George R. Biltz

Simulated physician learning intervention to improve safety and quality of diabetes care: a randomized trial.

OBJECTIVE To assess two physician learning interventions designed to improve safety and quality of diabetes care delivered by primary care physicians (PCPs). RESEARCH DESIGN AND METHODS This group randomized clinical trial included 57 consenting PCPs and their 2,020 eligible adult patients with diabetes. Physicians were randomized to no intervention (group A), a simulated case-based physician learning intervention (group B), or the same simulated case-based learning intervention with physician opinion leader feedback (group C). Dependent variables included A1C values, LDL cholesterol values, pharmacotherapy intensification rates in patients not at clinical goals, and risky prescribing events. RESULTS Groups B and C had substantial reductions in risky prescribing of metformin in patients with renal impairment (P = 0.03). Compared with groups A and C, physicians in group B achieved slightly better glycemic control (P = 0.04), but physician intensification of oral glucose-lowering medications was not affected by interventions (P = 0.41). Lipid management improved over time (P < 0.001) but did not differ across study groups (P = 0.67). CONCLUSIONS A simulated, case-based learning intervention for physicians significantly reduced risky prescribing events and marginally improved glycemic control in actual patients. The addition of opinion leader feedback did not improve the learning intervention. Refinement and further development of this approach is warranted.

Simulated Physician Learning Program Improves Glucose Control in Adults With Diabetes

OBJECTIVE Inexpensive and standardized methods to deliver medical education to primary care physicians (PCPs) are desirable. Our objective was to assess the impact of an individualized simulated learning intervention on diabetes care provided by PCPs. RESEARCH DESIGN AND METHODS Eleven clinics with 41 consenting PCPs in a Minnesota medical group were randomized to receive or not receive the learning intervention. Each intervention PCP was assigned 12 simulated type 2 diabetes cases that took about 15 min each to complete. Cases were designed to remedy specific physician deficits found in their electronic medical record observed practice patterns. General linear mixed models that accommodated the cluster randomized study design were used to assess patient-level change from preintervention to 12-month postintervention of A1C, blood pressure, and LDL cholesterol. The relationship between the study arm and the total of intervention and patient health care costs was also analyzed. RESULTS Intervention clinic patients with baseline A1C ≥7% significantly improved glycemic control at the last postintervention A1C measurement, intervention effect of −0.19% mean A1C (P = 0.034) and +6.7% in A1C <7% goal achievement (P = 0.0099). Costs trended lower, with the cost per patient −

Variations in cognitive demand affect heart rate in typically developing children and children at risk for developmental coordination disorder.

71 (SE = 142, P = 0.63) relative to nonintervention clinic patients. The intervention did not significantly improve blood pressure or LDL control. Models adjusting for age, sex, and comorbidity showed similar results. PCPs reported high satisfaction. CONCLUSIONS A brief individualized case-based simulated learning intervention for PCPs led to modest but significant glucose control improvement in adults with type 2 diabetes without increasing costs.

Acanthosis Nigricans and Oral Glucose Tolerance in Obese Children

BACKGROUND Developmental coordination disorder (DCD) is a diagnosis for children who present with movement difficulties, but are of normal intelligence without neurological deficits. Previous studies have demonstrated that children with DCD exhibit perceptual deficits and lower cognition performance. To date, their autonomic nervous system (ANS) responses during tasks requiring cognitive and perceptual effort have not been compared to typically developing children (TDC). OBJECTIVE The present study investigated heart rate variability (HRV) as a marker for ANS response differences between DCD and TDC, and the impact of different levels of task difficulty. METHODS Participants were 60 individuals (9-10 years); 30 children at risk for DCD, and 30 TDC. Each participant performed two tasks each of which demanded enhanced cognitive effort: a visual signal detection task and a digit memory task-each task had two levels of difficulty, low (LD) and high (HD). Heart rate responses were continuously recorded during performance of each task. Frequency domain analysis and heart rate sample entropy (SampEn) were computed to determine ANS responses in each of the tasks. RESULTS HRV differences were detected between the two levels of task difficulty, LD and HD, for the visual signal detection task, but not for the digit memory task. HRV differences between LD and HD conditions were greater for TDC children than DCD when engaged in visual signal detection task, compare to the memory task. INTERPRETATION The results suggest that children at risk for DCD may show decreased HRV as a marker for altered ANS responses and potential deficits in the linkage between their perceptions and actions.

RER variability analysis by sample entropy: comparing trained and untrained adolescent female soccer players

The recent dramatic increase in childhood obesity has been accompanied by an increased incidence of acanthosis nigricans (AN), with reports of up to 62% of obese youth having this condition. AN, a dermatologic manifestation characterized by thick and darkened layers of skin, has been proposed as a potentially useful clinical marker of insulin resistance and increased risk of future type 2 diabetes. This contention is supported by metabolic studies, which have shown that in obese children, AN is significantly associated with hyperinsulinemia, impaired postprandial glucose and insulin responses, and type 2 diabetes. Because children with AN tend to be at the most severe spectrum of obesity, it is not clear whether AN is independently associated with increased metabolic risk. Indeed, some reports have suggested that AN is not a reliable clinical marker of hyperinsulinemia and insulin resistance when fat mass is taken into account. Therefore, to address these conflicting reports, we sought to evaluate whether AN, independent of level of adiposity, is associated with increased basal and glucose-stimulated insulin levels in obese children. We hypothesized that obese children with AN would have higher fasting and postprandial levels of insulin compared to obese children without AN.

Examining Failure in a Dynamic Decision Environment: Strategies for Treating Patients with a Chronic Disease

Economy of movement is defmed as the mass related aerobic demand (V02 mL·kg-l·min-l) or energy expenditure required to run or walk at a given submaximal speed (Morgan, 2000). It has been well established that children have a lower economy compared to adults (Rowland and Green, 1988; Rowland et al., 1987; Unnithan and Eston, 1990). This means that at any given walking or running speed, children exhibit a higher weight relative V02compared to that of an adult. The difference in economy between children and adults is thought to be due to differences in stride frequency (SF), leg length, body-surface-area to mass ratio (BSA:M), body mass index (BMI), and ventilatory efficiency (Rowland et al., 1987; Rowland and Green, 1988; Unnithan and Eston, 1990).

Repeatability of Respiratory Exchange Ratio Time Series Analysis.

In this paper we investigate the dynamic decision-making task of primary care physicians treating patients with type 2 diabetes to achieve a blood glucose goal. The focus of the study is on developing and testing an information processing theory that can explain why some physicians more often succeed and others more often fail to achieve desirable clinical goals. The developed theory is represented in the form of two types of computational models, one employing a feedback decision-making strategy and the other a feedforward strategy. The models were implemented in software and tested using data from a previously reported experiment where physicians treated simulated patients with type 2 diabetes. The physician data were scored for a defined set of treatment errors. Computational processes were systematically examined to identify and specify processes to perturb in order to generate the observed errors. Models were created for each physician by introducing perturbations in computational processes based on errors that each physician committed during the experiment. These models treated the same simulated patients that the physicians treated; results from each model treating the patients were compared with the represented physician’s results to test the sufficiency of the models to explain observed errors. Process perturbations which explained observed errors took two characteristic forms, both of which resulted in delayed treatment action: (1) elevated thresholds for triggering action and (2) overestimating delayed effects of medications. Physician models made predictions for types and timing of subjects’ treatment errors: physician models generated 79 % of the same types of treatment errors as committed by physicians. As demonstrated by this study, developing task specific information processing theories (expressed as computational models) are useful for investigating patterns of decision making that lead to errors of performance. Studies of this nature can support the design of decision support systems intended to reduce errors associated with dynamic tasks, such as treating a chronic disease.

C-A3-02: How Do the Best Physicians Get Diabetes Patients to Glycemic Goals?

Abstract Nelson, MT, Biltz, GR, and Dengel, DR. Repeatability of respiratory exchange ratio time series analysis. J Strength Cond Res 29(9): 2550–2558, 2015—Currently, there are few studies on the repeatability of a time series analysis of respiratory exchange ratio (RER) under the same conditions. This repeated-measures study compared 2 trials completed under the same conditions. After an 8-hour fast, subjects (7 male and 5 female) (mean ± SD) of age 27.3 ± 3.7 years, body weight of 71.8 ± 8.4 kg, percent body fat of 16.4 ± 8.1%, and peak oxygen uptake (V[Combining Dot Above]O2peak) of 46.0 ± 5.3 ml·kg−1·min−1 completed a V[Combining Dot Above]O2peak test followed 7 days later by a cycle ergometer test at 30% of ventilatory threshold (VT) and 60% of VT for 15 minutes each. These tests were repeated again 7 days later. Paired t-tests revealed no significant differences between the tests for mean RER or sample entropy (SampEn) score at both intensities. The coefficients of variance were generally similar for the mean and SampEn of the RER. The intraclass correlation coefficient (ICC) values for the mean RER at 30% of VT were 1.00 and at 60% of VT were 0.92. The ICC values for the SampEn RER at 30% of VT were 0.81 and at 60% of VT were the lowest at 0.25. Bland-Altman plots demonstrated a measure of agreement between both methods. We demonstrated that RER measurements at 30 and 60% of VT are repeatable during steady-state cycle ergometery. Future research should determine if this finding is consistent with a larger sample size and different exercise intensities.

C-B4-04: Personalized Physician Learning Intervention Improved Glucose Control in Adults With Diabetes

Objective: To examine the glucose control related practice patterns of primary care physicians (PCP) and ascertain if those who provide better quality diabetes care have lower rates of clinical inertia. Methods: Study subjects included 80 PCPs at a large medial group in Minnesota, who were ranked on quality of diabetes care using a composite diabetes quality of care measure. Data on use of glucose lowering pharmacotherapy was combined with laboratory data indicating the level of glycated hemoglobin (A1c) at the time of each office visit to examine differences in patterns of glucose related treatment as a function of the physicians’ quality of care. GLM statistical models were used to assess the relationship. Results: Optimal PCPs, defined as the top quartile of PCPs, had lower rates of clinical inertia than their less well performing peers. Optimal PCPs initiated (P=0.08) and titrated (P=0.02) glucose lowering therapy at lower A1c levels than their peers. Optimal practice PCPs exhibited a feed forward treatment strategy, while their less well performing peers exhibited a feedback treatment strategy. Conclusions: There was significant variation in rates of clinical inertia and in trigger levels of A1c at which different PCPs initiated or intensified glucose lowering therapy in their adult patients with diabetes. Optimal docs had lower rates of clinical inertia. Interventions to reduce clinical inertia have great potential to improve diabetes care.

Clinical Inertia and Outpatient Medical Errors

Context: Personalization of learning interventions using opinion leaders improves care but is expensive. Automated methods to deliver personalized learning interventions to physicians have not been widely studied or rigorously evaluated. Objectives: To assess the impact of a computer-based personalized learning intervention for primary care physicians designed to improve control of glycated hemoglobin (A1c), blood pressure (BP) and LDL Cholesterol (LDL) in adults with type 2 diabetes. Design, Setting, and Participants: The randomized trial was conducted from October 2006 to May 2007 in Minnesota. Eleven clinics with 40 consenting primary care physicians (PCP) were randomized either to receive or not to receive a simulated personalized learning intervention designed to improve A1c, BP, and LDL in actual diabetes patients not at recommended clinical goals. Main Outcome Measures: Post-intervention levels of A1c, BP, and LDL controlling for pre-intervention levels and nesting of data. Results: Patients of intervention group PCPs had significantly better A1c (P=.044), SBP (P=.018), and DBP (P=.001), but not LDL relative to patients of PCPs randomized to the control arm of the study based on general linear mixed models with a repeated time measurement to control for clustering. Additional analytic models that adjusted for patient age, gender, and co-morbidity showed similar results. Nearly all PCPs were very satisfied with the intervention, which most completed in fewer than three hours in split sessions over one to two days. Conclusions: An inexpensive simulated personalized physician learning intervention for primary care physicians significantly improved glucose and BP control in adults with type 2 diabetes who were not at recommended clinical goals.