Dataset Information

Accuracy and User Performance Evaluation of a New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device.

ABSTRACT: The new Contour®Plus ONE blood glucose monitoring system (BGMS) features an easy-to-use, wireless-enabled blood glucose meter that links to a smart mobile device via Bluetooth® connectivity and can sync with the Contour™ Diabetes app on a smartphone or tablet.The accuracy of the new BGMS was assessed in 2 studies according to ISO 15197:2013 criteria. In Study 1 (laboratory study), fingertip capillary blood samples from 100 subjects were tested in duplicate using 3 test strip lots. In Study 2 (clinical study), 134 subjects with type 1 or type 2 diabetes enrolled at 2 clinical sites. BGMS results and YSI analyzer (YSI) reference results were compared for fingertip blood obtained by untrained subjects' self-testing and for study staff-obtained fingertip, subject palm, and venous results.In Study 1, 99.0% (594/600) of combined results for all 3 test strip lots fulfilled ISO 15197:2013 Section 6.3 accuracy criteria. In Study 2, 99.2% (133/134) of subject-obtained capillary fingertip results, 99.2% (133/134) of study staff-obtained fingertip results, 99.2% (125/126) of subject-obtained palm results, and 100% (132/132) of study staff-obtained venous results met ISO 15197:2013 Section 8 accuracy criteria. Moreover, 95.5% (128/134) of subject-obtained fingertip self-test results were within ±10 mg/dl (±0.6 mmol/L) or ±10% of the YSI reference result. Questionnaire results showed that most subjects found the BGMS easy to use.The BGMS exceeded ISO 15197:2013 accuracy criteria both in the laboratory and in a clinical setting when used by untrained subjects with diabetes.

SUBMITTER: Bailey TS

PROVIDER: S-EPMC5588817 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Accuracy and User Performance Evaluation of a New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device.

Bailey Timothy S TS Wallace Jane F JF Pardo Scott S Warchal-Windham Mary Ellen ME Harrison Bern B Morin Robert R Christiansen Mark M

Journal of diabetes science and technology 20170201 4

<h4>Background</h4>The new Contour<sup>®</sup>Plus ONE blood glucose monitoring system (BGMS) features an easy-to-use, wireless-enabled blood glucose meter that links to a smart mobile device via Bluetooth<sup>®</sup> connectivity and can sync with the Contour<sup>™</sup> Diabetes app on a smartphone or tablet.<h4>Methods</h4>The accuracy of the new BGMS was assessed in 2 studies according to ISO 15197:2013 criteria. In Study 1 (laboratory study), fingertip capillary blood samples from 100 subje ...[more]

PMID: 28617617

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Project description:BackgroundThe Smart Angel home medical device allows ambulatory surgery patients to monitor their own health by taking their blood pressure and oxygen levels and answering a health questionnaire from home. Currently, this device is a prototype in the design phase, and no usability evaluation has been performed. This preventive device must be usable by patients with different profiles; however, it is important to select patients carefully to ensure their safety when using the device. As such, it would be interesting to know how to select or exclude patients. However, the links between user characteristics and the usability of this home medical device remain unclear.ObjectiveThis study aims to better understand the links between certain characteristics of potential patients (ie, age, education, technophilia, and health literacy) and the usability (ie, effectiveness, efficiency, and satisfaction) of Smart Angel, as defined by the ISO 9241-11.MethodsWe conducted an experimental study involving 36 participants investigating the effects of 4 patient characteristics (ie, age, education, technophilia, and health literacy) on usability, measured in terms of effectiveness, efficiency, and satisfaction. A mixed methods approach (subjective vs objective) using a variety of standard instruments was adopted (direct observation, video analysis, and questionnaires). First, to help participants project themselves into the real use of the Smart Angel device, they watched a scenario in a video. Second, the participants completed a set of questionnaires to show the extent of their health literacy level (Newest Vital Sign [NVS] and the Health Literacy Survey [HLS]) and then operated Smart Angel devices. Efficiency (ie, handling time) and effectiveness (ie, number of handling errors) measures were collected by video analysis. Satisfaction measures were collected by a questionnaire (System Usability Scale [SUS]). The qualitative observational data were coded using inductive analysis by 2 independent researchers specialized in cognitive psychology and cognitive ergonomics.ResultsThe results show a moderate and positive correlation between age and effectiveness (r=0.359; P=.03) and efficiency (r=0.357; P=.03). There is strong correlation between health literacy scored by the NVS and effectiveness (r=0.417; P=.01), efficiency (r=-0.38; P=.02), and satisfaction (r=0.45; P=.006). However, there is a weak correlation between technophilia and usability and no relationship between education level and usability.ConclusionsOur results show that literacy level and age are 2 important factors to consider when selecting future users of the Smart Angel device to ensure patient safety. This study also serves as an example promoting mixed methodologies in assessments of medical device usability that cannot be performed under real-world conditions.

Project description:BackgroundAtrial fibrillation (AF) is the most common tachyarrhythmia and associated with a risk of stroke. The detection and diagnosis of AF represent a major clinical challenge due to AF's asymptomatic and intermittent nature. Novel consumer-grade mobile health (mHealth) products with automatic arrhythmia detection could be an option for long-term electrocardiogram (ECG)-based rhythm monitoring and AF detection.ObjectiveWe evaluated the feasibility and accuracy of a wearable automated mHealth arrhythmia monitoring system, including a consumer-grade, single-lead heart rate belt ECG device (heart belt), a mobile phone application, and a cloud service with an artificial intelligence (AI) arrhythmia detection algorithm for AF detection. The specific aim of this proof-of-concept study was to test the feasibility of the entire sequence of operations from ECG recording to AI arrhythmia analysis and ultimately to final AF detection.MethodsPatients (n=159) with an AF (n=73) or sinus rhythm (n=86) were recruited from the emergency department. A single-lead heart belt ECG was recorded for 24 hours. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics and as a reference device in a user experience survey with patients over 65 years of age (high-risk group).ResultsThe heart belt provided a high-quality ECG recording for visual interpretation resulting in 100% accuracy, sensitivity, and specificity of AF detection. The accuracy of AF detection with the automatic AI arrhythmia detection from the heart belt ECG recording was also high (97.5%), and the sensitivity and specificity were 100% and 95.4%, respectively. The correlation between the automatic estimated AF burden and the true AF burden from Holter recording was >0.99 with a mean burden error of 0.05 (SD 0.26) hours. The heart belt demonstrated good user experience and did not significantly interfere with the patient's daily activities. The patients preferred the heart belt over Holter ECG for rhythm monitoring (85/110, 77% heart belt vs 77/109, 71% Holter, P=.049).ConclusionsA consumer-grade, single-lead ECG heart belt provided good-quality ECG for rhythm diagnosis. The mHealth arrhythmia monitoring system, consisting of heart-belt ECG, a mobile phone application, and an automated AF detection achieved AF detection with high accuracy, sensitivity, and specificity. In addition, the mHealth arrhythmia monitoring system showed good user experience.Trial registrationClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335.

Dataset Information

Accuracy and User Performance Evaluation of a New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device.

Publications

Accuracy and User Performance Evaluation of a New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device.

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