Improved Outcomes from Diabetes Monitoring: The Benefits of Better Adherence, Therapy Adjustments, Patient Education, and Telemedicine Support

Klonoff, David C.

doi:10.1177/193229681200600301

Cited by 29 publications

(27 citation statements)

References 26 publications

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“…These “smart” BGMs are also conceived to provide an electronic log book and to store information regarding insulin intake, food consumption, physical activity, and health information. They are sometimes engineered to transmit data to web databases where they are interpreted by specialized software systems [28]. …”

Section: Methodsmentioning

confidence: 99%

Glucose Meters with Built-In Automated Bolus Calculator: Gadget or Real Value for Insulin-Treated Diabetic Patients?

Colin¹,

Pâris²

2012

Diabetes Ther

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Self-monitoring of blood glucose is now widely recognized as efficacious to enhance and facilitate diabetes management. More than just a means of recording and storing data, some blood glucose meters (BGMs) are now designed with an embedded automated bolus calculator (ABC) with the goal to propose patients recommendations about insulin dosage. The growing literature in this field tends to claim that these new smart BGMs make patient’s life easier and decision making safer. The main purpose of this review is to verify whether BGMs with a built-in ABC indeed improve the willingness and the ability of insulin-treated patients to make adequate therapeutic decisions and positively impact the metabolic control and the quality of life of ABC users. It appears that, as long as the education provided by caregivers remains a top priority, BGMs with a built-in ABC (more than just electronic gadgets) can be regarded as bringing real value to insulin-treated patients with diabetes.

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Section: Methodsmentioning

confidence: 99%

Glucose Meters with Built-In Automated Bolus Calculator: Gadget or Real Value for Insulin-Treated Diabetic Patients?

Colin¹,

Pâris²

2012

Diabetes Ther

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“…These practices had shown inefficacy to self-management of diabetes and its complications as was illustrated in the study done in France: 'reporting by logbook was considered with doubtable efficacy since data could be wrongly filled, incorrectely recorded or delayed to be reported to clinicians'. [23] As a consequence, the clinician can intervene on wrongly findings or delay supporting the patients in a critical situation. [24] Indeed, automatic reporting home measurement using mobile phones could be enhanced instead of storing and forwarding system.…”

Section: Demographic Profilementioning

confidence: 99%

M-health tools utilization of tele-home healthcare services for diabetes management among youth in Kigali City

Uwimana¹,

Nyirandegeya²,

Nisingizwe³

2020

Rwanda Journal of Medicine and Health Sciences

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Background Self-care of diabetes for youth requires a daily self-active participation, which is complex and demanding. Effective patient engagement through technology tools may bring about compliance to healthcare 24 hours/ 7 days which minimises the diabetes complications and clinicians overload. Objective This study aimed to assess M-health tools utilization of tele-home healthcare services for diabetes management among youth in Kigali City. Method This cross-sectional study was conducted among the Rwanda Diabetes Association members. The study populations were youth diabetic patients residing in Kigali city. With simple random sampling, self-administered questionnaire was used to collect data for 122 participants. The raw data was entered into the Statistical Package for the Social Sciences (SPSS: 20) to perform descriptive and inferential statistics in data analysis. Results The mobile telephone is highly used in healthcare by participants (≥80%) with its functions such as Short Message Services, and the voice call is more useful (≥87%). Furthermore, occupation and education level of diabetic youth do not have significance influence (p=0.825 and p=0.751) over the use of a mobile telephone in healthcare. Radios and televisions are mostly used in healthcare education (93.5%). Conclusions Tele-home healthcare is practised in Rwanda but dominated by store and forward system. Mobile telephone, radio and television are mostly used whereas emails and social media are slowly used.

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“…[3][4][5] With the increasing prevalence of BG meters with advanced processing and display functionality, and technologies that transmit BG data to smartphone or cloud based systems in real time, there is an opportunity to develop an intelligent system that can overcome the above shortcomings.…”

Section: 3mentioning

confidence: 99%

“…2,3 These methods have several shortcomings, including (1) the limited characterization of the utility of the information provided and (2) the significant time and mental workload required to extract distinct patterns or other actionable information. [3][4][5] With the increasing prevalence of BG meters with advanced processing and display functionality, and technologies that transmit BG data to smartphone or cloud based systems in real time, there is an opportunity to develop an intelligent system that can overcome the above shortcomings.…”

mentioning

confidence: 99%

Evaluation of the Utility of a Glycemic Pattern Identification System

Otto

Tannan²

2014

J Diabetes Sci Technol

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For insulin-dependent diabetes patients and their care providers, the ability to quickly and efficiently identify deleterious patterns in blood glucose (BG) data can have a significant impact on improving diabetes management outcomes and quality of life.1,2 Standard tools for aiding in identifying patterns typically involve (1) paper log books or (2) software on a desktop computer, BG meter, or other handheld device. In the case of software, data logs may be accompanied by weekly averages or point charts, or more complex analytical tools in the form of modal days, percentage of readings in and out of a target range, or averages by diurnal time period. 2,3These methods have several shortcomings, including (1) the limited characterization of the utility of the information provided and (2) the significant time and mental workload required to extract distinct patterns or other actionable information. [3][4][5] With the increasing prevalence of BG meters with advanced processing and display functionality, and technologies that transmit BG data to smartphone or cloud based systems in real time, there is an opportunity to develop an intelligent system that can overcome the above shortcomings.There is support for the management of diurnal BG patterns with behavioral or treatment related interventions. 2,3,6,7 We are evaluating a novel system named Vigilant™ (investigational use software device from InSpark Technologies, Inc, Charlottesville, VA) that is designed to message users about diurnal patterns in upcoming daily time periods when the patient is testing, and to optimize the frequency of pattern messaging to within a desirable range. Patterns of hyperglycemia and hypoglycemia are identified if the product of the following exceeds a predetermined threshold: (1) the percentage of BG readings in a diurnal time period exceeding a clinical threshold and (2) the probability that the identified diurnal BG pattern is deviant relative to the rest of the patient's BG levels. This method, hereinafter referred to as "method 1," has been described in detail in a prior publication. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes.Method: To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows.Results: Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The syst...

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Improved Outcomes from Diabetes Monitoring: The Benefits of Better Adherence, Therapy Adjustments, Patient Education, and Telemedicine Support

Abstract: Abbreviations: (HbA1c) glycated hemoglobin, (BG) blood glucose, (CGM) continuous glucose monitoring, (FDA) Food and Drug Administration, (GPS) global positioning system, (SMBG) self-monitoring of blood glucose

Cited by 29 publications

References 26 publications

Glucose Meters with Built-In Automated Bolus Calculator: Gadget or Real Value for Insulin-Treated Diabetic Patients?

Glucose Meters with Built-In Automated Bolus Calculator: Gadget or Real Value for Insulin-Treated Diabetic Patients?

M-health tools utilization of tele-home healthcare services for diabetes management among youth in Kigali City

Evaluation of the Utility of a Glycemic Pattern Identification System

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