Efficacy, safety and cost-effectiveness comparison between U-100 human regular insulin and rapid acting insulin when delivered by V-Go wearable insulin delivery device in type 2 diabetes.

INTRODUCTION: We compared the efficacy and safety of human regular insulin (HRI) versus rapid-acting insulin (RAI) in a type 2 diabetes population already using the V-Go insulin delivery device. RESEARCH DESIGN AND METHODS: This was a 14-week, multicenter, randomized, open-label, parallel-group, phase IV, non-inferiority study. Patients ≥21years of age, with inadequately controlled type 2 diabetes who were currently using the V-Go insulin delivery system with RAI, with glycated hemoglobin (HbA1c) ≥6.5% (≥48 mmol/L) to ≤12.5% (≤108 mmol/L) were randomized 1:1 to RAI continuation or switch to HRI. The primary outcome was estimated treatment difference (ETD) in HbA1c least-squares mean change from baseline at 14 weeks (prespecified non-inferiority hypothesis with 95% CI upper limit <0.4%). Primary analysis was by per protocol (PP); safety analysis was by intention to treat. RESULTS: We randomized 136 patients to continued RAI treatment (n=67) or HRI (n=69); 113 patients were included in the PP analysis (RAI, n=54; HRI, n=59). Mean change in HbA1c from baseline to study end was -0.60±1.1% (95% CI -0.90 to -0.29); -6.6±12.0 mmol/mol (95% CI -9.8 to -3.2) with HRI treatment and -0.38±1.3% (95% CI -0.70 to -0.05); -4.2±14.2 mmol/mol (95% CI -7.7 to -0.5) with RAI treatment, with ETD of -0.22% (95% CI -0.67 to 0.22); -2.4 mmol/mol (95% CI -7.3 to 2.4), p=0.007, confirming non-inferiority of HRI to RAI. No between-group differences in changes in total daily insulin doses, number of hypoglycemic values (≤70 mg/dL (≤39 mmol/L) or body weight were observed. No severe hypoglycemic events were reported. Direct pharmacy cost savings (-US$265.85; 95% CI -US$288.60 to -US$243.11; p<0.0001) were observed with HRI treatment. CONCLUSIONS: Individuals with type 2 diabetes requiring insulin can be treated with V-Go wearable insulin delivery device using HRI, safely and effectively, and potentially at a much lower cost compared with RAI, which can lead to improved access to insulin therapy for these individuals. TRIAL REGISTRATION NUMBER: NCT03495908.

A novel endocrinology-based wellness program to reduce medication expenditures and improve glycemic outcomes.

AIMS: The purpose of this study was to determine the difference in diabetes-related medication expenditures as a result of a 16-week lifestyle intervention program. Medical expenditures for patients with diabetes are twice as high compared to patients without this condition. Secondary objectives were changes in HbA1C, BMI, weight, body fat, and program satisfaction. METHODS: The Wellness Life! Program includes educational sessions focused on nutrition, fitness, and behavioral therapy. Medication costs were based on Average Wholesale Prices, tabulated from the 2010 Red Book. RESULTS: A total of 36 patients (49-80 years old) enrolled, of which 27 patients have diabetes mellitus (Type 2=26, Type 1=1). Mean 30-day anti-diabetic medication costs decreased by $142.92. Clinical mean parameters improved in both the overall group and the diabetic subgroup, respectively: HbA1C (%) -0.69, -0.82; weight (lbs) -16.94, -17.11; BMI -2.73, -2.88; and body fat (%) -1.71, -1.79. Participants were generally satisfied with the program. CONCLUSIONS: Employing a multidisciplinary wellness program within an endocrinology practice can reduce anti-diabetic medication expenses; however, long term follow-up is needed to determine if medication reductions and improved clinical parameters persist.

Evaluation of PROforma as a language for implementing medical guidelines in a practical context.

BACKGROUND: PROforma is one of several languages that allow clinical guidelines to be expressed in a computer-interpretable manner. How these languages should be compared, and what requirements they should meet, are questions that are being actively addressed by a community of interested researchers. METHODS: We have developed a system to allow hypertensive patients to be monitored and assessed without visiting their GPs (except in the most urgent cases). Blood pressure measurements are performed at the patients' pharmacies and a web-based system, created using PROforma, makes recommendations for continued monitoring, and/or changes in medication. The recommendations and measurements are transmitted electronically to a practitioner with authority to issue and change prescriptions. We evaluated the use of PROforma during the knowledge acquisition, analysis, design and implementation of this system. The analysis focuses on the logical adequacy, heuristic power, notational convenience, and explanation support provided by the PROforma language. RESULTS: PROforma proved adequate as a language for the implementation of the clinical reasoning required by this project. However a lack of notational convenience led us to use UML activity diagrams, rather than PROforma process descriptions, to create the models that were used during the knowledge acquisition and analysis phases of the project. These UML diagrams were translated into PROforma during the implementation of the project. CONCLUSION: The experience accumulated during this study highlighted the importance of structure preserving design, that is to say that the models used in the design and implementation of a knowledge-based system should be structurally similar to those created during knowledge acquisition and analysis. Ideally the same language should be used for all of these models. This means that great importance has to be attached to the notational convenience of these languages, by which we mean the ease with which they can be read, written, and understood by human beings. The importance of notational convenience arises from the fact that a language used during knowledge acquisition and analysis must be intelligible to the potential users of a system, and to the domain experts who provide the knowledge that will be used in its construction.

The syntax and semantics of the PROforma guideline modeling language.

PROforma is an executable process modeling language that has been used successfully to build and deploy a range of decision support systems, guidelines, and other clinical applications. It is one of a number of recent proposals for representing clinical protocols and guidelines in a machine-executable format (see ). In this report, the authors outline the task model for the language and provide an operational semantics for process enactment together with a semantics for expressions, which may be used to query the state of a task during enactment. The operational semantics includes a number of public operations that may be performed on an application by an external agent, including operations that change the values of data items, recommend or make decisions, manage tasks that have been performed, and perform any task state changes that are implied by the current state of the application. Disclosure: PROforma has been used as the basis of a commercial decision support and guideline technology Arezzo (Infermed, London, UK; details in text).