carbohydrate counting and the modified plate method improve glycemic control as part of DSME/S.

Numeracy and Dietary Intake in Patients With Type 2 Diabetes

Purpose The purpose of this study is to describe the association between numeracy and self-reported dietary intake in patients with type 2 diabetes. Methods Numeracy and dietary intake were assessed with the validated Diabetes Numeracy Test and a validated food frequency questionnaire in a cross-sectional study of 150 primary care patients enrolled in a randomized clinical trial at an academic medical center between April 2008 and October 2009. Associations between numeracy and caloric and macronutrient intakes were examined with linear regression models. Results Patients with lower numeracy consumed a higher percentage of calories from carbohydrates and lower percentages from protein and fat. However, no differences in energy consumption or the percentage of energy intake owing to carbohydrates, fat, or protein were observed in adjusted analyses. Patients with lower numeracy were significantly more likely to report extremely high or low energy intake inconsistent with standard dietary intake. Conclusions Numeracy was not associated with dietary intake in adjusted analyses. Low numeracy was associated with inaccurate dietary reporting. Providers who take dietary histories in patients with diabetes may need to consider numeracy in their assessment of dietary intake.

Random Blood Glucose: A Robust Risk Factor For Type 2 Diabetes

CONTEXT Although random blood glucose (RBG) values are common in clinical practice, the role of elevated RBG values as a risk factor for type 2 diabetes is not well described. OBJECTIVE This study aimed to examine nondiagnostic, RBG values as a risk factor for type 2 diabetes DESIGN This was a cross-sectional study of National Health and Nutrition Examination Surveys (NHANES) participants (2005-2010). PARTICIPANTS Nonfasting NHANES participants (n = 13 792) without diagnosed diabetes were included. PRIMARY OUTCOME The primary outcome was glycemic status (normal glycemia, undiagnosed prediabetes, or undiagnosed diabetes) using hemoglobin HbA1C as the criterion standard. ANALYSIS Multinomial logistic regression examined associations between diabetes risk factors and RBG values according to glycemic status. Associations between current U.S. screening strategies and a hypothetical RBG screening strategy with undiagnosed diabetes were examined. RESULTS In unadjusted analyses, a single RBG ≥ 100 mg/dL (5.6 mmol/L) was more strongly associated with undiagnosed diabetes than any single risk factor (odds ratio [OR], 31.2; 95% confidence interval [CI], 21.3-45.5) and remained strongly associated with undiagnosed diabetes (OR, 20.4; 95% CI, 14.0-29.6) after adjustment for traditional diabetes risk factors. Using RBG < 100 mg/dL as a reference, the adjusted odds of undiagnosed diabetes increased significantly as RBG increased. RBG 100-119 mg/dL (OR 7.1; 95% CI 4.4-11.4); RBG 120-139 mg/dL (OR 30.3; 95% CI 20.0-46.0); RBG ≥ 140 mg/dL (OR 256; 95% CI 150.0-436.9). As a hypothetical screening strategy, an elevated RBG was more strongly associated with undiagnosed diabetes than current United States Preventative Services Task Force guidelines (hypertension alone; P < .0001) and similar to American Diabetes Association guidelines (P = .12). CONCLUSIONS A single RBG ≥ 100 mg/dL is more strongly associated with undiagnosed diabetes than traditional risk factors. Abnormal RBG values are a risk factor for diabetes and should be considered in screening guidelines.

Blood pressure control in a hypertension telemedicine intervention: does distance to primary care matter?

Although telemedicine may help overcome geographic access barriers, it is unknown whether rural patients receive greater benefits. In a secondary analysis of 503 veterans participating in a hypertension telemedicine study, the authors hypothesized that patients with greater travel distances would have greater improvements in 18‐month systolic blood pressure (SBP). Patients were categorized by telemedicine exposure and travel distance to primary care, derived from zip codes. Comparisons were (1) usual care (UC), distance <30 miles (reference); (2) UC, distance ≥30 miles; (3) telemedicine, distance <30 miles; (4) telemedicine, distance ≥30 miles. Compared with patients receiving UC, distance <30 miles (intercept=127.7), no difference in 18‐month SBP was observed in patients receiving UC, distance ≥30 miles (0.13 mm Hg, 95% confidence interval [−6.6 to 6.8]); telemedicine, distance <30 miles (−1.1 mm Hg [−7.3 to 5.2]); telemedicine, distance ≥30 miles (−0.80 mm Hg [−6.6 to 5.1]). Although telemedicine may help overcome geographic access barriers, additional studies are needed to identify patients most likely to benefit.

Performance of a Random Glucose Case-Finding Strategy to Detect Undiagnosed Diabetes

INTRODUCTION Random glucose <200 mg/dL is associated with undiagnosed diabetes but not included in screening guidelines. This study describes a case-finding approach using non-diagnostic random glucose values to identify individuals in need of diabetes testing and compares its performance to current screening guidelines. METHODS In 2015, cross-sectional data from non-fasting adults without diagnosed diabetes or prediabetes (N=7,161) in the 2007-2012 National Health and Nutrition Examination Surveys were analyzed. Random glucose and survey data were used to assemble the random glucose, American Diabetes Association (ADA), and U.S. Preventive Services Task Force (USPSTF) screening strategies and predict diabetes using hemoglobin A1c criteria. RESULTS Using random glucose ≥100 mg/dL to select individuals for diabetes testing was 81.6% (95% CI=74.9%, 88.4%) sensitive, 78% (95% CI=76.6%, 79.5%) specific and had an area under the receiver operating curve (AROC) of 0.80 (95% CI=0.78, 0.83) to detect undiagnosed diabetes. Overall performance of ADA (AROC=0.59, 95% CI=0.58, 0.60), 2008 USPSTF (AROC=0.62, 95% CI=0.59, 0.65), and 2015 USPSTF (AROC=0.64, 95% CI=0.61, 0.67) guidelines was similar. The random glucose strategy correctly identified one case of undiagnosed diabetes for every 14 people screened, which was more efficient than ADA (number needed to screen, 35), 2008 USPSTF (44), and 2015 USPSTF (32) guidelines. CONCLUSIONS Using random glucose ≥100 mg/dL to identify individuals in need of diabetes screening is highly sensitive and specific, performing better than current screening guidelines. Case-finding strategies informed by random glucose data may improve diabetes detection. Further evaluation of this strategys effectiveness in real-world clinical practice is needed.