A longitudinal study into the new and long-term use of self-monitoring blood glucose strips in the UK

Aims To determine the impact of self-monitoring blood glucose (SMBG) strip use in patients with type 2 diabetes in the UK. Methods The study period was April 1, 2004 to July 31, 2005. Data from primary care was extracted from The Health Improvement Network database. Patients identified with diabetes and matching the inclusion criteria were defined as new users of SMBG, prevalent users, or non-users. Patients were also defined as treated with insulin, with oral agents (OA), or not pharmacologically treated. Change in glycosylated hemoglobin (HbA1c) at baseline and after 12 months was compared. Results 2559 patients met the inclusion criteria. For new users, HbA1c fell by 0.59% (P=0.399) for those treated with insulin, 1.52% (P<0.001) for those treated with OA, and 0.51% (P<0.001) for no treatment. In prevalent users, changes were 0.31% (P<0.001), 0.34% (P<0.001), and 0.09% (P=0.456), respectively. In non-users, changes were 0.28% (P=0.618), 0.42% (P<0.001), and an increase of 0.05% (P=0.043), respectively. A significant decrease in mean HbA1c was associated with increasing strip use in OA patients newly initiated on strips. Conclusion This observational study showed a significant decrease in HbA1c for new users of SMBG treated either non-pharmacologically or with OA, and for prevalent users treated with insulin or OA. Reduced HbA1c with increasing strip use was observed but was only significant for OA-treated new users. This suggests that SMBG use has a role in the treatment of non-insulin treated patients with type 2 diabetes

Food insecurity, food "deserts," and glycemic control in patients with diabetes: A longitudinal analysis

OBJECTIVE Both food insecurity (limited food access owing to cost) and living in areas with low physical access to nutritious foods are public health concerns, but their relative contribution to diabetes management is poorly understood. RESEARCH DESIGN AND METHODS This was a prospective cohort study. A random sample of patients with diabetes in a primary care network completed food insecurity assessment in 2013. Low physical food access at the census tract level was defined as no supermarket within 1 mile in urban areas and 10 miles in rural areas. HbA1c measurements were obtained from electronic health records through November 2016. The relationship among food insecurity, low physical food access, and glycemic control (as defined by HbA1c) was analyzed using hierarchical linear mixed models. RESULTS Three hundred and ninety-one participants were followed for a mean of 37 months. Twenty percent of respondents reported food insecurity, and 31% resided in an area of low physical food access. In adjusted models, food insecurity was associated with higher HbA1c (difference of 0.6%[6.6mmol/mol], 95% CI 0.4-0.8[4.4-8.7],P&lt;0.0001), which did not improve over time (P = 0.50). Living in an area with low physical food access was not associated with a difference in HbA1c (difference 0.2%[2.2mmol/mol], 95% CI 20.2 to 0.5 [22.2 to 5.6], P = 0.33) or with change over time (P = 0.07). CONCLUSIONS Food insecurity is associated with higher HbA1c, but living in an area with low physical food access is not. Food insecurity screening and interventions may help improve glycemic control for vulnerable patients

Treatment intensification and risk factor control: toward more clinically relevant quality measures.

BACKGROUND: Intensification of pharmacotherapy in persons with poorly controlled chronic conditions has been proposed as a clinically meaningful process measure of quality. OBJECTIVE: To validate measures of treatment intensification by evaluating their associations with subsequent control in hypertension, hyperlipidemia, and diabetes mellitus across 35 medical facility populations in Kaiser Permanente, Northern California. DESIGN: Hierarchical analyses of associations of improvements in facility-level treatment intensification rates from 2001 to 2003 with patient-level risk factor levels at the end of 2003. PATIENTS: Members (515,072 and 626,130; age &gt;20 years) with hypertension, hyperlipidemia, and/or diabetes mellitus in 2001 and 2003, respectively. MEASUREMENTS: Treatment intensification for each risk factor defined as an increase in number of drug classes prescribed, of dosage for at least 1 drug, or switching to a drug from another class within 3 months of observed poor risk factor control. RESULTS: Facility-level improvements in treatment intensification rates between 2001 and 2003 were strongly associated with greater likelihood of being in control at the end of 2003 (P &lt; or = 0.05 for each risk factor) after adjustment for patient- and facility-level covariates. Compared with facility rankings based solely on control, addition of percentages of poorly controlled patients who received treatment intensification changed 2003 rankings substantially: 14%, 51%, and 29% of the facilities changed ranks by 5 or more positions for hypertension, hyperlipidemia, and diabetes, respectively. CONCLUSIONS: Treatment intensification is tightly linked to improved control. Thus, it deserves consideration as a process measure for motivating quality improvement and possibly for measuring clinical performance

Treatment intensification and risk factor control: toward more clinically relevant quality measures.

BACKGROUND: Intensification of pharmacotherapy in persons with poorly controlled chronic conditions has been proposed as a clinically meaningful process measure of quality. OBJECTIVE: To validate measures of treatment intensification by evaluating their associations with subsequent control in hypertension, hyperlipidemia, and diabetes mellitus across 35 medical facility populations in Kaiser Permanente, Northern California. DESIGN: Hierarchical analyses of associations of improvements in facility-level treatment intensification rates from 2001 to 2003 with patient-level risk factor levels at the end of 2003. PATIENTS: Members (515,072 and 626,130; age &gt;20 years) with hypertension, hyperlipidemia, and/or diabetes mellitus in 2001 and 2003, respectively. MEASUREMENTS: Treatment intensification for each risk factor defined as an increase in number of drug classes prescribed, of dosage for at least 1 drug, or switching to a drug from another class within 3 months of observed poor risk factor control. RESULTS: Facility-level improvements in treatment intensification rates between 2001 and 2003 were strongly associated with greater likelihood of being in control at the end of 2003 (P &lt; or = 0.05 for each risk factor) after adjustment for patient- and facility-level covariates. Compared with facility rankings based solely on control, addition of percentages of poorly controlled patients who received treatment intensification changed 2003 rankings substantially: 14%, 51%, and 29% of the facilities changed ranks by 5 or more positions for hypertension, hyperlipidemia, and diabetes, respectively. CONCLUSIONS: Treatment intensification is tightly linked to improved control. Thus, it deserves consideration as a process measure for motivating quality improvement and possibly for measuring clinical performance

Therapy modifications in response to poorly controlled hypertension, dyslipidemia, and diabetes mellitus.

BACKGROUND: Poorly controlled cardiovascular risk factors are common. Evaluating whether physicians respond appropriately to poor risk factor control in patients may better reflect quality of care than measuring proportions of patients whose conditions are controlled. OBJECTIVES: To evaluate therapy modifications in response to poor control of hypertension, dyslipidemia, or diabetes in a large clinical population. DESIGN: Retrospective cohort study within an 18-month period in 2002 to 2003. SETTING: Kaiser Permanente of Northern California. PATIENTS: 253,238 adult members with poor control of 1 or more of these conditions. MEASUREMENTS: The authors assessed the proportion of patients with poor control who experienced a change in pharmacotherapy within 6 months, and they defined "appropriate care" as a therapy modification or return to control without therapy modification within 6 months. RESULTS: A total of 64% of patients experienced modifications in therapy for poorly controlled systolic blood pressure, 71% for poorly controlled diastolic blood pressure, 56% for poorly controlled low-density lipoprotein cholesterol level, and 66% for poorly controlled hemoglobin A1c level. Most frequent modifications were increases in number of drug classes (from 70% to 84%) and increased dosage (from 15% to 40%). An additional 7% to 11% of those with poorly controlled blood pressure, but only 3% to 4% of those with elevated low-density lipoprotein cholesterol level or hemoglobin A1c level, returned to control without therapy modification. Patients with more than 1 of the 3 conditions, higher baseline values, and target organ damage were more likely to receive "appropriate care." LIMITATIONS: Patient preferences and suboptimal adherence to therapy were not measured and may explain some failures to act. CONCLUSIONS: As an additional measure of the quality of care, measuring therapy modifications in response to poor control in a large population is feasible. Many patients with poorly controlled hypertension, dyslipidemia, or diabetes had their therapy modified and, thus, seemed to receive clinically "appropriate care" with this new quality measure