Blood glucose self-monitoring and internet diabetes management on A1C outcomes in patients with type 2 diabetes.

OBJECTIVES: The purpose of this study was to determine any correlation between frequency of self-monitoring of blood glucose (SMBG), frequency of patient-provider communication of SMBG (reporting), and hemoglobin A1C for patients with non-insulin-dependent diabetes solely on oral medications. RESEARCH DESIGN AND METHODS: 191 charts of patients with type 2 diabetes treated solely with oral hypoglycemic agents were reviewed retrospectively. A1C, SMBG frequency, and frequency of online communication with an endocrinologist within the most recent 6-month period were used in the analyses. Regression analysis was used to determine correlations to A1C. For subsequent subgroup analysis, patients were separated into infrequent and frequent SMBG groups, defined as those who test on average once or less per day or twice or more per day. RESULTS: Although testing frequency did not correlate with A1C, higher reporting frequency correlated with lower A1C. Subgroup analysis of the frequent SMBG group showed a significantly lower A1C in frequent reporters when compared to infrequent reporters (N=118, p<0.05). This trend was not observed in the infrequent SMBG group (N=73, p=0.161). CONCLUSIONS: The inverse correlation between reporting frequency and A1C, as well as the significant difference in A1C only for the frequent testers, suggests that frequent SMBG has an effect on reducing A1C only when combined with regular, frequent communication of SMBG with a healthcare provider.

Determining starting basal rates of insulin infusion for insulin pump users: a comparison between methods.

OBJECTIVE: We aimed to assess the accuracy and safety of presently available methods of estimating starting basal insulin rates for patients with type 1 and 2 diabetes, and to compare them against an empirically derived standard basal rate and a newly developed regression formula. RESEARCH DESIGN AND METHODS: Data on 61 patients with type 1 diabetes on continuous subcutaneous insulin infusion (CSII) therapy and 34 patients with type 2 diabetes on CSII were reviewed. Patient data were first analyzed for correlations between initial patient parameters and final basal rates. Starting basal rates were then retrospectively calculated for these patients according to the weight-based method (WB-M), the total daily dose (TDD) of insulin method (TDD-M), a flat empiric value, and a new formula developed by regression analysis of clinical data. These 4 methods were subsequently compared in their accuracy and potential risk of hypoglycemia. RESULTS: For type 1 diabetes, patient weight and TDD of long-acting insulin correlated with final basal rates. Both the regression formula and the TDD-M appeared safer than the WB-M and empirical estimates. For type 2 diabetes, only patient TDD of long-acting insulin correlated with final basal rates. The regression formula was significantly more accurate for patients with type 2 diabetes overall, but the TDD-M estimate was marginally safer. CONCLUSIONS: The pre-existing TDD-M was found to be the safest presently recommended estimate of initial basal rates for pump initiation in both type 1 and 2 diabetes. The best-fit regression was found to have potential use for type 2 CSII initiation.

Cost-benefit analysis of internet therapeutic intervention on patients with diabetes.

BACKGROUND: With the emergence of IBGMS for allowing for patients to communicate their self-monitored blood glucose (SMBG) readings with their health care providers, their impact on the management of diabetes is becoming well-supported with regards to clinical benefits. Their impact on healthcare costs, however, has yet to be investigated. This study aims to determine the cost-benefits of such interventions in comparison to routine care. OBJECTIVES: To analyze the cost-benefit of an Internet Blood Glucose Monitoring Service (IBGMS) in comparison to routine diabetes care. PATIENTS AND METHODS: 200 patients were surveyed to assess the cost associated with doctor appointments in the past 12 months. Annual number of visits to medical services for diabetes and costs of transportation, parking, and time taken off work for visits were surveyed. Self-reported frequency of SMBG and most recent A1C were also surveyed. We compared 100 patients who used the IBGMS with 100 patients who only used routine care. RESULTS: There is a trend of lowered total cost in the intervention group compared to the control group. The control group spent $210.89 per year on visits to physicians; the intervention group spent $131.26 (P = 0.128). Patients in control group visited their endocrinologist 1.76 times per year, those in intervention group visited their endocrinologist 1.36 times per year, significantly less frequently than the control group (P = 0.014). Number of visits to other medical services is similar between the groups. Average A1C in intervention group is 7.57%, in control group is 7.69% (P = 0.309). CONCLUSIONS: We have demonstrated that IBGMS, while not reaching statistical significance, may be associated with slightly reduced A1C and cost due to visiting physicians.