The Intelligent Dosing System: application for insulin therapy and diabetes management.

Diabetes mellitus is an increasing public health problem. Insulin is an essential tool in the management of hyperglycemia, but methods of dose adjustment are purely empirical. The Intelligent Dosing System (IDS, Dimensional Dosing Systems, Inc., Wexford, PA) is a software suite that incorporates patient-specific, dose-response data in a mathematical model and then calculates the new dose of the medication needed to achieve the next desired therapeutic goal. We discuss the application of the IDS in insulin management. The IDS concept and the initial modeling used to construct an insulin doser are reviewed first. Additional data are then provided on the use of the IDS for titrating insulin therapy in a clinical setting. Finally, recent modifications in the IDS software and future applications of this technology for insulin dosing and diabetes management are discussed.

Evolving demographics and disparities in an urban diabetes clinic: implications for diabetes education and treatment.

OBJECTIVES: To compare demographics and disease characteristics in a multiethnic diabetes clinic population to identify changes over time. DESIGN: Analysis and comparison of demographics and disease characteristics of diabetes patients, recorded electronically at intake over 10 years. SETTING: An urban outpatient diabetes clinic. PATIENTS: A total of 8,551 African-American (88%), White (7%), or Hispanic (3%) patients (average age, 52 years; mean diabetes duration, 5.1 years; 59% women). MAIN OUTCOME MEASURES: Proportion of patients by ethnic group, age, diabetes duration, initial hemoglobin A1c, and body mass index. RESULTS: Between 1992 and 2001, the percentage of African-American patients was relatively unchanged (from 87.6% to 87.2%; P=.2), White patients decreased (from 9% to 5%; P=.0006), and Hispanic patients increased (from 1.3% to 5.5%; P<.0001). Among African-American patients, average age decreased from 52 to 50 years (P=.015), diabetes duration decreased from 5.6 years to 4.3 years (P=.0003), initial hemoglobin A1c decreased from 9.3% to 8.8% (P<.0001), and body mass index increased from 31 kg/m2 to 32.1 kg/m2 (P=.0001). Compared with African-American and White patients, Hispanic patients were younger (P<.0001) and had a lower body mass index (P<.0001) but had hemoglobin A1c comparable to that of African-American patients (9.3% vs 9.1%; P=.45) and higher than that of White patients (9.3% vs 8.7%; P=.0022). CONCLUSIONS: The demographic and disease profiles of patients in this urban diabetes clinic have shifted, and disparities in glycemic control and obesity exist. Modifications in treatment and education approaches may be necessary to compensate for a changing patient population.

Management of insulin therapy in urban diabetes patients is facilitated by use of an intelligent dosing system.

The Intelligent Dosing System (IDS, Dimensional Dosing Systems, Inc., Wexford, PA) is a software suite that incorporates patient-specific, dose-response data in a mathematical model, and then calculates the new dose of agent needed to achieve the next desired therapeutic goal. We evaluated use of the IDS for titrating insulin therapy. The IDS was placed on handheld platforms and provided to practitioners to use in adjusting total daily insulin dose. Fasting glucose, random glucose, and hemoglobin A1c were used as markers against which insulin could be adjusted. Values of markers expected at the next follow-up visit, as predicted by the model, were compared with levels actually observed. For 264 patients, 334 paired visits were analyzed. Average age was 54 years, diabetes' duration was 10 years, and body mass index was 33.2 kg/m(2); 57% were female, 88% were African American, and 92% had type 2 diabetes. The correlation between IDS suggested and actual prescribed total daily dose was high (r = 0.99), suggesting good acceptability of the IDS by practitioners. Significant decreases in fasting glucose, random glucose, and hemoglobin A1c levels were seen (all P < 0.0001). No significant difference between average expected and observed follow-up fasting glucose values was found (145 vs. 149 mg/dL, P = 0.42), and correlation was high (r = 0.79). Mean observed random glucose value at follow-up was comparable to the IDS predicted level (167 vs. 168 mg/dL, P = 0.97), and correlation was high (r = 0.73). Observed follow-up hemoglobin A1c was higher than the value expected (7.9% vs. 7.4%, P < 0.0055), but correlation was good (r = 0.70). These analyses suggest the IDS is a useful adjunct for decisions regarding insulin therapy even when using a variety of markers of glucose control, and can be used by practitioners to assist in attainment of glycemic goals.