Development of Evidence-Based Clinical Practice Guidelines for Diabetes

Pogach, Leonard; Brietzke, Stephen; Cowan, Claude L.; Conlin, Paul R.; Walder, Debby J.; Sawin, Clark T.

doi:10.2337/diacare.27.suppl_2.b82

Cited by 64 publications

(36 citation statements)

References 32 publications

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“…This result suggests that insulin self-management (injection compliance), the prescribed regimen, or both were inadequate to achieve good glycemic control. Newly developed Veterans Administration guidelines encourage targeting HbA 1c at Ͻ7% but allow for higher levels for older, sicker patients (17). Providers might be more lenient with high HbA 1c levels because of inconvenience, syringe-filling inaccuracy, wastage, or other dosing problems for these patients as long as patients did not become hypoglycemic or hyperglycemic.…”

Section: Research Design Andmentioning

confidence: 99%

The Influence of Insulin Use on Glycemic Control

2005

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OBJECTIVE -The purposes of this study were to determine the relationship between insulin self-management and glycemic control and to identify patient characteristics associated with better control. RESEARCH DESIGN AND METHODS-A Department of Veterans Affairs regional database was used to identify patients with diabetes on chronic insulin therapy (n ϭ 6,222) with dose defined as number of units and doses. The rate of insulin use during a 2-year period was calculated using pharmacy data. Regression analyses were used 1) to predict compliance with prescribed insulin regimens using demographic variables, HbA 1c levels, and a measure of diabetes management intensity and 2) to predict HbA 1c levels using demographic variables and rates of insulin use.RESULTS -Insulin use was 77.44 Ϯ 17% of prescribed amounts, including wastage; HbA 1c levels were 7.98 Ϯ 1.66%. Concomitant oral hypoglycemic agent use (84.89 Ϯ 16%) was higher than insulin use (P Ͻ 0.0001) but correlated with insulin use (r ϭ 0.189, P Ͻ 0.0001). Ordinary least-squares regression showed that race, HbA 1c levels, and intensity of diabetes management were significant predictors of insulin use. Age, race, and insulin use were significant predictors of HbA 1c levels.CONCLUSIONS -Adults prescribed a specific insulin regimen averaged using 77% of prescribed doses, demonstrating good intention to follow the prescription. However, HbA 1c higher than the recommended level suggested that the rate of insulin use, the prescribed regimen, or both were inadequate to achieve good glycemic control in patients with long-term insulin use. Diabetes Care 28:78 -83, 2005

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Section: Research Design Andmentioning

confidence: 99%

The Influence of Insulin Use on Glycemic Control

2005

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“…7 Moreover, while metabolic control in veterans tends to be better than in non-veterans, 8,9 studies show that many veterans have elevated A1c levels, 10 even after adjusting for comorbidity and life expectancy. 10,11 In particular, despite evidence-based guidelines showing "a strong case for intensive control among patients free, or nearly free, of diabetic microvascular disease" 12 early in their natural histories, many veterans do not have good diabetes control.…”

Section: Introductionmentioning

confidence: 99%

Increased Cardiovascular Disease, Resource Use, and Costs Before the Clinical Diagnosis of Diabetes in Veterans in the Southeastern U.S.

et al. 2015

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IMPORTANCE:Screening for diabetes might be more widespread if adverse associations with cardiovascular disease (CVD), resource use, and costs were known to occur earlier than conventional clinical diagnosis. OBJECTIVE: The purpose of this study was to determine whether adverse effects associated with diabetes begin prior to clinical diagnosis. DESIGN: Veterans with diabetes were matched 1:2 with controls by follow-up, age, race/ethnicity, gender, and VA facility. CVD was obtained from ICD-9 codes, and resource use and costs from VA datasets. SETTING: VA facilities in SC, GA, and AL. PARTICIPANTS: Patients with and without diagnosed diabetes. MAIN OUTCOME MEASURES: Diagnosed CVD, resource use, and costs. RESULTS: In this study, the 2,062 diabetic patients and 4,124 controls were 63 years old on average, 99 % male, and 29 % black; BMI was 30.8 in diabetic patients vs. 27.8 in controls (p<0.001). CVD prevalence was higher and there were more outpatient visits in Year −4 before diagnosis through Year +4 after diagnosis among diabetic vs. control patients (all p<0.01); in Year −2, CVD prevalence was 31 % vs. 24 %, and outpatient visits were 22 vs. 19 per year, respectively. Total VA costs/year/veteran were higher in diabetic than control patients from Year −4 ($4,083 vs. $2,754) through Year +5 ($8,347 vs. $5,700) (p<0.003) for each, reflecting underlying increases in outpatient, inpatient, and pharmacy costs KEY WORDS: diabetes; health care cost; cardiovascular disease; prediabetes. ABBREVIATIONS A1cHemoglobin A1c 749(p<0.05 for each). Regression analysis showed that diabetes contributed an average of $1,748/year to costs, independent of CVD (p<0.001). CONCLUSIONS AND RELEVANCE: VA costs per veteran are higher-over $1,000/year before and $2,000/year after diagnosis of diabetes-due to underlying increases in outpatient, inpatient, and pharmacy costs, greater number of outpatient visits, and increased CVD. Moreover, adverse associations with veterans' health and the VA healthcare system occur early in the natural history of the disease, several years before diabetes is diagnosed. Since adverse associations begin before diabetes is recognized, greater consideration should be given to systematic screening in order to permit earlier detection and initiation of preventive management. Keeping frequency of CVD and marginal costs in line with those of patients before diabetes is currently diagnosed has the potential to save up to $2 billion a year.

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“…These are increasingly being used across many countries in the routine clinical care of cancer patients. Most of them are published by national professional medical associations (e.g., Rizzo et al, 2002;Atwood et al, 2004;Makuuchi and Kokudo, 2006), but some are developed by governmental bodies (e.g., Pogach et al, 2004).…”

mentioning

confidence: 99%

The impact of cancer research: how publications influence UK cancer clinical guidelines

Lewison

Sullivan

2008

Br J Cancer

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There has been a substantially increased interest in biomedical research impact assessment over the past 5 years. This can be studied by a number of methods, but its influence on clinical guidelines must rank as one of the most important. In cancer, there are 43 UK guidelines (and associated Health Technology Assessments) published (up to October 2006) across three series, each of which has an evidence base in the form of references, many of which are papers in peer-reviewed journals. These have all been identified and analysed to determine their geographical provenance and type of research, in comparison with overall oncology research published in the peak years of guideline references (1999 -2001). The UK papers were cited nearly three times as frequently as would have been expected from their presence in world oncology research (6.5%). Within the United Kingdom, Edinburgh and Glasgow stood out for their unexpectedly high contributions to the guidelines' scientific base. The cited papers from the United Kingdom acknowledged much more explicit funding from all sectors than did the UK cancer research papers at the same research level.

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Development of Evidence-Based Clinical Practice Guidelines for Diabetes

Cited by 64 publications

References 32 publications

The Influence of Insulin Use on Glycemic Control

The Influence of Insulin Use on Glycemic Control

Increased Cardiovascular Disease, Resource Use, and Costs Before the Clinical Diagnosis of Diabetes in Veterans in the Southeastern U.S.

The impact of cancer research: how publications influence UK cancer clinical guidelines

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