Seamless recording of glucometer measurements among older experienced diabetic patients – A study of perception and usability

Self-measurement and documentation of blood-glucose are critical elements of diabetes management, particularly in regimes including insulin. In this study, we analyze the usability of iBG-STAR, the first blood glucose meter connectable to a smartphone. This technology records glucometer measurements, removing the burden of documentation from diabetic patients. This study assesses the potential for implementation of iBG-STAR in routine care. Twelve long-term diabetic patients (4 males; median age of 66.5 years) were enrolled in the study. N = 4/12 reported diabetic polyneuropathy. Reported subjective mental workload for all tasks related to iBG-STAR was on average lower than 12 points, corresponding to the verbal code ‘nearly no effort needed’. A “Post Study System Usability Questionnaire”, evaluated the glucometer at an average value of 2.06 (SD = 1.02) on a 7-Likert-scale (1 = ‘I fully agree’ to 7 = ‘I completely disagree’) for usability. These results represent a positive user-experience. Patients with polyneuropathy may experience physical difficulties in completing the tasks, thereby affecting usability. Technologically savvy patients (n = 6) with a positive outlook on diabetes assessed the product as a suitable tool for themselves and would recommend to other diabetic patients. The main barrier to regular use was treating physicians’ inability to retrieve digitally recorded data. This barrier was due to a shortcoming in interoperability of mobile devices and medical information systems.

[1]  J. Sandberg,et al.  The think aloud method , 1994 .

[2]  Tana M Luger,et al.  Older Adult Experience of Online Diagnosis: Results From a Scenario-Based Think-Aloud Protocol , 2014, Journal of medical Internet research.

[3]  F. Ferris,et al.  New visual acuity charts for clinical research. , 1982, American journal of ophthalmology.

[4]  C. Schlick,et al.  A mobile application improves therapy-adherence rates in elderly patients undergoing rehabilitation , 2016, Medicine.

[5]  Urs-Vito Albrecht,et al.  mHealth 2.0: Experiences, Possibilities, and Perspectives , 2014, JMIR mHealth and uHealth.

[6]  Lorenz Uhlmann,et al.  A Personal Electronic Health Record: Study Protocol of a Feasibility Study on Implementation in a Real-World Health Care Setting , 2017, JMIR research protocols.

[7]  Martin F Mendiola,et al.  Valuable Features in Mobile Health Apps for Patients and Consumers: Content Analysis of Apps and User Ratings , 2015, JMIR mHealth and uHealth.

[8]  A. Haines,et al.  The Effectiveness of Mobile-Health Technologies to Improve Health Care Service Delivery Processes: A Systematic Review and Meta-Analysis , 2013, PLoS medicine.

[9]  J. Car,et al.  Smartphone Versus Pen-and-Paper Data Collection of Infant Feeding Practices in Rural China , 2012, Journal of medical Internet research.

[10]  G. Jay,et al.  Influence of direct computer experience on older adults' attitudes toward computers. , 1992, Journal of gerontology.

[11]  Eric Renard,et al.  Monitoring glycemic control: the importance of self-monitoring of blood glucose. , 2005, The American journal of medicine.

[12]  L. Piwek,et al.  The Rise of Consumer Health Wearables: Promises and Barriers , 2016, PLoS medicine.

[13]  Alexander Mertens,et al.  Use of Information and Communication Technology in Healthcare Context by Older Adults in Germany: Initial Results of the Tech4Age Long-Term Study , 2017, i-com.

[14]  M. O'Kane,et al.  Efficacy of self monitoring of blood glucose in patients with newly diagnosed type 2 diabetes (ESMON study): randomised controlled trial , 2008, BMJ : British Medical Journal.

[15]  Wilhelm Kirch,et al.  Acceptance Factors of Mobile Apps for Diabetes by Patients Aged 50 or Older: A Qualitative Study , 2015, Medicine 2.0.

[16]  Renu Joshi,et al.  Improving adherence and outcomes in diabetic patients , 2017, Patient preference and adherence.

[17]  Jeff Sauro,et al.  Quantifying the User Experience: Practical Statistics for User Research , 2012 .

[18]  Jae-Hyoung Cho,et al.  Mobile communication using a mobile phone with a glucometer for glucose control in Type 2 patients with diabetes: as effective as an Internet-based glucose monitoring system , 2009, Journal of telemedicine and telecare.

[19]  H. Parihar,et al.  iOS Appstore-Based Phone Apps for Diabetes Management: Potential for Use in Medication Adherence , 2017, JMIR diabetes.

[20]  B. Shi,et al.  Information and Communication Technology-Powered Diabetes Self-Management Systems in China: A Study Evaluating the Features and Requirements of Apps and Patents , 2016, JMIR diabetes.

[21]  A. Edwards,et al.  Smartphone App Use for Diabetes Management: Evaluating Patient Perspectives , 2017, JMIR diabetes.

[22]  Brian Godman,et al.  Efficacy of Mobile Apps to Support the Care of Patients With Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials , 2017, JMIR mHealth and uHealth.

[23]  Maarten van Someren,et al.  The Think Aloud Method: A Practical Guide to Modelling Cognitive Processes , 1994 .

[24]  Simon Watts,et al.  ‘It’s not a disease, it’s a nuisance’: Controlling diabetes and achieving goals in the context of men with Type 1 diabetes , 2013, Psychology & health.

[25]  Tobias Otto,et al.  Neural correlates of mental effort evaluation--involvement of structures related to self-awareness. , 2014, Social cognitive and affective neuroscience.

[26]  Christopher G Parkin,et al.  Value of Self-Monitoring Blood Glucose Pattern Analysis in Improving Diabetes Outcomes , 2009, Journal of diabetes science and technology.

[27]  S. Shiffman,et al.  Patient compliance with paper and electronic diaries. , 2003, Controlled clinical trials.

[28]  O. Dale,et al.  Despite technical problems personal digital assistants outperform pen and paper when collecting patient diary data. , 2007, Journal of clinical epidemiology.

[29]  In Young Choi,et al.  Efficacy of the Smartphone-Based Glucose Management Application Stratified by User Satisfaction , 2014, Diabetes & metabolism journal.

[30]  G. Rutten,et al.  Patients’ Experiences with and Attitudes towards a Diabetes Patient Web Portal , 2015, PloS one.

[31]  C. Mathers,et al.  Projections of Global Mortality and Burden of Disease from 2002 to 2030 , 2006, PLoS medicine.

[32]  Chandra Y Osborn,et al.  One Drop | Mobile: An Evaluation of Hemoglobin A1c Improvement Linked to App Engagement , 2017, JMIR diabetes.

[33]  F.R.H. Zijlstra,et al.  Efficiency in work behaviour: A design approach for modern tools , 1993 .

[34]  S. Söderberg,et al.  Telemonitoring and Health Counseling for Self-Management Support of Patients With Type 2 Diabetes: A Randomized Controlled Trial , 2017, JMIR diabetes.

[35]  Andreas Pfützner,et al.  Clinical assessment of the accuracy of blood glucose measurement devices , 2012, Current medical research and opinion.