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1.  Seeing the forests and the trees—innovative approaches to exploring heterogeneity in systematic reviews of complex interventions to enhance health system decision-making: a protocol 
Systematic Reviews  2014;3:88.
To improve quality of care and patient outcomes, health system decision-makers need to identify and implement effective interventions. An increasing number of systematic reviews document the effects of quality improvement programs to assist decision-makers in developing new initiatives. However, limitations in the reporting of primary studies and current meta-analysis methods (including approaches for exploring heterogeneity) reduce the utility of existing syntheses for health system decision-makers. This study will explore the role of innovative meta-analysis approaches and the added value of enriched and updated data for increasing the utility of systematic reviews of complex interventions.
We will use the dataset from our recent systematic review of 142 randomized trials of diabetes quality improvement programs to evaluate novel approaches for exploring heterogeneity. These will include exploratory methods, such as multivariate meta-regression analyses and all-subsets combinatorial meta-analysis. We will then update our systematic review to include new trials and enrich the dataset by surveying authors of all included trials. In doing so, we will explore the impact of variables not, reported in previous publications, such as details of study context, on the effectiveness of the intervention. We will use innovative analytical methods on the enriched and updated dataset to identify key success factors in the implementation of quality improvement interventions for diabetes. Decision-makers will be involved throughout to help identify and prioritize variables to be explored and to aid in the interpretation and dissemination of results.
This study will inform future systematic reviews of complex interventions and describe the value of enriching and updating data for exploring heterogeneity in meta-analysis. It will also result in an updated comprehensive systematic review of diabetes quality improvement interventions that will be useful to health system decision-makers in developing interventions to improve outcomes for people with diabetes.
Systematic review registration
PROSPERO registration no. CRD42013005165
PMCID: PMC4174390  PMID: 25115289
Diabetes care; Knowledge translation; Quality improvement interventions; Complex Interventions; Health system decision-makers; Systematic review; Meta-analysis; Implementation science; Heterogeneity; Hierarchical modeling
2.  Identifying strategies to improve diabetes care in Alberta, Canada, using the knowledge-to-action cycle 
CMAJ Open  2013;1(4):E142-E150.
Strategic clinical networks, a recent development in the health system in Alberta, have been charged with bringing together front-line clinicians, researchers and policy-makers to identify variation in clinical care, and to propose standards, pathways and innovative solutions to improve access and quality of care. Here, we describe a collaborative workshop held between researchers and the Obesity, Diabetes and Nutrition Strategic Clinical Network to describe barriers to and facilitators of care for people with diabetes and to identify quality improvement interventions that should be prioritized.
Through collaboration between health researchers and the strategic clinical network, and using principles of the knowledge-to-action cycle, we identified barriers to and facilitators of diabetes care using data from a patient survey and a provider focus group (5 primary care physicians and 1 diabetes educator). In addition, we identified best evidence from a systematic review of quality improvement initiatives in diabetes. This information was reviewed at a multistakeholder workshop where potential quality improvement initiatives were considered at various service levels.
A pilot survey involving 59 patients with diabetes and a focus group of primary care and allied health care providers identified several important barriers to optimal outcomes in diabetes care, including patient-level financial barriers to care and difficulty navigating the health system. Our collaborative discussion using the knowledge-to-action cycle prioritized feasible, evidence-based interventions to improve outcomes for patients with diabetes, including enabling care by allied health care providers and creating clear care maps and processes for system navigation.
We identified important barriers to achieving optimal outcomes in diabetes that may be overcome through the use of evidence-based quality improvement interventions. As recommended within the knowledge-to-action cycle, future research is required to determine whether program implementation improves outcomes and is cost-effective.
PMCID: PMC3985932  PMID: 25077116
3.  Enrolment in primary care networks: impact on outcomes and processes of care for patients with diabetes 
Primary care networks are a newer model of primary care that focuses on improved access to care and the use of multidisciplinary teams for patients with chronic disease. We sought to determine the association between enrolment in primary care networks and the care and outcomes of patients with diabetes.
We used administrative health care data to study the care and outcomes of patients with incident and prevalent diabetes separately. For patients with prevalent diabetes, we compared those whose care was managed by physicians who were or were not in a primary care network using propensity score matching. For patients with incident diabetes, we studied a cohort before and after primary care networks were established. Each cohort was further divided based on whether or not patients were cared for by physicians enrolled in a network. Our primary outcome was admissions to hospital or visits to emergency departments for ambulatory care sensitive conditions specific to diabetes.
Compared with patients whose prevalent diabetes is managed outside of primary care networks, patients in primary care networks had a lower rate of diabetes-specific ambulatory care sensitive conditions (adjusted incidence rate ratio 0.81, 95% confidence interval [CI] 0.75 to 0.87), were more likely to see an ophthalmologist or optometrist (risk ratio 1.19, 95% CI 1.17 to 1.21) and had better glycemic control (adjusted mean difference −0.067, 95% CI −0.081 to −0.052).
Patients whose diabetes was managed in primary care networks received better care and had better clinical outcomes than patients whose condition was not managed in a network, although the differences were very small.
PMCID: PMC3273535  PMID: 22143232
4.  Clinical and medication profiles stratified by household income in patients referred for diabetes care 
Low income individuals with diabetes are at particularly high risk for poor health outcomes. While specialized diabetes care may help reduce this risk, it is not currently known whether there are significant clinical differences across income groups at the time of referral. The objective of this study is to determine if the clinical profiles and medication use of patients referred for diabetes care differ across income quintiles.
This cross-sectional study was conducted using a Canadian, urban, Diabetes Education Centre (DEC) database. Clinical information on the 4687 patients referred to the DEC from May 2000 – January 2002 was examined. These data were merged with 2001 Canadian census data on income. Potential differences in continuous clinical parameters across income quintiles were examined using regression models. Differences in medication use were examined using Chi square analyses.
Multivariate regression analysis indicated that income was negatively associated with BMI (p < 0.0005) and age (p = 0.023) at time of referral. The highest income quintiles were found to have lower serum triglycerides (p = 0.011) and higher HDL-c (p = 0.008) at time of referral. No significant differences were found in HBA1C, LDL-c or duration of diabetes. The Chi square analysis of medication use revealed that despite no significant differences in HBA1C, the lowest income quintiles used more metformin (p = 0.001) and sulfonylureas (p < 0.0005) than the wealthy. Use of other therapies were similar across income groups, including lipid lowering medications. High income patients were more likely to be treated with diet alone (p < 0.0005).
Our findings demonstrate that low income patients present to diabetes clinic older, heavier and with a more atherogenic lipid profile than do high income patients. Overall medication use was higher among the lower income group suggesting that differences in clinical profiles are not the result of under-treatment, thus invoking lifestyle factors as potential contributors to these findings.
PMCID: PMC1852090  PMID: 17397550
5.  Association of socio-economic status with diabetes prevalence and utilization of diabetes care services 
Low income appears to be associated with a higher prevalence of diabetes and diabetes related complications, however, little is known about how income influences access to diabetes care. The objective of the present study was to determine whether income is associated with referral to a diabetes centre within a universal health care system.
Data on referral for diabetes care, diabetes prevalence and median household income were obtained from a regional Diabetes Education Centre (DEC) database, the Canadian National Diabetes Surveillance System (NDSS) and the 2001 Canadian Census respectively. Diabetes rate per capita, referral rate per capita and proportion with diabetes referred was determined for census dissemination areas. We used Chi square analyses to determine if diabetes prevalence or population rates of referral differed across income quintiles, and Poisson regression to model diabetes rate and referral rate in relation to income while controlling for education and age.
There was a significant gradient in both diabetes prevalence (χ2 = 743.72, p < 0.0005) and population rates of referral (χ2 = 168.435, p < 0.0005) across income quintiles, with the lowest income quintiles having the highest rates of diabetes and referral to the DEC. Referral rate among those with diabetes, however, was uniform across income quintiles. Controlling for age and education, Poisson regression models confirmed a significant socio-economic gradient in diabetes prevalence and population rates of referral.
Low income is associated with a higher prevalence of diabetes and a higher population rate of referral to this regional DEC. After accounting for diabetes prevalence, however, the equal proportions referred to the DEC across income groups suggest that there is no access bias based on income.
PMCID: PMC1618393  PMID: 17018153

Results 1-8 (8)